From 7f32f2d0bf45035315502330bae8abba383af479 Mon Sep 17 00:00:00 2001
From: tinaok <tinaok@users.noreply.github.com>
Date: Tue, 31 Oct 2023 16:10:25 +0000
Subject: [PATCH] deploy: fbf3f072eae7604546c627bd60419e2c3bd5cc64

---
 _images/chunked.png                         |  Bin 17266 -> 0 bytes
 _images/datasize.png                        |  Bin 271359 -> 269974 bytes
 _images/notchunked.png                      |  Bin 11446 -> 0 bytes
 _sources/part3/chunking_introduction.ipynb  |  553 +-
 _sources/part3/scaling_dask.ipynb           |   12 +-
 part1/visualization.html                    |   10 +-
 part1/xarray_pitfalls.html                  |  170 +-
 part3/chunking_introduction.html            | 7975 +------------------
 part3/data_exploitability_pangeo.html       |   24 +-
 part3/scaling_dask.html                     |  147 +-
 reports/part3/chunking_introduction.err.log |   31 +
 searchindex.js                              |    2 +-
 12 files changed, 1009 insertions(+), 7915 deletions(-)
 delete mode 100644 _images/chunked.png
 delete mode 100644 _images/notchunked.png
 create mode 100644 reports/part3/chunking_introduction.err.log

diff --git a/_images/chunked.png b/_images/chunked.png
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diff --git a/_sources/part3/chunking_introduction.ipynb b/_sources/part3/chunking_introduction.ipynb
index 13d561a..6065231 100644
--- a/_sources/part3/chunking_introduction.ipynb
+++ b/_sources/part3/chunking_introduction.ipynb
@@ -95,351 +95,552 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d1f4818f-2b6b-44c1-af77-97daf8a1c2a1",
+   "id": "97eb32e7-cb5f-47cd-be1b-ec668266bec5",
    "metadata": {},
    "source": [
-    "## Global LTS\n",
+    "## title here\n",
     "\n",
-    "In the previous episode, we used Long Term statistics time-series for the region of Lombardy e.g. a very small area. Now we would like to use the original dataset that has a global coverage. Let us first open a single file (for January 1999-2019) to understand how much larger the global dataset is."
+    "we are ..."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b4a418ed-c764-4577-803c-a6947db16966",
-   "metadata": {},
+   "id": "2ab40279-d857-437d-9405-3a0dfc9aa5ca",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
-    "import fsspec\n",
-    "import s3fs\n",
-    "import xarray as xr"
+    "import pystac_client\n",
+    "import geopandas as gpd\n",
+    "from shapely.geometry import mapping\n",
+    "import stackstac\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\")"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "32bdead9-5f24-442e-93bf-715068fd330b",
+   "id": "85914868-6215-43ae-88d2-fbec027f9e0a",
    "metadata": {},
    "outputs": [],
    "source": [
-    "fs = s3fs.S3FileSystem(anon=True,\n",
-    "      client_kwargs={\n",
-    "         'endpoint_url': 'https://object-store.cloud.muni.cz'\n",
-    "      })"
+    "%%time\n",
+    "aoi = gpd.read_file('data/catchment_outline.geojson', crs=\"EPGS:4326\")\n",
+    "aoi_geojson = mapping(aoi.iloc[0].geometry)\n",
+    "URL = \"https://earth-search.aws.element84.com/v1\"\n",
+    "catalog = pystac_client.Client.open(URL)\n",
+    "items = catalog.search(\n",
+    "    intersects=aoi_geojson,\n",
+    "    collections=[\"sentinel-2-l2a\"],\n",
+    "    datetime=\"2019-02-01/2019-06-10\"\n",
+    ").item_collection()\n",
+    "sentinel2_l2a = stackstac.stack(items)\n"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f9a41ca7-ccd2-4223-ae15-d4119d7657cd",
-   "metadata": {},
+   "id": "8fc5711c-669d-418c-a0e4-f8e0beb8b6b7",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
-    "s3path = 's3://foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1221_GLOBE_VGT-PROBAV_V3.0.1.nc'"
+    "sentinel2_l2a"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f05d2938-d0ea-41fe-b32c-af81a8055416",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## What is a __chunk__\n",
+    "\n",
+    "If you look carefully to `sentinel2_l2a`,  xarray.DataArray is a `dask.array` with a chunk size of `(1, 1, 1024, 1024)`. The full data would load arrays of dimensions `(101, 32, 20982, 10980)`, 746 592 of the 'chunk', in total 5.42 TiB into the computer's RAM.  \n",
+    "\n",
+    "We can see the Dask Array information by clicking the icon as circled blue in the image below.\n",
+    "\n",
+    "![Dask.array](../figures/datasize.png)\n",
+    "\n",
+    "By clicking Red circled triangle icon, we can have detailed informations on the xarray, such as Coordinates, Indexes and Attributes.   \n",
+    "\n",
+    "When you create Xarray object using stackstac, we can easily turns STAC collection into a lazy xarray.DataArray, in chunk form, so then it is backed by dask. \n",
+    "\n",
+    "The size and shape of chunk which we will use defines the parallelisation done by Dask, thus Picking a good chunksize will have significant effects on performance.  \n",
+    "\n",
+    "\n",
+    "This is where understanding and using chunking correctly comes into play.\n",
+    "\n",
+    " \n"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "7d25782c-c132-4e2d-8e72-f560c97693d2",
+   "id": "4c7dfb0c-5daa-41e8-bbb8-f453be29e1d7",
    "metadata": {},
    "source": [
-    "As shown in the [Data discovery](./data_discovery.ipynb) chapter, when we have several files to read at once, we need to use Xarray `open_mfdataset` instead of `open_dataset`. It takes a list in input, and not a single element. We can also use `open_mfdataset` with one file as done below, just as an introduction."
+    "__Chunking__ is splitting a dataset into small pieces. \n",
+    "\n",
+    "Original dataset, in one piece,  \n",
+    "<img src=\"../figures/notchunked.png\" width=\"200\" height=\"100\">\n",
+    "\n",
+    "and we split it into several smaller pieces.  \n",
+    "<img src=\"../figures/chunked.png\" width=\"200\" height=\"100\">\n",
+    "\n",
+    "We split it into pieces so that we can process our data block by block or __chunk__ by __chunk__.\n",
+    "\n",
+    "In our case, for the moment, we used stackstac without specifying 'chunk' explicitly.   The dataset is composed of 8MiB each, each contains, 1 time step, 1 band, 1024 x 1024 on x and y direction.  \n",
+    "<img src=\"../figures/chunk_original.png\" width=\"200\" height=\"100\">\n",
+    "\n",
+    "\n",
+    "If we have too small chunk size, we will divide our work flow in too small pieces, which can create too many communications, too many 'distirbution' overheads. \n",
+    "If we have too big chunk size, we may not be able to hold the enough memory and our workflow may die.  \n",
+    "\n",
+    "The right size of chunk depends on your computation and the machine you use.  \n",
+    "\n",
+    "Here, 8MiB, is very small compare to usual RAM size available. For example, dask's default array size is 128MiB.  \n",
+    " "
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "af670e00-fbad-4f70-a24f-1b6dc7320a8f",
+   "id": "0cc3cf9c-583b-46a8-b6eb-38083af17bbc",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import dask\n",
+    "dask.config.get('array.chunk-size')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "77a95b34-8ecb-4dca-8c4a-861d9b078012",
    "metadata": {},
+   "source": [
+    "## Modifying chunks\n",
+    "Lets try to modify our chunk size.    \n",
+    "\n",
+    "\n",
+    "To modify chunks on your existing Xarray  `DataArray`  we can use `chunk` function of Xarray.\n",
+    "We know that we only need 3 bands for computing the snow index example, so we select only 'green','swir16','scl' to simplyfy our example.  \n",
+    "\n",
+    "We would like to have each time series separeated in each chunk, then keep all band informnation on one chunk, and let dask to compute x and y coordinate's chunk size. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6b35188d-fe2d-4977-aa3d-7a0c49a2d75b",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
-    "%%time\n",
-    "LTS = xr.open_mfdataset([fs.open(s3path)])\n",
-    "LTS"
+    "sentinel2_l2a=sentinel2_l2a.sel(\n",
+    "    band=['green','swir16','scl']).chunk(\n",
+    "    chunks={'time': 1, 'band':3, 'x':'auto','y':'auto'})\n",
+    "sentinel2_l2a"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "9e1c5fa8-f144-4330-b927-ea946fb19fce",
+   "id": "19f05ca7-1439-4a44-aad5-0dda313eeb5f",
    "metadata": {},
    "source": [
-    "Using `open_mfdataset` automatically switch from Numpy Arrays to Dask Arrays as the data structure used by Xarray. "
+    "If you look into details of any variable in the representation above, you'll see that each x and y coordinate's each 'chunk' is bigger, and we have much less chunks (6666 chunks) than example before.  Chunk size as 96 MiB,  is already more manageable than 8MiB small chunk."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "aeab2142-9c78-465c-b743-3028c10cb0ea",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "sentinel2_l2a.chunk(chunks = ( 1, -1, 12048,2048))"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "5e82268f-d173-4baf-9239-94678d5de1b9",
+   "id": "7ac448da",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-warning\">\n",
     "    <i class=\"fa-check-circle fa\" style=\"font-size: 22px;color:#666;\"></i> <b>Go Further</b>\n",
     "    <br>\n",
+    "    <br>\n",
+    "    You can try to apply different ways for specifying chunk.\n",
     "    <ul>\n",
-    "        <li>You can try to open the same file with xr.open_dataset(fs.open(s3path))</li> \n",
-    "        <li>Compare the xarray output between open_mfdataset and open_dataset, what do you see as difference?</li>\n",
-    "            </ul>\n",
+    "        <li> chunks = -1 -> the entire array will be used as a single chunk\n",
+    "        <li> chunks = {'x':-1, 'y': 1000} -> chunks of entire _x_ dimension, but splitted every 1000 values on _y_ dimension</li>\n",
+    "        <li> chunks = {'x':-1, 'y': 'auto'} -> Xarray relies on Dask to use an ideal size according to the preferred chunk sizes for _y_ dimension</li>\n",
+    "        <li> chunks = { 'x':-1 ,'y':\"500MiB\" } -> Xarray seeks the size according to a specific memory target expressed in MiB</li>\n",
+    "        <li> chunks = ( 1, 3, 12048,2048) -> Specifying chunk size in the order of dimension. </li>\n",
+    "    </ul>\n",
     "</div>"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "f05d2938-d0ea-41fe-b32c-af81a8055416",
+   "id": "6d1f923b-6e45-4494-af6c-c537e1791f99",
+   "metadata": {},
+   "source": [
+    "## Defining the chunk at the creatioin of Xarray\n",
+    "\n",
+    "We can define the chunk size when we create the object.  \n",
+    "This is usually done with Xarray using the `chunks` kwarg when opening a file with `xr.open_dataset` or with `xr.open_mfdataset`, if you create Xarray from your local file.  \n",
+    "In our snow index example, we create Xarray from stackstac. As stackstac's default 'chunksize' definition is 1024 for x and y dimension, we had that chunksize.  We can pass the chunksize option to stdeackstac and make that bigger.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ac7fd516-7366-4b22-9a6a-87ad615da69a",
    "metadata": {
     "tags": []
    },
+   "outputs": [],
    "source": [
-    "## What is a __chunk__\n",
+    "%%time\n",
+    "sentinel2_l2a = stackstac.stack(items\n",
+    "                                ,assets=['green','swir16','scl']\n",
+    "                               ,chunksize=( 1, 3, 2048,2048)\n",
+    ")\n",
+    "sentinel2_l2a"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8df00ba1-46ea-46a6-92e6-433187e8f433",
+   "metadata": {
+    "jp-MarkdownHeadingCollapsed": true,
+    "tags": []
+   },
+   "source": [
+    "## So, why chunks?\n",
     "\n",
-    "If you look carefully to `LTS`, each Data Variable is a `dask.array` with a chunk size of `(15680, 40320)`. So basically accessing one data variable would load arrays of dimensions `(15680, 40320)` into the computer's RAM. You can see this information and more details by clicking the icon as indicated in the image below.\n",
+    "Chunks are mandatory for accessing files or dataset that are bigger than a single computer's memory. If all the data has to be accessed, it can be done sequentially e.g. chunks are processed one after the othe).\n",
     "\n",
-    "![Dask.array](../figures/datasize.png)\n",
+    "Moreover, chunks allow for distributed processing and so increased speed for your data analysis, as seen in the next episode.\n",
     "\n",
-    "When you open one or several netCDF files with `open_mdfataset`, by default, the chunks correspond to the entire size of the variable data array read from each file. When you need to analyze large files, a computer's memory may not be sufficient anymore (see in this example, 2.36GiB for one chunk!).\n",
+    "### Chunks and files\n",
     "\n",
-    "This is where understanding and using chunking correctly comes into play.\n"
+    "Xarray chunking possibilities also relies on the underlying input or output file format used. Most modern file format allows to store a dataset or a single file using chunks. NetCDF4 uses chunks when storing a file on the disk through the use of HDF5. Any read of data in a NetCDF4 file will lead to the load of at least one chunk of this file. So when reading one of its chunk as defined in `open_dataset` call, Xarray will take advantage of native file chunking and won't have to read the entire file too.\n",
+    "\n",
+    "\n",
+    "Yet, it is really important to note that __Xarray chunks and file chunks are not necessarily the same__. It is however a really good idea to configure Xarray chunks so that they align well on input file format chunks (so ideally, Xarray chunks should contain one or several input file chunks)."
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "4c7dfb0c-5daa-41e8-bbb8-f453be29e1d7",
+   "id": "413a0ddb-3b89-4392-9822-dfaa80111c52",
    "metadata": {},
    "source": [
-    "__Chunking__ is splitting a dataset into small pieces. \n",
+    "## Zarr storage format\n",
     "\n",
-    "Original dataset is in one piece,  \n",
-    "![Dask.array](../figures/notchunked.png)\n",
+    "This brings to our next subjects [Zarr](https://zarr.readthedocs.io/en/stable/) and [Kerchunk](https://fsspec.github.io/kerchunk/).\n",
     "\n",
-    "and we split it into several smaller pieces.  \n",
-    "![Dask.array](../figures/chunked.png)\n",
+    "If we can have our original dataset already 'chunked' and accessed in an optimized way according to it's actual byte storage on disk, we won't need to load entire dataset every time, and our data anlayzis, even working on the entire dataset, will be greatly optimized.\n",
     "\n",
-    "We split it into pieces so that we can process our data block by block or __chunk__ by __chunk__.\n",
+    "Let's convert our intermediate data into Zarr format so that we can learn what it is. We can keep the data as in DataArray or convert that into DataSet before storing them.\n",
     "\n",
-    "In our case, for the moment, the dataset is composed of several files, so already several pieces (or just one in the example above), and Xarray just creates one chunk for each variable of each file."
+    "We start again from loading data using stackstac, but this time we go to next step, clipping the data and computation of snow index, and lets try to save those intermediate result in a zarr file.  \n"
    ]
   },
   {
-   "cell_type": "markdown",
-   "id": "77a95b34-8ecb-4dca-8c4a-861d9b078012",
-   "metadata": {},
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "38c5bb65-8143-4841-98f0-a704f1034b2b",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "tags": []
+   },
+   "outputs": [],
    "source": [
-    "## Using chunks within a single file\n",
+    "# Data Manipulation and Analysis Libraries\n",
+    "import pandas as pd  \n",
+    "import numpy as np \n",
     "\n",
-    "When we want to read one or several big files, or files containing large arrays (the above 2.36GiB per array is already quite big), we will almost certainly need chunks so that we can process arrays piece by piece.\n",
+    "# Geospatial Data Handling Libraries\n",
+    "import geopandas as gpd \n",
+    "from shapely.geometry import mapping  \n",
+    "import pyproj\n",
     "\n",
-    "This is usually done with Xarray using the `chunks` kwarg when opening a file with `xr.open_dataset` or with `xr.open_mfdataset`."
+    "# Multidimensional and Satellite Data Libraries\n",
+    "import xarray as xr \n",
+    "import rioxarray as rio\n",
+    "import stackstac\n",
+    "\n",
+    "# Data Visualization Libraries\n",
+    "import holoviews as hv\n",
+    "import hvplot.xarray\n",
+    "import hvplot.pandas\n",
+    "\n",
+    "# Data parallelization and distributed computing libraries\n",
+    "import dask\n",
+    "from dask.distributed import Client, progress, LocalCluster\n",
+    "\n",
+    "# STAC Catalogue Libraries\n",
+    "import pystac_client\n",
+    "\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\")"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "3e554760-d78b-4d0f-a276-cf57f886080c",
-   "metadata": {},
+   "id": "30439c85-6f76-4747-951f-93612cb6ccbd",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "tags": []
+   },
    "outputs": [],
    "source": [
-    "LTS = xr.open_dataset(fs.open(s3path), chunks={\"lon\": 40320 / 2, \"lat\": 15680 / 2})\n",
-    "LTS"
+    "cluster = LocalCluster()\n",
+    "client = Client(cluster)\n",
+    "client"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "19f05ca7-1439-4a44-aad5-0dda313eeb5f",
+   "id": "2c711573-b93b-4979-a28c-5e8ce3fb6f84",
    "metadata": {},
    "source": [
-    "If you look into details of any variable in the representation above, you'll see that each array is chunked into 4 pieces, 602.96 MiB each, which is already more manageable in memory."
+    "## Load data using stackstac (with specific chunk) "
    ]
   },
   {
-   "cell_type": "markdown",
-   "id": "6d1f923b-6e45-4494-af6c-c537e1791f99",
-   "metadata": {},
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4833d382-e110-4ba8-a911-8c9ce7cb18d1",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
    "source": [
-    "Xarray `Dataset` and `DataArray` objects also have a `chunk` function. We can use it to change our dataset chunks size.\n",
-    "Lets try to 'chunk' our data array LTS.nobs using this command.\n"
+    "%%time\n",
+    "aoi = gpd.read_file('data/catchment_outline.geojson', crs=\"EPGS:4326\")\n",
+    "aoi_geojson = mapping(aoi.iloc[0].geometry)\n",
+    "URL = \"https://earth-search.aws.element84.com/v1\"\n",
+    "catalog = pystac_client.Client.open(URL)\n",
+    "items = catalog.search(\n",
+    "    intersects=aoi_geojson,\n",
+    "    collections=[\"sentinel-2-l2a\"],\n",
+    "    datetime=\"2019-02-01/2019-06-10\"\n",
+    ").item_collection()\n",
+    "ds = stackstac.stack(items\n",
+    "                                ,assets=['green','swir16','scl']\n",
+    "                               ,chunksize=( 1, 3, 1024,1024)\n",
+    ")\n",
+    "#ds"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "babfb689-5a92-4e67-8304-8fecc30f742d",
+   "id": "49d282f0-c4f4-493d-9144-292885edb720",
    "metadata": {},
    "source": [
-    "As we would like to play with small sized array, we first select a subset of data as you've learned in [xarray_introduction](./xarray_introduction.ipynb). "
+    "## Coomputing Snow index\n"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ec60ad82-9abb-42a6-9119-26f9b567b7fc",
-   "metadata": {},
+   "id": "a78f2c90-4dc9-4ced-b11a-1a08c3e9316c",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "tags": []
+   },
    "outputs": [],
    "source": [
-    "test = LTS.nobs.sel(lat=slice(80.,70.), lon=slice(70.,90))\n",
-    "test"
+    "green = ds.sel(band='green')\n",
+    "swir = ds.sel(band='swir16')\n",
+    "scl = ds.sel(band='scl')\n",
+    "ndsi = (green - swir) / (green + swir)\n",
+    "snow = xr.where((ndsi > 0.42) & ~np.isnan(ndsi), 1, ndsi)\n",
+    "snowmap = xr.where((snow <= 0.42) & ~np.isnan(snow), 0, snow)\n",
+    "mask = np.logical_not(scl.isin([8, 9, 3])) \n",
+    "snow_cloud = xr.where(mask, snowmap, 2)\n",
+    "#snow_cloud"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "59e8990f-5436-4723-a26b-bd396b19bb33",
+   "id": "eac3ce48-30dd-4fc8-8491-1c7124016063",
    "metadata": {},
    "source": [
-    "The test value has dimensions `(1121, 2240)`.  We will chunk it on 600x600 pieces using the following command. "
+    "## Clip the data"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "7f644ba3-8eb5-4cf9-bd20-0aebda8bc05e",
+   "id": "d939b76f-32f3-48da-bce9-4a082fd0f473",
    "metadata": {
     "tags": []
    },
    "outputs": [],
    "source": [
-    "test=test.chunk(600)\n",
-    "test"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "437ce642",
-   "metadata": {},
-   "source": [
-    "As you can see in the above graphics we got 8 __chunks__.  These 8 chunks are noted as (0,0) ..(0,3) (1,0),..(1,3) as you can see in the next visualisation."
+    "aoi_utm32 = aoi.to_crs(epsg=32632)\n",
+    "geom_utm32 = aoi_utm32.iloc[0]['geometry']\n",
+    "snow_cloud.rio.write_crs(\"EPSG:32632\", inplace=True)\n",
+    "snow_cloud.rio.set_nodata(np.nan, inplace=True)\n",
+    "snow_cloud = snow_cloud.rio.clip([geom_utm32])\n",
+    "#snow_cloud"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "d36efa13-b1e5-429a-9b2c-537b07d9e49a",
+   "id": "1740cd1a-dda2-407b-b58d-e626aa11fb64",
    "metadata": {},
    "source": [
-    "## Operations on a chunked dataset\n",
-    "\n",
-    "Let's have a look of our chunked test dataset backend representation."
+    "## Lets save the intermediate result of a few days in a zarr format"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "9768b366",
+   "id": "86826bf9-baae-45a3-9caf-a0ac784e77bf",
    "metadata": {
-    "collapsed": false,
-    "jupyter": {
-     "outputs_hidden": false
-    }
+    "tags": []
    },
    "outputs": [],
    "source": [
-    "test.data.visualize()"
+    "test=snow_cloud.isel(time=slice(0,3))\n",
+    "test"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "1302b99f",
+   "id": "6b7c06cc-64f1-4a19-9048-d494eaa47a82",
    "metadata": {},
    "source": [
-    "` test.data` is the backend array Python representation of Xarray's Data Array, [__Dask Array__](https://docs.dask.org/en/stable/array.html) when using chunking, Numpy by default.\n",
-    "\n",
-    "We will introduce Dask arrays and Dask graphs visualization in the next section [dask_introduction](./dask_introduction.ipynb)."
+    "## Before saving, we clean the chunk size, clean attribute and save the data in Xarray DataSet format\n"
    ]
   },
   {
-   "cell_type": "markdown",
-   "id": "5da222df-6f45-434c-b741-34ef27352199",
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "445791b6-3676-4237-8098-3ff65713c441",
    "metadata": {
-    "jp-MarkdownHeadingCollapsed": true,
     "tags": []
    },
+   "outputs": [],
    "source": [
-    "Anyway, when applying `chunk` function you may have the impression that the chunks sizes just changes and everything will be fine.\n",
+    "test=test.chunk(chunks = {'x':'auto', 'y': 'auto'}).to_dataset(name='data')\n",
+    "test\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "987063c7-156a-4d0f-9243-adf6e59a48f6",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%time\n",
     "\n",
-    "However, as you can see in the graph visualization above, Xarray will actually have to fetch at least one entire initial chunk that was defined when opening the Dataset at first before rechunking at a smaller size or even selecting one value. This is true when applying any funtions on any values: Xarray will work by loading entire chunks.\n",
+    "def remove_attrs(obj, to_remove):\n",
+    "    new = obj.copy()\n",
+    "    new.attrs = {k: v for k, v in obj.attrs.items() if k not in to_remove}\n",
     "\n",
-    "You can imagine that it will not be very optimal if you load one file as an entire chunk, or if your initial chunks are too big (your Python Jupyter kernel may crash!), especially with large numbers of files and large files. Choosing an appropriate chunk size is really important and depends on your analysis.\n",
+    "    return new\n",
     "\n",
-    "You can find a really nice article by Dask team on how to chose the right chunk size [here](https://blog.dask.org/2021/11/02/choosing-dask-chunk-sizes)."
+    "def encode(obj):\n",
+    "    object_coords = [name for name, coord in obj.coords.items() if coord.dtype.kind == \"O\"]\n",
+    "    return obj.drop_vars(object_coords).pipe(remove_attrs, [\"spec\", \"transform\"])\n",
+    "\n",
+    "\n",
+    "test.pipe(encode).to_zarr('test.zarr',mode='w')"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "7ac448da",
+   "id": "a6b84245-fc8e-46c9-a531-1e0ccc0bee0d",
    "metadata": {},
    "source": [
-    "<div class=\"alert alert-warning\">\n",
-    "    <i class=\"fa-check-circle fa\" style=\"font-size: 22px;color:#666;\"></i> <b>Go Further</b>\n",
-    "    <br>\n",
-    "    <br>\n",
-    "    You can try to apply different ways for specifying chunk.\n",
-    "    <ul>\n",
-    "        <li> chunks = 'auto' -> Xarray relies on Dask to use an ideal size according to the preferred chunk sizes</li>\n",
-    "        <li> chunks = -1 -> the entire array will be used as a single chunk\n",
-    "        <li> chunks = \"1MiB\" -> Xarray seeks the size according to a specific memory target expressed in MiB</li>\n",
-    "        <li> chunks = {'lat'=-1, 'lon'= 1000} -> chunks of entire _lat_ dimension, but splitted every 1000 values on _lon_ dimension</li>\n",
-    "        <li> compare the resulting chunked data's shape, size, tasks, data.visualize..... What do you see?</li>\n",
-    "    </ul>\n",
-    "</div>"
+    "## Load the temporaly data saved as zarr back to Xarray"
    ]
   },
   {
-   "cell_type": "markdown",
-   "id": "8df00ba1-46ea-46a6-92e6-433187e8f433",
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "391e0e9c-c1d3-4744-8e8a-7b8a89db7f3e",
    "metadata": {
-    "jp-MarkdownHeadingCollapsed": true,
     "tags": []
    },
+   "outputs": [],
    "source": [
-    "## So, why chunks?\n",
-    "\n",
-    "In the end, chunks are mandatory for accessing files or dataset that are bigger than a single computer's memory. If all the data has to be accessed, it can be done sequentially e.g. chunks are processed one after the othe).\n",
-    "\n",
-    "Moreover, chunks allow for distributed processing and so increased speed for your data analysis, as seen in the next episode.\n",
-    "\n",
-    "### Chunks and files\n",
-    "\n",
-    "Xarray chunking possibilities also relies on the underlying input or output file format used. Most modern file format allows to store a dataset or a single file using chunks. NetCDF4 uses chunks when storing a file on the disk through the use of HDF5. Any read of data in a NetCDF4 file will lead to the load of at least one chunk of this file. So when reading one of its chunk as defined in `open_dataset` call, Xarray will take advantage of native file chunking and won't have to read the entire file too.\n",
-    "\n",
-    "Yet, it is really important to note that __Xarray chunks and file chunks are not necessarily the same__. It is however a really good idea to configure Xarray chunks so that they align well on input file format chunks (so ideally, Xarray chunks should contain one or several input file chunks)."
+    "snow_cloud=xr.open_zarr('test.zarr').data"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "413a0ddb-3b89-4392-9822-dfaa80111c52",
+   "id": "89e7c5c3-7d6e-4618-8207-008915b6fb78",
    "metadata": {},
    "source": [
-    "## Zarr storage format\n",
-    "\n",
-    "This brings to our next subjects [Zarr](https://zarr.readthedocs.io/en/stable/) and [Kerchunk](https://fsspec.github.io/kerchunk/).\n",
-    "\n",
-    "If we can have our original dataset already 'chunked' and accessed in an optimized way according to it's actual byte storage on disk, we won't need to load entire dataset every time, and our data anlayzis, even working on the entire dataset, will be greatly optimized.\n",
-    "\n",
-    "Let's convert our input data into Zarr format so that we can learn what it is. We can keep the data as in DataArray or convert that into DataSet before storing them."
+    "## Group by to a day, and plot the results"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "bc4fb079",
+   "id": "4d939364-683d-4961-bfd7-21031cd53f76",
    "metadata": {
-    "collapsed": false,
-    "jupyter": {
-     "outputs_hidden": false
-    }
+    "tags": []
    },
    "outputs": [],
    "source": [
-    "test.to_zarr('test_DataArray.zarr',mode='w')"
+    "clipped_date = snow_cloud.groupby(snow_cloud.time.dt.floor('D')).max(skipna=True)\n",
+    "clipped_date = clipped_date.rename({'floor': 'date'})"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "698991c9-d910-44a0-a7b2-569464614bd1",
+   "id": "169af488-e1c7-4791-ab83-9111e0b5978d",
    "metadata": {
     "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
-    }
+    },
+    "tags": []
    },
    "outputs": [],
    "source": [
-    "test.to_dataset().to_zarr('test.zarr',mode='w')"
+    "clipped_date.hvplot.image(\n",
+    "    x='x',\n",
+    "    y='y',\n",
+    "    groupby='date',\n",
+    "    crs=pyproj.CRS.from_epsg(32632),\n",
+    "    cmap='Pastel2',\n",
+    "    clim=(-1, 2),\n",
+    "    frame_width=500,\n",
+    "    frame_height=500,\n",
+    "    title='Snowmap',\n",
+    "    geo=True, tiles='OSM')"
    ]
   },
   {
@@ -451,6 +652,7 @@
     "    <i class=\"fa-check-circle fa\" style=\"font-size: 22px;color:#666;\"></i> <b>Exercise</b>\n",
     "    <br>\n",
     "    <ul>\n",
+    "        <li>What about saving the data in Netcdf format? `ls -la test.zarr` and  `ls -la test.zarr/nobs `</li>\n",
     "        <li>You can try to explore the zarr file you just created using `ls -la test.zarr` and  `ls -la test.zarr/nobs `</li>\n",
     "        <li>You can explore zarr metadata file by `cat test.zarr/.zmetadata` </li>\n",
     "        <li>Did you find the __chunks__ we defined previously in your zarr file? </li>\n",
@@ -458,6 +660,18 @@
     "</div>"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "aca0670d-11cf-4521-abd4-515cb2dd51fe",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "xr.open_zarr('test.zarr').to_netcdf('test.nc')"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -465,7 +679,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!du -sh test.zarr/"
+    "!du -sh test.zarr/ test.nc"
    ]
   },
   {
@@ -480,7 +694,7 @@
    },
    "outputs": [],
    "source": [
-    "!ls -al test.zarr/nobs"
+    "!ls  -la test.zarr/data"
    ]
   },
   {
@@ -502,7 +716,7 @@
    "source": [
     "Zarr format main characteristics are the following:\n",
     "\n",
-    "- Every chunk of a Zarr dataset is stored as a single file (see x.y files in `ls -al test.zarr/nobs`)\n",
+    "- Every chunk of a Zarr dataset is stored as a single file (see x.y files in `ls -al test.zarr/data`)\n",
     "- Each Data array in a Zarr dataset has a two unique files containing metadata:\n",
     "  - .zattrs for dataset or dataarray general metadatas\n",
     "  - .zarray indicating how the dataarray is chunked, and where to find them on disk or other storage.\n",
@@ -513,7 +727,9 @@
   {
    "cell_type": "markdown",
    "id": "d9103092",
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "source": [
     "## Opening multiple NetCDF files and Kerchunk\n",
     "\n",
@@ -939,6 +1155,45 @@
     "We will use this catalogue in [dask_introduction](./dask_introduction.ipynb) chapter. "
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "d36efa13-b1e5-429a-9b2c-537b07d9e49a",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Operations on a chunked dataset\n",
+    "\n",
+    "Let's have a look of our chunked test dataset backend representation."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1302b99f",
+   "metadata": {},
+   "source": [
+    "` test.data` is the backend array Python representation of Xarray's Data Array, [__Dask Array__](https://docs.dask.org/en/stable/array.html) when using chunking, Numpy by default.\n",
+    "\n",
+    "We will introduce Dask arrays and Dask graphs visualization in the next section [dask_introduction](./dask_introduction.ipynb)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5da222df-6f45-434c-b741-34ef27352199",
+   "metadata": {
+    "jp-MarkdownHeadingCollapsed": true,
+    "tags": []
+   },
+   "source": [
+    "Anyway, when applying `chunk` function you may have the impression that the chunks sizes just changes and everything will be fine.\n",
+    "\n",
+    "However, as you can see in the graph visualization above, Xarray will actually have to fetch at least one entire initial chunk that was defined when opening the Dataset at first before rechunking at a smaller size or even selecting one value. This is true when applying any funtions on any values: Xarray will work by loading entire chunks.\n",
+    "\n",
+    "You can imagine that it will not be very optimal if you load one file as an entire chunk, or if your initial chunks are too big (your Python Jupyter kernel may crash!), especially with large numbers of files and large files. Choosing an appropriate chunk size is really important and depends on your analysis.\n",
+    "\n",
+    "You can find a really nice article by Dask team on how to chose the right chunk size [here](https://blog.dask.org/2021/11/02/choosing-dask-chunk-sizes)."
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "1665722c-4c65-4334-987e-1f5bc4841036",
@@ -996,7 +1251,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.11.6"
   }
  },
  "nbformat": 4,
diff --git a/_sources/part3/scaling_dask.ipynb b/_sources/part3/scaling_dask.ipynb
index 7fb11c7..f9943d0 100644
--- a/_sources/part3/scaling_dask.ipynb
+++ b/_sources/part3/scaling_dask.ipynb
@@ -54,11 +54,11 @@
     "## Context\n",
     "\n",
     "\n",
-    "We will be using [Dask](https://docs.dask.org/) with [Xarray](https://docs.xarray.dev/en/stable/) to parallelize our data analysis. The analysis is very similar to what we have done in previous episodes but this time we will use data on a global coverage that we read from a shared catalog (stored online in the Pangeo EOSC Openstack Object Storage).\n",
+    "We will be using [Dask](https://docs.dask.org/) with [Xarray](https://docs.xarray.dev/en/stable/) to parallelize our data analysis.  We continue to use the snow index example.  \n",
     "\n",
     "### Data\n",
     "\n",
-    "In this episode, we will be using Global Long Term Statistics (1999-2019) product provided by the [Copernicus Global Land Service over Lombardia](https://land.copernicus.eu/global/index.html) and access them through [S3-comptabile storage](https://en.wikipedia.org/wiki/Amazon_S3) ([OpenStack Object Storage \"Swift\"](https://wiki.openstack.org/wiki/Swift)) with a data catalog we have created and made publicly available."
+    "In this episode, we will be using xxx"
    ]
   },
   {
@@ -264,19 +264,19 @@
    "source": [
     "### Dask Dashboard\n",
     "\n",
-    "Dask comes with a really handy interface: the Dask Dashboard. It is a web interface that you can open in a separated tab of your browser (but not with he link above, you've got to use Jupyterlabs proxy: https://pangeo-foss4g.vm.fedcloud.eu/jupyterhub/user/_yourusername_/proxy/8787/status).\n",
+    "Dask comes with a really handy interface: the Dask Dashboard. It is a web interface that you can open in a separated tab of your browser (but not with he link above, you've got to use Jupyterlabs proxy: /user/todaka/proxy/8787/status).\n",
     "\n",
     "We will learn here how to use it through [dask jupyterlab extension](https://github.com/dask/dask-labextension).  \n",
     "\n",
-    "To use Dask Dashboard through jupyterlab extension on Pangeo EOSC FOSS4G infrastructure,\n",
+    "To use Dask Dashboard through jupyterlab extension on Pangeo EOSC infrastructure,\n",
     "you will just need too look at the html link you have for your jupyterlab, and Dask dashboard port number, as highlighted in the figure below.\n",
     "\n",
     "\n",
     "<img src=\"../figures/dashboardlink.png\" width=\"50%\">\n",
-    "<img src=\"../figures/dasklab.png\" width=\"30%\">\n",
+    "<img src=\"../figures/dasklab.png\" width=\"80%\">\n",
     "\n",
     "Then click the orange icon indicated in the above figure, and type 'your' dashboard link (normally, you just need to replace 'todaka' to 'your username').  \n",
-    "\n",
+    "<img src=\"../figures/daskclick.png\" width=\"30%\">\n",
     "\n",
     "\n",
     "\n",
diff --git a/part1/visualization.html b/part1/visualization.html
index f42555f..7ccc655 100644
--- a/part1/visualization.html
+++ b/part1/visualization.html
@@ -976,7 +976,7 @@ <h2>Open local dataset<a class="headerlink" href="#open-local-dataset" title="Pe
   * lon      (lon) float64 8.502 8.505 8.508 8.511 ... 11.42 11.42 11.42 11.43
   * lat      (lat) float64 46.5 46.5 46.49 46.49 ... 44.69 44.69 44.68 44.68
 Data variables:
-    NDVI     (time, lat, lon) float64 ...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f6a4fad6-dad1-4a94-a7d9-bd57a5fe7590' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f6a4fad6-dad1-4a94-a7d9-bd57a5fe7590' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 20</li><li><span class='xr-has-index'>lon</span>: 984</li><li><span class='xr-has-index'>lat</span>: 612</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-08ae1fb5-d3ae-4b4c-bd1f-c08a29917e07' class='xr-section-summary-in' type='checkbox'  checked><label for='section-08ae1fb5-d3ae-4b4c-bd1f-c08a29917e07' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-155291a8-81a4-44f9-ba68-ba4f388bb866' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-155291a8-81a4-44f9-ba68-ba4f388bb866' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c5fab55-86ab-40f3-b860-f45ddebefd66' class='xr-var-data-in' type='checkbox'><label for='data-3c5fab55-86ab-40f3-b860-f45ddebefd66' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
+    NDVI     (time, lat, lon) float64 ...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b0fb0f13-924a-44d7-a539-6af91fc68ade' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b0fb0f13-924a-44d7-a539-6af91fc68ade' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 20</li><li><span class='xr-has-index'>lon</span>: 984</li><li><span class='xr-has-index'>lat</span>: 612</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-3e848272-0845-41ae-b59b-622508c86976' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3e848272-0845-41ae-b59b-622508c86976' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-5e252c64-cfbf-41a9-a173-2ac70df81b7c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e252c64-cfbf-41a9-a173-2ac70df81b7c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e751b5f1-09f2-41bf-83ec-a3535524434c' class='xr-var-data-in' type='checkbox'><label for='data-e751b5f1-09f2-41bf-83ec-a3535524434c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
        &#x27;2022-01-21T00:00:00.000000000&#x27;, &#x27;2022-02-01T00:00:00.000000000&#x27;,
        &#x27;2022-02-11T00:00:00.000000000&#x27;, &#x27;2022-02-21T00:00:00.000000000&#x27;,
        &#x27;2022-03-01T00:00:00.000000000&#x27;, &#x27;2022-03-11T00:00:00.000000000&#x27;,
@@ -986,12 +986,12 @@ <h2>Open local dataset<a class="headerlink" href="#open-local-dataset" title="Pe
        &#x27;2022-05-21T00:00:00.000000000&#x27;, &#x27;2022-06-01T00:00:00.000000000&#x27;,
        &#x27;2022-06-11T00:00:00.000000000&#x27;, &#x27;2022-06-21T00:00:00.000000000&#x27;,
        &#x27;2022-07-01T00:00:00.000000000&#x27;, &#x27;2022-07-11T00:00:00.000000000&#x27;],
-      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-e67c85f3-36b2-42bf-bd56-d85398056269' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e67c85f3-36b2-42bf-bd56-d85398056269' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd5fc85a-9036-41b0-91e2-0c0a31289a79' class='xr-var-data-in' type='checkbox'><label for='data-dd5fc85a-9036-41b0-91e2-0c0a31289a79' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.5 46.5 46.49 ... 44.68 44.68</div><input id='attrs-2b653c66-0574-4f85-bba3-936a93643a33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b653c66-0574-4f85-bba3-936a93643a33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4f6fc3c-a7e0-4793-a329-ad9548506aa1' class='xr-var-data-in' type='checkbox'><label for='data-b4f6fc3c-a7e0-4793-a329-ad9548506aa1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.499803, 46.496827, 46.493851, ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-55632224-1a9c-46f3-a2af-35d81417e9fd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-55632224-1a9c-46f3-a2af-35d81417e9fd' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>NDVI</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-330c678e-f101-4000-8332-0fd8219eaf3d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-330c678e-f101-4000-8332-0fd8219eaf3d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b69af2c-d9db-40ed-9e1a-e270de96dea6' class='xr-var-data-in' type='checkbox'><label for='data-7b69af2c-d9db-40ed-9e1a-e270de96dea6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[12044160 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d1e08232-ca2b-4011-a510-fb21584e66c2' class='xr-section-summary-in' type='checkbox'  ><label for='section-d1e08232-ca2b-4011-a510-fb21584e66c2' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-34491397-e807-4628-84ae-1c08965fc939' class='xr-index-data-in' type='checkbox'/><label for='index-34491397-e807-4628-84ae-1c08965fc939' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-7edd862b-1851-44fe-bd4f-0a271f355df8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7edd862b-1851-44fe-bd4f-0a271f355df8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91833374-5dcc-4d72-8974-6a17c6e239c4' class='xr-var-data-in' type='checkbox'><label for='data-91833374-5dcc-4d72-8974-6a17c6e239c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.5 46.5 46.49 ... 44.68 44.68</div><input id='attrs-f440148f-209f-415e-b216-49e40d1cf267' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f440148f-209f-415e-b216-49e40d1cf267' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4b3b0f7-927e-4e35-8c3e-dfe3c5f567de' class='xr-var-data-in' type='checkbox'><label for='data-f4b3b0f7-927e-4e35-8c3e-dfe3c5f567de' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.499803, 46.496827, 46.493851, ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ffc9e4f4-07dc-466b-bf52-7a5f954448e7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ffc9e4f4-07dc-466b-bf52-7a5f954448e7' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>NDVI</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3ba59771-de78-42d5-9776-69c4b7c4d25e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3ba59771-de78-42d5-9776-69c4b7c4d25e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-728be626-df73-431c-b1ca-b060083fe1c3' class='xr-var-data-in' type='checkbox'><label for='data-728be626-df73-431c-b1ca-b060083fe1c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[12044160 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-37d7cd8a-b657-4d60-82b4-2215272ca84f' class='xr-section-summary-in' type='checkbox'  ><label for='section-37d7cd8a-b657-4d60-82b4-2215272ca84f' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0208763c-611e-432a-bda2-764d2f362938' class='xr-index-data-in' type='checkbox'/><label for='index-0208763c-611e-432a-bda2-764d2f362938' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
                &#x27;2022-02-11&#x27;, &#x27;2022-02-21&#x27;, &#x27;2022-03-01&#x27;, &#x27;2022-03-11&#x27;,
                &#x27;2022-03-21&#x27;, &#x27;2022-04-01&#x27;, &#x27;2022-04-11&#x27;, &#x27;2022-04-21&#x27;,
                &#x27;2022-05-01&#x27;, &#x27;2022-05-11&#x27;, &#x27;2022-05-21&#x27;, &#x27;2022-06-01&#x27;,
                &#x27;2022-06-11&#x27;, &#x27;2022-06-21&#x27;, &#x27;2022-07-01&#x27;, &#x27;2022-07-11&#x27;],
-              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8b021f8f-f5f4-4198-bd21-f597943b5391' class='xr-index-data-in' type='checkbox'/><label for='index-8b021f8f-f5f4-4198-bd21-f597943b5391' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4d5ef41d-d6a3-42bd-8fb2-a0b6ce1e1860' class='xr-index-data-in' type='checkbox'/><label for='index-4d5ef41d-d6a3-42bd-8fb2-a0b6ce1e1860' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
          8.51066566666671,  8.513641857142915,  8.516618047619119,
         8.519594238095323,  8.522570428571527,   8.52554661904773,
         8.528522809523935,
@@ -1000,7 +1000,7 @@ <h2>Open local dataset<a class="headerlink" href="#open-local-dataset" title="Pe
        11.409475190489406,  11.41245138096561, 11.415427571441814,
        11.418403761918018, 11.421379952394222, 11.424356142870426,
         11.42733233334663],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e5a9a902-b883-4654-ae23-ef31b7a95c92' class='xr-index-data-in' type='checkbox'/><label for='index-e5a9a902-b883-4654-ae23-ef31b7a95c92' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.49980333333342, 46.49682714285723, 46.49385095238104,
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-90e5dfa7-f13a-4eda-b2f8-788c520e0cb0' class='xr-index-data-in' type='checkbox'/><label for='index-90e5dfa7-f13a-4eda-b2f8-788c520e0cb0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.49980333333342, 46.49682714285723, 46.49385095238104,
        46.49087476190485, 46.48789857142866, 46.48492238095247,
        46.48194619047628, 46.47897000000009, 46.47599380952389,
         46.4730176190477,
@@ -1009,7 +1009,7 @@ <h2>Open local dataset<a class="headerlink" href="#open-local-dataset" title="Pe
        44.69920809523846, 44.69623190476227, 44.69325571428608,
        44.69027952380989,  44.6873033333337, 44.68432714285751,
        44.68135095238132],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=612))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-34836260-6e69-48f3-a5cf-6407e2250380' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-34836260-6e69-48f3-a5cf-6407e2250380' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=612))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7baa6261-a47e-44f8-a658-054a0b610b6c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7baa6261-a47e-44f8-a658-054a0b610b6c' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
 </div>
 </section>
 <section id="clipping-data-according-to-a-polygon">
diff --git a/part1/xarray_pitfalls.html b/part1/xarray_pitfalls.html
index 8e876d9..70d117b 100644
--- a/part1/xarray_pitfalls.html
+++ b/part1/xarray_pitfalls.html
@@ -1021,7 +1021,7 @@ <h2>Open and read metadata through Xarray<a class="headerlink" href="#open-and-r
     NDVI     (t, y, x) uint8 ...
 Attributes:
     Conventions:  CF-1.8
-    institution:  openEO platform</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-728504d3-0f0d-44a6-8c94-624cc4927300' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-728504d3-0f0d-44a6-8c94-624cc4927300' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>t</span>: 20</li><li><span class='xr-has-index'>x</span>: 984</li><li><span class='xr-has-index'>y</span>: 657</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-61744617-4df3-4eac-812e-c38129c85718' class='xr-section-summary-in' type='checkbox'  checked><label for='section-61744617-4df3-4eac-812e-c38129c85718' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>t</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-7bbec0bf-061c-45c4-8234-ad1f4680b2ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7bbec0bf-061c-45c4-8234-ad1f4680b2ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3b7362e-47ba-4499-8c0e-7843b1123c3b' class='xr-var-data-in' type='checkbox'><label for='data-e3b7362e-47ba-4499-8c0e-7843b1123c3b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
+    institution:  openEO platform</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-9614ea50-e1c6-4c6d-a534-6d31c6d8a364' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9614ea50-e1c6-4c6d-a534-6d31c6d8a364' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>t</span>: 20</li><li><span class='xr-has-index'>x</span>: 984</li><li><span class='xr-has-index'>y</span>: 657</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f58ac377-25b2-4e5b-9c3b-6b1a0c924c80' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f58ac377-25b2-4e5b-9c3b-6b1a0c924c80' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>t</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-9f8ac3e3-9c1a-478d-89e7-83aa2967aa99' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f8ac3e3-9c1a-478d-89e7-83aa2967aa99' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51e1851b-4502-458d-a80b-56bbae20318a' class='xr-var-data-in' type='checkbox'><label for='data-51e1851b-4502-458d-a80b-56bbae20318a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
        &#x27;2022-01-21T00:00:00.000000000&#x27;, &#x27;2022-02-01T00:00:00.000000000&#x27;,
        &#x27;2022-02-11T00:00:00.000000000&#x27;, &#x27;2022-02-21T00:00:00.000000000&#x27;,
        &#x27;2022-03-01T00:00:00.000000000&#x27;, &#x27;2022-03-11T00:00:00.000000000&#x27;,
@@ -1031,12 +1031,12 @@ <h2>Open and read metadata through Xarray<a class="headerlink" href="#open-and-r
        &#x27;2022-05-21T00:00:00.000000000&#x27;, &#x27;2022-06-01T00:00:00.000000000&#x27;,
        &#x27;2022-06-11T00:00:00.000000000&#x27;, &#x27;2022-06-21T00:00:00.000000000&#x27;,
        &#x27;2022-07-01T00:00:00.000000000&#x27;, &#x27;2022-07-11T00:00:00.000000000&#x27;],
-      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-aee36972-b345-4ac2-8d80-401047ecb621' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aee36972-b345-4ac2-8d80-401047ecb621' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fbeaa959-c388-4ad6-977b-b858188f8f91' class='xr-var-data-in' type='checkbox'><label for='data-fbeaa959-c388-4ad6-977b-b858188f8f91' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.63 46.63 46.63 ... 44.68 44.68</div><input id='attrs-28e01afa-93d9-43a5-b4a3-da1091b5c825' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-28e01afa-93d9-43a5-b4a3-da1091b5c825' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-821a1865-1898-44ba-a3c0-38568261a665' class='xr-var-data-in' type='checkbox'><label for='data-821a1865-1898-44ba-a3c0-38568261a665' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.633732, 46.630756, 46.62778 , ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a16272cb-91d6-43d0-81a8-80a6b11d4ffd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a16272cb-91d6-43d0-81a8-80a6b11d4ffd' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-08433bbd-966e-46e4-a67f-0dc308afd3b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-08433bbd-966e-46e4-a67f-0dc308afd3b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-329a32e6-64c3-4c47-ad1b-b632c62492d9' class='xr-var-data-in' type='checkbox'><label for='data-329a32e6-64c3-4c47-ad1b-b632c62492d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;, DATUM[&quot;World Geodetic System 1984&quot;, SPHEROID[&quot;WGS 84&quot;, 6378137.0, 298.257223563, AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]], AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]], PRIMEM[&quot;Greenwich&quot;, 0.0, AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]], UNIT[&quot;degree&quot;, 0.017453292519943295], AXIS[&quot;Geodetic longitude&quot;, EAST], AXIS[&quot;Geodetic latitude&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;, DATUM[&quot;World Geodetic System 1984&quot;, SPHEROID[&quot;WGS 84&quot;, 6378137.0, 298.257223563, AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]], AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]], PRIMEM[&quot;Greenwich&quot;, 0.0, AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]], UNIT[&quot;degree&quot;, 0.017453292519943295], AXIS[&quot;Geodetic longitude&quot;, EAST], AXIS[&quot;Geodetic latitude&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=|S1]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NDVI</span></div><div class='xr-var-dims'>(t, y, x)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-175db1ef-81be-454e-bc8e-0b7b2a508028' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-175db1ef-81be-454e-bc8e-0b7b2a508028' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d28ac070-2cab-4202-a38b-ae55a54c7fdd' class='xr-var-data-in' type='checkbox'><label for='data-d28ac070-2cab-4202-a38b-ae55a54c7fdd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div><div class='xr-var-data'><pre>[12929760 values with dtype=uint8]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dce8ddd4-5ce9-48c0-9159-b871d21aac76' class='xr-section-summary-in' type='checkbox'  ><label for='section-dce8ddd4-5ce9-48c0-9159-b871d21aac76' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>t</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e8e35f07-9527-4a53-bb7d-1819ba99319f' class='xr-index-data-in' type='checkbox'/><label for='index-e8e35f07-9527-4a53-bb7d-1819ba99319f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-a2780b29-51cf-428f-ac11-cf7b617b0817' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2780b29-51cf-428f-ac11-cf7b617b0817' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01e99014-d5f0-48b6-9b86-0a7431a2fb38' class='xr-var-data-in' type='checkbox'><label for='data-01e99014-d5f0-48b6-9b86-0a7431a2fb38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.63 46.63 46.63 ... 44.68 44.68</div><input id='attrs-776785c4-15a2-4b4d-a3c3-f4250fe4c649' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-776785c4-15a2-4b4d-a3c3-f4250fe4c649' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-844a088a-8439-4cb0-b82c-0f56b8f83c18' class='xr-var-data-in' type='checkbox'><label for='data-844a088a-8439-4cb0-b82c-0f56b8f83c18' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.633732, 46.630756, 46.62778 , ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5c752ac0-388b-4a67-b3f1-d98ab6e10fd5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5c752ac0-388b-4a67-b3f1-d98ab6e10fd5' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-08664952-64d1-48fa-a4f9-93b5150f229a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-08664952-64d1-48fa-a4f9-93b5150f229a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1bf6b64-bda4-4a12-8acc-9c089522ad2f' class='xr-var-data-in' type='checkbox'><label for='data-b1bf6b64-bda4-4a12-8acc-9c089522ad2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;, DATUM[&quot;World Geodetic System 1984&quot;, SPHEROID[&quot;WGS 84&quot;, 6378137.0, 298.257223563, AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]], AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]], PRIMEM[&quot;Greenwich&quot;, 0.0, AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]], UNIT[&quot;degree&quot;, 0.017453292519943295], AXIS[&quot;Geodetic longitude&quot;, EAST], AXIS[&quot;Geodetic latitude&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;, DATUM[&quot;World Geodetic System 1984&quot;, SPHEROID[&quot;WGS 84&quot;, 6378137.0, 298.257223563, AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]], AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]], PRIMEM[&quot;Greenwich&quot;, 0.0, AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]], UNIT[&quot;degree&quot;, 0.017453292519943295], AXIS[&quot;Geodetic longitude&quot;, EAST], AXIS[&quot;Geodetic latitude&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=|S1]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NDVI</span></div><div class='xr-var-dims'>(t, y, x)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b5e85877-a996-4d3f-9caa-524f624729e1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b5e85877-a996-4d3f-9caa-524f624729e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d7fbf3a-0ee1-40b0-8672-1b118b0a64b6' class='xr-var-data-in' type='checkbox'><label for='data-4d7fbf3a-0ee1-40b0-8672-1b118b0a64b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div><div class='xr-var-data'><pre>[12929760 values with dtype=uint8]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6f5d6471-eb6d-46ab-aa94-107d98410af6' class='xr-section-summary-in' type='checkbox'  ><label for='section-6f5d6471-eb6d-46ab-aa94-107d98410af6' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>t</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e3c8023d-ce58-4e51-8364-a154712d8e4c' class='xr-index-data-in' type='checkbox'/><label for='index-e3c8023d-ce58-4e51-8364-a154712d8e4c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
                &#x27;2022-02-11&#x27;, &#x27;2022-02-21&#x27;, &#x27;2022-03-01&#x27;, &#x27;2022-03-11&#x27;,
                &#x27;2022-03-21&#x27;, &#x27;2022-04-01&#x27;, &#x27;2022-04-11&#x27;, &#x27;2022-04-21&#x27;,
                &#x27;2022-05-01&#x27;, &#x27;2022-05-11&#x27;, &#x27;2022-05-21&#x27;, &#x27;2022-06-01&#x27;,
                &#x27;2022-06-11&#x27;, &#x27;2022-06-21&#x27;, &#x27;2022-07-01&#x27;, &#x27;2022-07-11&#x27;],
-              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;t&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e8e606c2-c9e4-4641-94fa-d91831e59057' class='xr-index-data-in' type='checkbox'/><label for='index-e8e606c2-c9e4-4641-94fa-d91831e59057' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;t&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b60a6bed-b679-4b4c-acb2-4983221ad4ce' class='xr-index-data-in' type='checkbox'/><label for='index-b60a6bed-b679-4b4c-acb2-4983221ad4ce' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
          8.51066566666671,  8.513641857142915,  8.516618047619119,
         8.519594238095323,  8.522570428571527,   8.52554661904773,
         8.528522809523935,
@@ -1045,7 +1045,7 @@ <h2>Open and read metadata through Xarray<a class="headerlink" href="#open-and-r
        11.409475190489406,  11.41245138096561, 11.415427571441814,
        11.418403761918018, 11.421379952394222, 11.424356142870426,
         11.42733233334663],
-      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-29f0163d-c6eb-44f6-8087-b7cc5ca86d05' class='xr-index-data-in' type='checkbox'/><label for='index-29f0163d-c6eb-44f6-8087-b7cc5ca86d05' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.633731904761966, 46.630755714285776, 46.627779523809586,
+      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-56201e66-01b5-43b0-bbbd-2140ee6d733c' class='xr-index-data-in' type='checkbox'/><label for='index-56201e66-01b5-43b0-bbbd-2140ee6d733c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.633731904761966, 46.630755714285776, 46.627779523809586,
        46.624803333333396,  46.62182714285721,  46.61885095238102,
         46.61587476190483,  46.61289857142864,  46.60992238095245,
         46.60694619047626,
@@ -1054,7 +1054,7 @@ <h2>Open and read metadata through Xarray<a class="headerlink" href="#open-and-r
         44.69920809523846,  44.69623190476227,  44.69325571428608,
         44.69027952380989,   44.6873033333337,  44.68432714285751,
         44.68135095238132],
-      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=657))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1b77f422-4efb-4737-8c2f-21913e1322ee' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1b77f422-4efb-4737-8c2f-21913e1322ee' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.8</dd><dt><span>institution :</span></dt><dd>openEO platform</dd></dl></div></li></ul></div></div></div></div>
+      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=657))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-057240bc-e34a-4024-a5c8-bbdb7c904ef6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-057240bc-e34a-4024-a5c8-bbdb7c904ef6' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.8</dd><dt><span>institution :</span></dt><dd>openEO platform</dd></dl></div></li></ul></div></div></div></div>
 </div>
 </section>
 <section id="what-is-xarray">
@@ -1463,7 +1463,7 @@ <h2>Accessing Coordinates and Data Variables<a class="headerlink" href="#accessi
 Attributes:
     standard_name:  t
     long_name:      t
-    axis:           T</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'t'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>t</span>: 20</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-c7b2a037-49ab-4c93-a2b4-abd1a5af874d' class='xr-array-in' type='checkbox' checked><label for='section-c7b2a037-49ab-4c93-a2b4-abd1a5af874d' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2022-01-01 2022-01-11 2022-01-21 ... 2022-06-21 2022-07-01 2022-07-11</span></div><div class='xr-array-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
+    axis:           T</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'t'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>t</span>: 20</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-98345ca0-f427-4fd3-93cf-0300a028f942' class='xr-array-in' type='checkbox' checked><label for='section-98345ca0-f427-4fd3-93cf-0300a028f942' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2022-01-01 2022-01-11 2022-01-21 ... 2022-06-21 2022-07-01 2022-07-11</span></div><div class='xr-array-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
        &#x27;2022-01-21T00:00:00.000000000&#x27;, &#x27;2022-02-01T00:00:00.000000000&#x27;,
        &#x27;2022-02-11T00:00:00.000000000&#x27;, &#x27;2022-02-21T00:00:00.000000000&#x27;,
        &#x27;2022-03-01T00:00:00.000000000&#x27;, &#x27;2022-03-11T00:00:00.000000000&#x27;,
@@ -1473,7 +1473,7 @@ <h2>Accessing Coordinates and Data Variables<a class="headerlink" href="#accessi
        &#x27;2022-05-21T00:00:00.000000000&#x27;, &#x27;2022-06-01T00:00:00.000000000&#x27;,
        &#x27;2022-06-11T00:00:00.000000000&#x27;, &#x27;2022-06-21T00:00:00.000000000&#x27;,
        &#x27;2022-07-01T00:00:00.000000000&#x27;, &#x27;2022-07-11T00:00:00.000000000&#x27;],
-      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></div></li><li class='xr-section-item'><input id='section-9627cc1a-1ccb-4101-92bb-74139a53dba9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9627cc1a-1ccb-4101-92bb-74139a53dba9' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>t</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-ccdafa11-1513-4278-8958-4a28b4da8624' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ccdafa11-1513-4278-8958-4a28b4da8624' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5bf4447b-0fc9-40b5-8e8d-f505305182e5' class='xr-var-data-in' type='checkbox'><label for='data-5bf4447b-0fc9-40b5-8e8d-f505305182e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></div></li><li class='xr-section-item'><input id='section-f62a4922-b94b-4954-8d82-39692091b03a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f62a4922-b94b-4954-8d82-39692091b03a' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>t</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-8dc4be54-25bc-48ec-b7af-0e2461025f27' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8dc4be54-25bc-48ec-b7af-0e2461025f27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e00ae82e-ba9e-44dd-8e5d-dcdbc993e0f6' class='xr-var-data-in' type='checkbox'><label for='data-e00ae82e-ba9e-44dd-8e5d-dcdbc993e0f6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
        &#x27;2022-01-21T00:00:00.000000000&#x27;, &#x27;2022-02-01T00:00:00.000000000&#x27;,
        &#x27;2022-02-11T00:00:00.000000000&#x27;, &#x27;2022-02-21T00:00:00.000000000&#x27;,
        &#x27;2022-03-01T00:00:00.000000000&#x27;, &#x27;2022-03-11T00:00:00.000000000&#x27;,
@@ -1483,12 +1483,12 @@ <h2>Accessing Coordinates and Data Variables<a class="headerlink" href="#accessi
        &#x27;2022-05-21T00:00:00.000000000&#x27;, &#x27;2022-06-01T00:00:00.000000000&#x27;,
        &#x27;2022-06-11T00:00:00.000000000&#x27;, &#x27;2022-06-21T00:00:00.000000000&#x27;,
        &#x27;2022-07-01T00:00:00.000000000&#x27;, &#x27;2022-07-11T00:00:00.000000000&#x27;],
-      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f5704da8-badb-468a-8063-294008c32791' class='xr-section-summary-in' type='checkbox'  ><label for='section-f5704da8-badb-468a-8063-294008c32791' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>t</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b8d511f1-797f-45df-a8bd-874567ab094f' class='xr-index-data-in' type='checkbox'/><label for='index-b8d511f1-797f-45df-a8bd-874567ab094f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8f883639-e2ff-40f2-8216-5857f4389db9' class='xr-section-summary-in' type='checkbox'  ><label for='section-8f883639-e2ff-40f2-8216-5857f4389db9' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>t</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-11ef046e-2e77-4109-b5de-1a75e2b9db54' class='xr-index-data-in' type='checkbox'/><label for='index-11ef046e-2e77-4109-b5de-1a75e2b9db54' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
                &#x27;2022-02-11&#x27;, &#x27;2022-02-21&#x27;, &#x27;2022-03-01&#x27;, &#x27;2022-03-11&#x27;,
                &#x27;2022-03-21&#x27;, &#x27;2022-04-01&#x27;, &#x27;2022-04-11&#x27;, &#x27;2022-04-21&#x27;,
                &#x27;2022-05-01&#x27;, &#x27;2022-05-11&#x27;, &#x27;2022-05-21&#x27;, &#x27;2022-06-01&#x27;,
                &#x27;2022-06-11&#x27;, &#x27;2022-06-21&#x27;, &#x27;2022-07-01&#x27;, &#x27;2022-07-11&#x27;],
-              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;t&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7a7e7174-9855-47c4-8cb9-95c3cc0cd38b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7a7e7174-9855-47c4-8cb9-95c3cc0cd38b' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div></li></ul></div></div></div></div>
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;t&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ce994267-d3ec-4ebe-8fa6-b9d547baf20c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ce994267-d3ec-4ebe-8fa6-b9d547baf20c' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <p><code class="docutils literal notranslate"><span class="pre">cgls_ds.t</span></code> is a one-dimensional <code class="docutils literal notranslate"><span class="pre">xarray.DataArray</span></code> with dates of type <code class="docutils literal notranslate"><span class="pre">datetime64[ns]</span></code></p>
 <div class="cell docutils container">
@@ -1870,7 +1870,7 @@ <h2>Accessing Coordinates and Data Variables<a class="headerlink" href="#accessi
 Attributes:
     long_name:     NDVI
     units:         
-    grid_mapping:  crs</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>t</span>: 20</li><li><span class='xr-has-index'>y</span>: 657</li><li><span class='xr-has-index'>x</span>: 984</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-8e397851-f3d3-4e4e-ac32-780cfe44ba7d' class='xr-array-in' type='checkbox' checked><label for='section-8e397851-f3d3-4e4e-ac32-780cfe44ba7d' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[12929760 values with dtype=uint8]</pre></div></div></li><li class='xr-section-item'><input id='section-d7527035-3e65-4003-a066-37bfdccc9c8f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d7527035-3e65-4003-a066-37bfdccc9c8f' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>t</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-5dcbae11-3857-4d6f-8750-3a8b05306fee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5dcbae11-3857-4d6f-8750-3a8b05306fee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d3898a3-559b-4631-8f66-5a6d11d2f7cf' class='xr-var-data-in' type='checkbox'><label for='data-8d3898a3-559b-4631-8f66-5a6d11d2f7cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
+    grid_mapping:  crs</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>t</span>: 20</li><li><span class='xr-has-index'>y</span>: 657</li><li><span class='xr-has-index'>x</span>: 984</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-126ff684-d2b4-4699-8e70-6cd932d6a174' class='xr-array-in' type='checkbox' checked><label for='section-126ff684-d2b4-4699-8e70-6cd932d6a174' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[12929760 values with dtype=uint8]</pre></div></div></li><li class='xr-section-item'><input id='section-967c65c3-9c29-4ea3-b0d9-c4be4a4e2019' class='xr-section-summary-in' type='checkbox'  checked><label for='section-967c65c3-9c29-4ea3-b0d9-c4be4a4e2019' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>t</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-ea32c059-6c17-4f53-ba46-e0c7cf9c4c45' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea32c059-6c17-4f53-ba46-e0c7cf9c4c45' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2976c35-0392-4b9f-b960-c197a77f00bb' class='xr-var-data-in' type='checkbox'><label for='data-d2976c35-0392-4b9f-b960-c197a77f00bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
        &#x27;2022-01-21T00:00:00.000000000&#x27;, &#x27;2022-02-01T00:00:00.000000000&#x27;,
        &#x27;2022-02-11T00:00:00.000000000&#x27;, &#x27;2022-02-21T00:00:00.000000000&#x27;,
        &#x27;2022-03-01T00:00:00.000000000&#x27;, &#x27;2022-03-11T00:00:00.000000000&#x27;,
@@ -1880,12 +1880,12 @@ <h2>Accessing Coordinates and Data Variables<a class="headerlink" href="#accessi
        &#x27;2022-05-21T00:00:00.000000000&#x27;, &#x27;2022-06-01T00:00:00.000000000&#x27;,
        &#x27;2022-06-11T00:00:00.000000000&#x27;, &#x27;2022-06-21T00:00:00.000000000&#x27;,
        &#x27;2022-07-01T00:00:00.000000000&#x27;, &#x27;2022-07-11T00:00:00.000000000&#x27;],
-      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-3115104a-cae4-4a58-a869-3577e7827a16' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3115104a-cae4-4a58-a869-3577e7827a16' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18a8abcf-43b8-49fb-98cf-3ab8c533c7b6' class='xr-var-data-in' type='checkbox'><label for='data-18a8abcf-43b8-49fb-98cf-3ab8c533c7b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.63 46.63 46.63 ... 44.68 44.68</div><input id='attrs-18ae4dfb-0b53-4dad-8db0-38018c051501' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18ae4dfb-0b53-4dad-8db0-38018c051501' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f332808d-f978-4cc6-a025-97a65048f6f5' class='xr-var-data-in' type='checkbox'><label for='data-f332808d-f978-4cc6-a025-97a65048f6f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.633732, 46.630756, 46.62778 , ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-252629f0-fdee-4ee4-9d9d-15bacb81b049' class='xr-section-summary-in' type='checkbox'  ><label for='section-252629f0-fdee-4ee4-9d9d-15bacb81b049' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>t</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a2458f59-d5f1-4e55-83a6-eb93915ada47' class='xr-index-data-in' type='checkbox'/><label for='index-a2458f59-d5f1-4e55-83a6-eb93915ada47' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-ca6d28f9-70c2-4177-b43d-792456340cc1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca6d28f9-70c2-4177-b43d-792456340cc1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d52115d3-a22b-48d1-bea7-b317388ad230' class='xr-var-data-in' type='checkbox'><label for='data-d52115d3-a22b-48d1-bea7-b317388ad230' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.63 46.63 46.63 ... 44.68 44.68</div><input id='attrs-fb2bfe4d-764d-4cc3-ab25-58ce1641153e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb2bfe4d-764d-4cc3-ab25-58ce1641153e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95b78f7f-0741-42b6-94d1-9eecb4f1bfc6' class='xr-var-data-in' type='checkbox'><label for='data-95b78f7f-0741-42b6-94d1-9eecb4f1bfc6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.633732, 46.630756, 46.62778 , ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cd50f9bc-42e6-4810-88a2-5679e10836ff' class='xr-section-summary-in' type='checkbox'  ><label for='section-cd50f9bc-42e6-4810-88a2-5679e10836ff' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>t</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3089dd0e-16d7-414d-8771-994580febe21' class='xr-index-data-in' type='checkbox'/><label for='index-3089dd0e-16d7-414d-8771-994580febe21' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
                &#x27;2022-02-11&#x27;, &#x27;2022-02-21&#x27;, &#x27;2022-03-01&#x27;, &#x27;2022-03-11&#x27;,
                &#x27;2022-03-21&#x27;, &#x27;2022-04-01&#x27;, &#x27;2022-04-11&#x27;, &#x27;2022-04-21&#x27;,
                &#x27;2022-05-01&#x27;, &#x27;2022-05-11&#x27;, &#x27;2022-05-21&#x27;, &#x27;2022-06-01&#x27;,
                &#x27;2022-06-11&#x27;, &#x27;2022-06-21&#x27;, &#x27;2022-07-01&#x27;, &#x27;2022-07-11&#x27;],
-              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;t&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b34dac58-0023-4bda-acd2-6c6b380580b8' class='xr-index-data-in' type='checkbox'/><label for='index-b34dac58-0023-4bda-acd2-6c6b380580b8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;t&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3abdd2b7-9571-4944-91bf-e796ae2b9bdf' class='xr-index-data-in' type='checkbox'/><label for='index-3abdd2b7-9571-4944-91bf-e796ae2b9bdf' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
          8.51066566666671,  8.513641857142915,  8.516618047619119,
         8.519594238095323,  8.522570428571527,   8.52554661904773,
         8.528522809523935,
@@ -1894,7 +1894,7 @@ <h2>Accessing Coordinates and Data Variables<a class="headerlink" href="#accessi
        11.409475190489406,  11.41245138096561, 11.415427571441814,
        11.418403761918018, 11.421379952394222, 11.424356142870426,
         11.42733233334663],
-      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-13d5f371-b8bc-41aa-a7d0-ae4edc13dba1' class='xr-index-data-in' type='checkbox'/><label for='index-13d5f371-b8bc-41aa-a7d0-ae4edc13dba1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.633731904761966, 46.630755714285776, 46.627779523809586,
+      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-33b3431d-605d-424f-a968-f60c862279ab' class='xr-index-data-in' type='checkbox'/><label for='index-33b3431d-605d-424f-a968-f60c862279ab' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.633731904761966, 46.630755714285776, 46.627779523809586,
        46.624803333333396,  46.62182714285721,  46.61885095238102,
         46.61587476190483,  46.61289857142864,  46.60992238095245,
         46.60694619047626,
@@ -1903,7 +1903,7 @@ <h2>Accessing Coordinates and Data Variables<a class="headerlink" href="#accessi
         44.69920809523846,  44.69623190476227,  44.69325571428608,
         44.69027952380989,   44.6873033333337,  44.68432714285751,
         44.68135095238132],
-      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=657))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-58619ba8-c0ed-4812-ba75-c31412eba104' class='xr-section-summary-in' type='checkbox'  checked><label for='section-58619ba8-c0ed-4812-ba75-c31412eba104' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div></li></ul></div></div></div></div>
+      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=657))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e7836132-da56-47d8-bfda-df0147d0a695' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e7836132-da56-47d8-bfda-df0147d0a695' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <p><code class="docutils literal notranslate"><span class="pre">cgls_ds.NDVI</span></code> is a three-dimensional <code class="docutils literal notranslate"><span class="pre">xarray.DataArray</span></code> with NDVI values of type <code class="docutils literal notranslate"><span class="pre">uint8</span></code></p>
 <div class="cell docutils container">
@@ -2285,7 +2285,7 @@ <h2>Accessing Coordinates and Data Variables<a class="headerlink" href="#accessi
 Attributes:
     long_name:     NDVI
     units:         
-    grid_mapping:  crs</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>t</span>: 20</li><li><span class='xr-has-index'>y</span>: 657</li><li><span class='xr-has-index'>x</span>: 984</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-5bdfbb7d-be90-45fc-9cd9-687c0ece53f3' class='xr-array-in' type='checkbox' checked><label for='section-5bdfbb7d-be90-45fc-9cd9-687c0ece53f3' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[12929760 values with dtype=uint8]</pre></div></div></li><li class='xr-section-item'><input id='section-13d072e7-2f5f-450d-acf9-c5955550941a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-13d072e7-2f5f-450d-acf9-c5955550941a' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>t</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-02cd4741-80e9-4276-a9bb-c33de641e055' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-02cd4741-80e9-4276-a9bb-c33de641e055' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4de3e52e-85fb-49c9-8aa6-0592616fcddb' class='xr-var-data-in' type='checkbox'><label for='data-4de3e52e-85fb-49c9-8aa6-0592616fcddb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
+    grid_mapping:  crs</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>t</span>: 20</li><li><span class='xr-has-index'>y</span>: 657</li><li><span class='xr-has-index'>x</span>: 984</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-00fe88e8-799b-4e04-a3fe-7e8307b8df1f' class='xr-array-in' type='checkbox' checked><label for='section-00fe88e8-799b-4e04-a3fe-7e8307b8df1f' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[12929760 values with dtype=uint8]</pre></div></div></li><li class='xr-section-item'><input id='section-71196001-3654-4395-b888-bcf7c131504a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-71196001-3654-4395-b888-bcf7c131504a' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>t</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-21eae67b-bd27-47ac-bfaf-a90b1e5c1759' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21eae67b-bd27-47ac-bfaf-a90b1e5c1759' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-924affb1-530f-4f3b-8c2c-029518d5dea5' class='xr-var-data-in' type='checkbox'><label for='data-924affb1-530f-4f3b-8c2c-029518d5dea5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
        &#x27;2022-01-21T00:00:00.000000000&#x27;, &#x27;2022-02-01T00:00:00.000000000&#x27;,
        &#x27;2022-02-11T00:00:00.000000000&#x27;, &#x27;2022-02-21T00:00:00.000000000&#x27;,
        &#x27;2022-03-01T00:00:00.000000000&#x27;, &#x27;2022-03-11T00:00:00.000000000&#x27;,
@@ -2295,12 +2295,12 @@ <h2>Accessing Coordinates and Data Variables<a class="headerlink" href="#accessi
        &#x27;2022-05-21T00:00:00.000000000&#x27;, &#x27;2022-06-01T00:00:00.000000000&#x27;,
        &#x27;2022-06-11T00:00:00.000000000&#x27;, &#x27;2022-06-21T00:00:00.000000000&#x27;,
        &#x27;2022-07-01T00:00:00.000000000&#x27;, &#x27;2022-07-11T00:00:00.000000000&#x27;],
-      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-329f76aa-2e86-4968-8941-3bc96d57791a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-329f76aa-2e86-4968-8941-3bc96d57791a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69648028-44e2-44b6-b94c-c6d4eb5ea28d' class='xr-var-data-in' type='checkbox'><label for='data-69648028-44e2-44b6-b94c-c6d4eb5ea28d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.63 46.63 46.63 ... 44.68 44.68</div><input id='attrs-1b311fce-ff66-4057-b1c7-511af415022a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b311fce-ff66-4057-b1c7-511af415022a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d799379-2aac-4018-b303-d3f1878f7235' class='xr-var-data-in' type='checkbox'><label for='data-0d799379-2aac-4018-b303-d3f1878f7235' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.633732, 46.630756, 46.62778 , ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f80aaeb1-9327-498d-95b7-9b64bd9d5153' class='xr-section-summary-in' type='checkbox'  ><label for='section-f80aaeb1-9327-498d-95b7-9b64bd9d5153' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>t</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ee2ad603-ae22-46c2-b367-16105041ddbb' class='xr-index-data-in' type='checkbox'/><label for='index-ee2ad603-ae22-46c2-b367-16105041ddbb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-b87a6172-bd67-4162-b96b-c8e5cbce6faf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b87a6172-bd67-4162-b96b-c8e5cbce6faf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6f0d0cb-fa2e-42df-b5ea-5b35a88185ab' class='xr-var-data-in' type='checkbox'><label for='data-c6f0d0cb-fa2e-42df-b5ea-5b35a88185ab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.63 46.63 46.63 ... 44.68 44.68</div><input id='attrs-6e73cedd-d177-46a8-9186-8f572341f3ce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e73cedd-d177-46a8-9186-8f572341f3ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ae8b206-fa54-459b-a727-ab6263e1c65a' class='xr-var-data-in' type='checkbox'><label for='data-3ae8b206-fa54-459b-a727-ab6263e1c65a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.633732, 46.630756, 46.62778 , ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2366a944-2585-4ee1-baa3-71aa79598785' class='xr-section-summary-in' type='checkbox'  ><label for='section-2366a944-2585-4ee1-baa3-71aa79598785' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>t</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c7541ad3-d499-44e8-93ef-4c6bcb2dc4fc' class='xr-index-data-in' type='checkbox'/><label for='index-c7541ad3-d499-44e8-93ef-4c6bcb2dc4fc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
                &#x27;2022-02-11&#x27;, &#x27;2022-02-21&#x27;, &#x27;2022-03-01&#x27;, &#x27;2022-03-11&#x27;,
                &#x27;2022-03-21&#x27;, &#x27;2022-04-01&#x27;, &#x27;2022-04-11&#x27;, &#x27;2022-04-21&#x27;,
                &#x27;2022-05-01&#x27;, &#x27;2022-05-11&#x27;, &#x27;2022-05-21&#x27;, &#x27;2022-06-01&#x27;,
                &#x27;2022-06-11&#x27;, &#x27;2022-06-21&#x27;, &#x27;2022-07-01&#x27;, &#x27;2022-07-11&#x27;],
-              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;t&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5c944861-83db-4a2a-832b-fc0ec984626a' class='xr-index-data-in' type='checkbox'/><label for='index-5c944861-83db-4a2a-832b-fc0ec984626a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;t&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-474efa47-877f-4fb3-aa22-4c0879ea3a92' class='xr-index-data-in' type='checkbox'/><label for='index-474efa47-877f-4fb3-aa22-4c0879ea3a92' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
          8.51066566666671,  8.513641857142915,  8.516618047619119,
         8.519594238095323,  8.522570428571527,   8.52554661904773,
         8.528522809523935,
@@ -2309,7 +2309,7 @@ <h2>Accessing Coordinates and Data Variables<a class="headerlink" href="#accessi
        11.409475190489406,  11.41245138096561, 11.415427571441814,
        11.418403761918018, 11.421379952394222, 11.424356142870426,
         11.42733233334663],
-      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ea903f21-06ad-4f11-a395-f410b478d9d8' class='xr-index-data-in' type='checkbox'/><label for='index-ea903f21-06ad-4f11-a395-f410b478d9d8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.633731904761966, 46.630755714285776, 46.627779523809586,
+      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bf33d0ec-b61e-4c0f-bbf0-4235068ae94b' class='xr-index-data-in' type='checkbox'/><label for='index-bf33d0ec-b61e-4c0f-bbf0-4235068ae94b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.633731904761966, 46.630755714285776, 46.627779523809586,
        46.624803333333396,  46.62182714285721,  46.61885095238102,
         46.61587476190483,  46.61289857142864,  46.60992238095245,
         46.60694619047626,
@@ -2318,7 +2318,7 @@ <h2>Accessing Coordinates and Data Variables<a class="headerlink" href="#accessi
         44.69920809523846,  44.69623190476227,  44.69325571428608,
         44.69027952380989,   44.6873033333337,  44.68432714285751,
         44.68135095238132],
-      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=657))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bb9929e4-a984-4475-a997-cd97d720d9bf' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bb9929e4-a984-4475-a997-cd97d720d9bf' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div></li></ul></div></div></div></div>
+      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=657))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ab22f2f0-4a70-42d3-abd9-2e18355441ec' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ab22f2f0-4a70-42d3-abd9-2e18355441ec' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <p>Same can be achieved for attributes and a DataArray.attrs will return a dictionary.</p>
 <div class="cell docutils container">
@@ -2812,7 +2812,7 @@ <h2>Renaming Coordinates and Data Variables<a class="headerlink" href="#renaming
     NDVI     (time, lat, lon) uint8 255 255 255 255 255 ... 144 172 175 166 255
 Attributes:
     Conventions:  CF-1.8
-    institution:  openEO platform</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-73b0839f-3374-4caa-8d4e-c9874ea7b5b9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-73b0839f-3374-4caa-8d4e-c9874ea7b5b9' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 20</li><li><span class='xr-has-index'>lon</span>: 984</li><li><span class='xr-has-index'>lat</span>: 657</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e15e91c6-265d-490a-909f-4adcb67160c1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e15e91c6-265d-490a-909f-4adcb67160c1' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-219b0e27-9805-4852-bfbc-7a38900f9fb1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-219b0e27-9805-4852-bfbc-7a38900f9fb1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7fc26fa7-fdad-4a22-a0f2-a142ca630557' class='xr-var-data-in' type='checkbox'><label for='data-7fc26fa7-fdad-4a22-a0f2-a142ca630557' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
+    institution:  openEO platform</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f5fa0673-d4d7-4275-8212-7d35606e1d3a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f5fa0673-d4d7-4275-8212-7d35606e1d3a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 20</li><li><span class='xr-has-index'>lon</span>: 984</li><li><span class='xr-has-index'>lat</span>: 657</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-790e7f7e-84f4-454a-b4ee-644cd0831555' class='xr-section-summary-in' type='checkbox'  checked><label for='section-790e7f7e-84f4-454a-b4ee-644cd0831555' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-593cd9eb-c740-4d21-83f3-11b90a3c5e49' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-593cd9eb-c740-4d21-83f3-11b90a3c5e49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7d7aad8-6423-4cc7-9500-17f96e939943' class='xr-var-data-in' type='checkbox'><label for='data-f7d7aad8-6423-4cc7-9500-17f96e939943' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
        &#x27;2022-01-21T00:00:00.000000000&#x27;, &#x27;2022-02-01T00:00:00.000000000&#x27;,
        &#x27;2022-02-11T00:00:00.000000000&#x27;, &#x27;2022-02-21T00:00:00.000000000&#x27;,
        &#x27;2022-03-01T00:00:00.000000000&#x27;, &#x27;2022-03-11T00:00:00.000000000&#x27;,
@@ -2822,7 +2822,7 @@ <h2>Renaming Coordinates and Data Variables<a class="headerlink" href="#renaming
        &#x27;2022-05-21T00:00:00.000000000&#x27;, &#x27;2022-06-01T00:00:00.000000000&#x27;,
        &#x27;2022-06-11T00:00:00.000000000&#x27;, &#x27;2022-06-21T00:00:00.000000000&#x27;,
        &#x27;2022-07-01T00:00:00.000000000&#x27;, &#x27;2022-07-11T00:00:00.000000000&#x27;],
-      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-bf53dd85-9a0d-4aba-a9da-9ffbea383d37' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf53dd85-9a0d-4aba-a9da-9ffbea383d37' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81fff15f-bce1-4263-9cf3-215278c05ee5' class='xr-var-data-in' type='checkbox'><label for='data-81fff15f-bce1-4263-9cf3-215278c05ee5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.63 46.63 46.63 ... 44.68 44.68</div><input id='attrs-64a07f1f-3264-48f1-a774-6e4ed22ae3fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64a07f1f-3264-48f1-a774-6e4ed22ae3fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5f0ef3f-0860-4604-818e-6136faf3b8a9' class='xr-var-data-in' type='checkbox'><label for='data-d5f0ef3f-0860-4604-818e-6136faf3b8a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.633732, 46.630756, 46.62778 , ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cf9e41f8-7772-45ae-92cd-4ef266fda612' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cf9e41f8-7772-45ae-92cd-4ef266fda612' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-447dcd3b-a13b-4fc0-9640-e80eec5eae51' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-447dcd3b-a13b-4fc0-9640-e80eec5eae51' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8719eff0-c3b2-4c19-8bb2-9fbfc5756ad7' class='xr-var-data-in' type='checkbox'><label for='data-8719eff0-c3b2-4c19-8bb2-9fbfc5756ad7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;, DATUM[&quot;World Geodetic System 1984&quot;, SPHEROID[&quot;WGS 84&quot;, 6378137.0, 298.257223563, AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]], AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]], PRIMEM[&quot;Greenwich&quot;, 0.0, AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]], UNIT[&quot;degree&quot;, 0.017453292519943295], AXIS[&quot;Geodetic longitude&quot;, EAST], AXIS[&quot;Geodetic latitude&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;, DATUM[&quot;World Geodetic System 1984&quot;, SPHEROID[&quot;WGS 84&quot;, 6378137.0, 298.257223563, AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]], AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]], PRIMEM[&quot;Greenwich&quot;, 0.0, AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]], UNIT[&quot;degree&quot;, 0.017453292519943295], AXIS[&quot;Geodetic longitude&quot;, EAST], AXIS[&quot;Geodetic latitude&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=|S1]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NDVI</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>255 255 255 255 ... 172 175 166 255</div><input id='attrs-94caab91-2d7a-4d29-a964-d11a464316c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94caab91-2d7a-4d29-a964-d11a464316c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33d80eb7-186a-4d17-8694-fe1a1e49e6db' class='xr-var-data-in' type='checkbox'><label for='data-33d80eb7-186a-4d17-8694-fe1a1e49e6db' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div><div class='xr-var-data'><pre>array([[[255, 255, ..., 255, 255],
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-77808669-f891-46f4-9e79-26c6d3a1a09f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-77808669-f891-46f4-9e79-26c6d3a1a09f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04c2cca3-fc5a-4239-9b7c-8df84ca330b5' class='xr-var-data-in' type='checkbox'><label for='data-04c2cca3-fc5a-4239-9b7c-8df84ca330b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.63 46.63 46.63 ... 44.68 44.68</div><input id='attrs-8126c0a8-0459-4808-98c4-a7439bb6597b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8126c0a8-0459-4808-98c4-a7439bb6597b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3b49dc0-1896-4e4d-88f7-55fe365ef410' class='xr-var-data-in' type='checkbox'><label for='data-e3b49dc0-1896-4e4d-88f7-55fe365ef410' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.633732, 46.630756, 46.62778 , ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-053afbc3-c701-4463-8cd6-1d7407399de3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-053afbc3-c701-4463-8cd6-1d7407399de3' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8abaf305-35f8-4a3a-a4ea-7f87e42a687a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8abaf305-35f8-4a3a-a4ea-7f87e42a687a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecad49df-9cee-459c-b01a-d4243dcf2b8e' class='xr-var-data-in' type='checkbox'><label for='data-ecad49df-9cee-459c-b01a-d4243dcf2b8e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;, DATUM[&quot;World Geodetic System 1984&quot;, SPHEROID[&quot;WGS 84&quot;, 6378137.0, 298.257223563, AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]], AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]], PRIMEM[&quot;Greenwich&quot;, 0.0, AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]], UNIT[&quot;degree&quot;, 0.017453292519943295], AXIS[&quot;Geodetic longitude&quot;, EAST], AXIS[&quot;Geodetic latitude&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;, DATUM[&quot;World Geodetic System 1984&quot;, SPHEROID[&quot;WGS 84&quot;, 6378137.0, 298.257223563, AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]], AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]], PRIMEM[&quot;Greenwich&quot;, 0.0, AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]], UNIT[&quot;degree&quot;, 0.017453292519943295], AXIS[&quot;Geodetic longitude&quot;, EAST], AXIS[&quot;Geodetic latitude&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=|S1]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NDVI</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>255 255 255 255 ... 172 175 166 255</div><input id='attrs-1cce93d4-e591-476a-b464-764f14fca3ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1cce93d4-e591-476a-b464-764f14fca3ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-796a1864-1feb-416d-ba5c-ad11fe7dedc2' class='xr-var-data-in' type='checkbox'><label for='data-796a1864-1feb-416d-ba5c-ad11fe7dedc2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div><div class='xr-var-data'><pre>array([[[255, 255, ..., 255, 255],
         [255, 255, ..., 255, 255],
         ...,
         [121, 120, ..., 123, 255],
@@ -2846,12 +2846,12 @@ <h2>Renaming Coordinates and Data Variables<a class="headerlink" href="#renaming
         [255, 255, ..., 197, 255],
         ...,
         [166, 153, ..., 157, 255],
-        [159, 141, ..., 166, 255]]], dtype=uint8)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f4a29dd8-65b8-47a0-8d9e-b142571dcdbd' class='xr-section-summary-in' type='checkbox'  ><label for='section-f4a29dd8-65b8-47a0-8d9e-b142571dcdbd' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c41692c8-3038-4bae-836c-ad49dd46966e' class='xr-index-data-in' type='checkbox'/><label for='index-c41692c8-3038-4bae-836c-ad49dd46966e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
+        [159, 141, ..., 166, 255]]], dtype=uint8)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ede51323-ecf7-4f01-8dbf-108435578036' class='xr-section-summary-in' type='checkbox'  ><label for='section-ede51323-ecf7-4f01-8dbf-108435578036' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bc9fccd9-bead-4d31-aaef-c887656b13b4' class='xr-index-data-in' type='checkbox'/><label for='index-bc9fccd9-bead-4d31-aaef-c887656b13b4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
                &#x27;2022-02-11&#x27;, &#x27;2022-02-21&#x27;, &#x27;2022-03-01&#x27;, &#x27;2022-03-11&#x27;,
                &#x27;2022-03-21&#x27;, &#x27;2022-04-01&#x27;, &#x27;2022-04-11&#x27;, &#x27;2022-04-21&#x27;,
                &#x27;2022-05-01&#x27;, &#x27;2022-05-11&#x27;, &#x27;2022-05-21&#x27;, &#x27;2022-06-01&#x27;,
                &#x27;2022-06-11&#x27;, &#x27;2022-06-21&#x27;, &#x27;2022-07-01&#x27;, &#x27;2022-07-11&#x27;],
-              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-74697639-05ae-42b0-a08d-4900da714e5a' class='xr-index-data-in' type='checkbox'/><label for='index-74697639-05ae-42b0-a08d-4900da714e5a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1454aba9-1b76-473f-96d6-a3f6cbc4bcca' class='xr-index-data-in' type='checkbox'/><label for='index-1454aba9-1b76-473f-96d6-a3f6cbc4bcca' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
          8.51066566666671,  8.513641857142915,  8.516618047619119,
         8.519594238095323,  8.522570428571527,   8.52554661904773,
         8.528522809523935,
@@ -2860,7 +2860,7 @@ <h2>Renaming Coordinates and Data Variables<a class="headerlink" href="#renaming
        11.409475190489406,  11.41245138096561, 11.415427571441814,
        11.418403761918018, 11.421379952394222, 11.424356142870426,
         11.42733233334663],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ae2ca2c4-328b-49d4-b6af-75fee531b9fe' class='xr-index-data-in' type='checkbox'/><label for='index-ae2ca2c4-328b-49d4-b6af-75fee531b9fe' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.633731904761966, 46.630755714285776, 46.627779523809586,
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-14740442-6fa5-4346-83ff-ffab13389b57' class='xr-index-data-in' type='checkbox'/><label for='index-14740442-6fa5-4346-83ff-ffab13389b57' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.633731904761966, 46.630755714285776, 46.627779523809586,
        46.624803333333396,  46.62182714285721,  46.61885095238102,
         46.61587476190483,  46.61289857142864,  46.60992238095245,
         46.60694619047626,
@@ -2869,7 +2869,7 @@ <h2>Renaming Coordinates and Data Variables<a class="headerlink" href="#renaming
         44.69920809523846,  44.69623190476227,  44.69325571428608,
         44.69027952380989,   44.6873033333337,  44.68432714285751,
         44.68135095238132],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=657))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-49b40390-e452-4d4f-bce5-92cb4fac6309' class='xr-section-summary-in' type='checkbox'  checked><label for='section-49b40390-e452-4d4f-bce5-92cb4fac6309' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.8</dd><dt><span>institution :</span></dt><dd>openEO platform</dd></dl></div></li></ul></div></div></div></div>
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=657))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d0cb942e-df87-4994-aa9e-a6d9bc205472' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d0cb942e-df87-4994-aa9e-a6d9bc205472' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.8</dd><dt><span>institution :</span></dt><dd>openEO platform</dd></dl></div></li></ul></div></div></div></div>
 </div>
 </section>
 <section id="selection-methods">
@@ -3254,7 +3254,7 @@ <h2>Selection methods<a class="headerlink" href="#selection-methods" title="Perm
 Attributes:
     long_name:     NDVI
     units:         
-    grid_mapping:  crs</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-2e962500-60b8-4fcb-b5ad-671a8c086ccb' class='xr-array-in' type='checkbox' checked><label for='section-2e962500-60b8-4fcb-b5ad-671a8c086ccb' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>87</span></div><div class='xr-array-data'><pre>array(87, dtype=uint8)</pre></div></div></li><li class='xr-section-item'><input id='section-2f8adacd-9f86-4cba-9f06-7ce423523719' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2f8adacd-9f86-4cba-9f06-7ce423523719' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01</div><input id='attrs-5e2610f0-20f0-4695-a21a-e7d13caf974d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e2610f0-20f0-4695-a21a-e7d13caf974d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d0ce298-9ac0-4b66-b878-b51b6aed32ad' class='xr-var-data-in' type='checkbox'><label for='data-8d0ce298-9ac0-4b66-b878-b51b6aed32ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-01-01T00:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.799</div><input id='attrs-a9eb4624-baa8-40e3-9156-95752410a16d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a9eb4624-baa8-40e3-9156-95752410a16d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7480e7bf-d64d-4f3b-9f1e-4b91827da7f6' class='xr-var-data-in' type='checkbox'><label for='data-7480e7bf-d64d-4f3b-9f1e-4b91827da7f6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array(8.79935614)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.34</div><input id='attrs-011ffe4b-68e6-4591-8d49-02358f42f437' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-011ffe4b-68e6-4591-8d49-02358f42f437' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab05f982-c870-4795-9824-fc6cd44ff6e5' class='xr-var-data-in' type='checkbox'><label for='data-ab05f982-c870-4795-9824-fc6cd44ff6e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array(46.33611286)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3ba90b5b-836e-446e-ada4-7c5ada9eebe9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3ba90b5b-836e-446e-ada4-7c5ada9eebe9' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-1f52dbb3-e081-4f58-89fb-95e5ae474484' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1f52dbb3-e081-4f58-89fb-95e5ae474484' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div></li></ul></div></div></div></div>
+    grid_mapping:  crs</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-04648440-7b68-417e-a858-93f10aed12e4' class='xr-array-in' type='checkbox' checked><label for='section-04648440-7b68-417e-a858-93f10aed12e4' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>87</span></div><div class='xr-array-data'><pre>array(87, dtype=uint8)</pre></div></div></li><li class='xr-section-item'><input id='section-6199c57d-6f01-401b-a4f3-c45f3b23c284' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6199c57d-6f01-401b-a4f3-c45f3b23c284' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01</div><input id='attrs-b1e39c45-be17-4cef-b2a7-92bdf9309f23' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b1e39c45-be17-4cef-b2a7-92bdf9309f23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8c1d277-5765-4465-bbef-6c8649838c04' class='xr-var-data-in' type='checkbox'><label for='data-b8c1d277-5765-4465-bbef-6c8649838c04' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-01-01T00:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.799</div><input id='attrs-23b5f4bf-92f7-4266-8df6-f49e0f352a79' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-23b5f4bf-92f7-4266-8df6-f49e0f352a79' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79c99275-45f3-468b-b975-392ebd97018b' class='xr-var-data-in' type='checkbox'><label for='data-79c99275-45f3-468b-b975-392ebd97018b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array(8.79935614)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.34</div><input id='attrs-f53866e1-e8e8-4e2f-8393-ed5d29029dad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f53866e1-e8e8-4e2f-8393-ed5d29029dad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e293d3f-da4b-4d38-8883-426e7104e1d6' class='xr-var-data-in' type='checkbox'><label for='data-7e293d3f-da4b-4d38-8883-426e7104e1d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array(46.33611286)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-30201bf7-c8ae-4581-b67a-6cc4a9dd1577' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-30201bf7-c8ae-4581-b67a-6cc4a9dd1577' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-2c395591-1fad-43bd-8c2d-5fdf94101cf5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2c395591-1fad-43bd-8c2d-5fdf94101cf5' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <p>or slicing</p>
 <div class="cell docutils container">
@@ -3660,7 +3660,7 @@ <h2>Selection methods<a class="headerlink" href="#selection-methods" title="Perm
 Attributes:
     long_name:     NDVI
     units:         
-    grid_mapping:  crs</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 5</li><li><span class='xr-has-index'>lat</span>: 10</li><li><span class='xr-has-index'>lon</span>: 10</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-851ca70e-b23b-4eb8-814a-afeb13bfe663' class='xr-array-in' type='checkbox' checked><label for='section-851ca70e-b23b-4eb8-814a-afeb13bfe663' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>87 0 0 107 96 103 98 255 255 76 ... 255 0 109 112 17 0 18 255 255 60</span></div><div class='xr-array-data'><pre>array([[[ 87,   0, ..., 255,  76],
+    grid_mapping:  crs</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 5</li><li><span class='xr-has-index'>lat</span>: 10</li><li><span class='xr-has-index'>lon</span>: 10</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e056f1f5-6c23-4a72-b3a2-d72e45da96c4' class='xr-array-in' type='checkbox' checked><label for='section-e056f1f5-6c23-4a72-b3a2-d72e45da96c4' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>87 0 0 107 96 103 98 255 255 76 ... 255 0 109 112 17 0 18 255 255 60</span></div><div class='xr-array-data'><pre>array([[[ 87,   0, ..., 255,  76],
         [114,   0, ...,  47,  45],
         ...,
         [ 81,  82, ..., 255, 255],
@@ -3684,21 +3684,21 @@ <h2>Selection methods<a class="headerlink" href="#selection-methods" title="Perm
         [116,  33, ...,  17,   7],
         ...,
         [255, 172, ...,  95,  72],
-        [255,   0, ..., 255,  60]]], dtype=uint8)</pre></div></div></li><li class='xr-section-item'><input id='section-5cb8de80-b63a-4d33-9a53-92726ca91cd6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5cb8de80-b63a-4d33-9a53-92726ca91cd6' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-02-11</div><input id='attrs-3dd967e4-5e6a-4a15-8d36-9bd0ab9965f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3dd967e4-5e6a-4a15-8d36-9bd0ab9965f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f1f35c9-ef05-495a-9785-aacb58ea6798' class='xr-var-data-in' type='checkbox'><label for='data-9f1f35c9-ef05-495a-9785-aacb58ea6798' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
+        [255,   0, ..., 255,  60]]], dtype=uint8)</pre></div></div></li><li class='xr-section-item'><input id='section-39973c1a-0362-48e2-85c0-0ad44ab1f0a0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-39973c1a-0362-48e2-85c0-0ad44ab1f0a0' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-02-11</div><input id='attrs-83b0cc40-1f9d-4e78-aa69-ce057269e8a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-83b0cc40-1f9d-4e78-aa69-ce057269e8a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43ffba28-3c46-4e94-8792-c0dc22c82666' class='xr-var-data-in' type='checkbox'><label for='data-43ffba28-3c46-4e94-8792-c0dc22c82666' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
        &#x27;2022-01-21T00:00:00.000000000&#x27;, &#x27;2022-02-01T00:00:00.000000000&#x27;,
-       &#x27;2022-02-11T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.799 8.802 8.805 ... 8.823 8.826</div><input id='attrs-acb74274-9ddd-46d7-9690-d8862db5bd81' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-acb74274-9ddd-46d7-9690-d8862db5bd81' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d5831a5-4b6e-4484-8036-fb9d99b38d6b' class='xr-var-data-in' type='checkbox'><label for='data-4d5831a5-4b6e-4484-8036-fb9d99b38d6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([8.799356, 8.802332, 8.805309, 8.808285, 8.811261, 8.814237, 8.817213,
-       8.820189, 8.823166, 8.826142])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.34 46.33 46.33 ... 46.31 46.31</div><input id='attrs-72259306-e0f3-4c2a-ae06-5956fafe08d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-72259306-e0f3-4c2a-ae06-5956fafe08d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38b87f8a-8b53-43de-a6ce-bd412923d609' class='xr-var-data-in' type='checkbox'><label for='data-38b87f8a-8b53-43de-a6ce-bd412923d609' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.336113, 46.333137, 46.33016 , 46.327184, 46.324208, 46.321232,
-       46.318256, 46.31528 , 46.312303, 46.309327])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f58c8737-e918-4fc6-b42d-e45951868183' class='xr-section-summary-in' type='checkbox'  ><label for='section-f58c8737-e918-4fc6-b42d-e45951868183' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-60c21eea-6c56-4fbe-b19a-ebf9ab56a4d5' class='xr-index-data-in' type='checkbox'/><label for='index-60c21eea-6c56-4fbe-b19a-ebf9ab56a4d5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
+       &#x27;2022-02-11T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.799 8.802 8.805 ... 8.823 8.826</div><input id='attrs-a7dc7f4c-3c42-43c1-90b2-cfddfe913c9b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a7dc7f4c-3c42-43c1-90b2-cfddfe913c9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4389eafa-72b3-4d84-acd2-e02ca88c7435' class='xr-var-data-in' type='checkbox'><label for='data-4389eafa-72b3-4d84-acd2-e02ca88c7435' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([8.799356, 8.802332, 8.805309, 8.808285, 8.811261, 8.814237, 8.817213,
+       8.820189, 8.823166, 8.826142])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.34 46.33 46.33 ... 46.31 46.31</div><input id='attrs-c95eae27-1ea1-418d-9ab7-119f36c2f74f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c95eae27-1ea1-418d-9ab7-119f36c2f74f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7cb6dd42-353a-4216-99e1-54625136bd0f' class='xr-var-data-in' type='checkbox'><label for='data-7cb6dd42-353a-4216-99e1-54625136bd0f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.336113, 46.333137, 46.33016 , 46.327184, 46.324208, 46.321232,
+       46.318256, 46.31528 , 46.312303, 46.309327])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-824d1ce3-505d-4be2-a0eb-beec37a65363' class='xr-section-summary-in' type='checkbox'  ><label for='section-824d1ce3-505d-4be2-a0eb-beec37a65363' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-42ad711f-efa5-4147-87bb-3bc8320505cb' class='xr-index-data-in' type='checkbox'/><label for='index-42ad711f-efa5-4147-87bb-3bc8320505cb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
                &#x27;2022-02-11&#x27;],
-              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ee0e5efc-8f36-4896-b551-88e137ea6997' class='xr-index-data-in' type='checkbox'/><label for='index-ee0e5efc-8f36-4896-b551-88e137ea6997' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([8.799356142858498, 8.802332333334702, 8.805308523810906,
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-31daa404-1b38-4bb9-b67e-d8511fa3ea35' class='xr-index-data-in' type='checkbox'/><label for='index-31daa404-1b38-4bb9-b67e-d8511fa3ea35' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([8.799356142858498, 8.802332333334702, 8.805308523810906,
         8.80828471428711, 8.811260904763314, 8.814237095239518,
        8.817213285715722, 8.820189476191926,  8.82316566666813,
        8.826141857144334],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a745ec4a-8402-4f0d-b6db-bd3dd4ae6017' class='xr-index-data-in' type='checkbox'/><label for='index-a745ec4a-8402-4f0d-b6db-bd3dd4ae6017' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.336112857142965, 46.333136666666775, 46.330160476190585,
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e30d74e5-f483-4e34-9a4f-1f6f4440bd73' class='xr-index-data-in' type='checkbox'/><label for='index-e30d74e5-f483-4e34-9a4f-1f6f4440bd73' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.336112857142965, 46.333136666666775, 46.330160476190585,
        46.327184285714395, 46.324208095238205, 46.321231904762016,
        46.318255714285826, 46.315279523809636, 46.312303333333446,
        46.309327142857256],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-916e0f11-a3a8-48f0-8010-61035ae62611' class='xr-section-summary-in' type='checkbox'  checked><label for='section-916e0f11-a3a8-48f0-8010-61035ae62611' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div></li></ul></div></div></div></div>
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7b9f3c7b-5756-4059-a761-f5a4964409eb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7b9f3c7b-5756-4059-a761-f5a4964409eb' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <p>As it is not easy to remember the order of dimensions, Xarray really helps by making it possible to select the position using names:</p>
 <ul class="simple">
@@ -4097,7 +4097,7 @@ <h2>Selection methods<a class="headerlink" href="#selection-methods" title="Perm
 Attributes:
     long_name:     NDVI
     units:         
-    grid_mapping:  crs</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-77383b70-eb31-4486-b19e-9e6467671ffd' class='xr-array-in' type='checkbox' checked><label for='section-77383b70-eb31-4486-b19e-9e6467671ffd' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>87</span></div><div class='xr-array-data'><pre>array(87, dtype=uint8)</pre></div></div></li><li class='xr-section-item'><input id='section-f439b828-517d-4b26-b952-b40b7e6f3bb8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f439b828-517d-4b26-b952-b40b7e6f3bb8' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01</div><input id='attrs-3ff2626b-b67f-4e6b-8af2-877f51c2974b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ff2626b-b67f-4e6b-8af2-877f51c2974b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d4edb7c-225c-44ee-b5cd-2ee69bd26c92' class='xr-var-data-in' type='checkbox'><label for='data-8d4edb7c-225c-44ee-b5cd-2ee69bd26c92' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-01-01T00:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.799</div><input id='attrs-26cfb26d-c687-47d0-911d-deab77a525db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26cfb26d-c687-47d0-911d-deab77a525db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5aac7331-2091-4d87-b12d-3645cde65a8c' class='xr-var-data-in' type='checkbox'><label for='data-5aac7331-2091-4d87-b12d-3645cde65a8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array(8.79935614)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.34</div><input id='attrs-8a85e2ff-7b4e-4cf8-9e36-b135c386f55e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a85e2ff-7b4e-4cf8-9e36-b135c386f55e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1d69034-666e-42a7-8b15-4a46eab85d92' class='xr-var-data-in' type='checkbox'><label for='data-d1d69034-666e-42a7-8b15-4a46eab85d92' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array(46.33611286)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b8c25304-d2c6-4cb8-bc7a-81f0e6ddb74a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b8c25304-d2c6-4cb8-bc7a-81f0e6ddb74a' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-ef9f7132-c586-4eef-b906-671322f69e45' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ef9f7132-c586-4eef-b906-671322f69e45' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div></li></ul></div></div></div></div>
+    grid_mapping:  crs</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-0719296a-df9a-42ef-add2-8765df337461' class='xr-array-in' type='checkbox' checked><label for='section-0719296a-df9a-42ef-add2-8765df337461' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>87</span></div><div class='xr-array-data'><pre>array(87, dtype=uint8)</pre></div></div></li><li class='xr-section-item'><input id='section-17e8eaf9-d7b7-42f9-a87d-5d5e9fe2b250' class='xr-section-summary-in' type='checkbox'  checked><label for='section-17e8eaf9-d7b7-42f9-a87d-5d5e9fe2b250' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01</div><input id='attrs-a56e0b6c-9cbf-4e77-b96b-459a0e62b9bf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a56e0b6c-9cbf-4e77-b96b-459a0e62b9bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3b2aa7b-1baa-49d7-9e37-230f23ebe0fc' class='xr-var-data-in' type='checkbox'><label for='data-e3b2aa7b-1baa-49d7-9e37-230f23ebe0fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-01-01T00:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.799</div><input id='attrs-dc236a1e-f021-4f7a-b303-75b2fcda8138' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc236a1e-f021-4f7a-b303-75b2fcda8138' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5f2f4dd-cb1d-4b4b-8027-9ed05c773706' class='xr-var-data-in' type='checkbox'><label for='data-a5f2f4dd-cb1d-4b4b-8027-9ed05c773706' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array(8.79935614)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.34</div><input id='attrs-6039eb7c-b968-469b-a9c2-eea90f65f66f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6039eb7c-b968-469b-a9c2-eea90f65f66f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23449ca8-cb24-4e6d-8594-ee7f07faf5a4' class='xr-var-data-in' type='checkbox'><label for='data-23449ca8-cb24-4e6d-8594-ee7f07faf5a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array(46.33611286)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-22979c95-69c1-44f1-bd77-f9c484b16665' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-22979c95-69c1-44f1-bd77-f9c484b16665' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-6a98c204-91bb-495c-b77d-2f068b696cb7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6a98c204-91bb-495c-b77d-2f068b696cb7' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <p>The more common way to select a point is through the labeled coordinate using the <code class="docutils literal notranslate"><span class="pre">.sel</span></code> method.</p>
 <div class="cell docutils container">
@@ -4485,13 +4485,13 @@ <h2>Selection methods<a class="headerlink" href="#selection-methods" title="Perm
 Attributes:
     long_name:     NDVI
     units:         
-    grid_mapping:  crs</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 657</li><li><span class='xr-has-index'>lon</span>: 984</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-a2f07ff8-6d1f-488b-8633-d3059027a832' class='xr-array-in' type='checkbox' checked><label for='section-a2f07ff8-6d1f-488b-8633-d3059027a832' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>255 255 255 255 255 255 255 255 255 ... 124 111 89 97 98 88 81 120 255</span></div><div class='xr-array-data'><pre>array([[255, 255, 255, ..., 255, 255, 255],
+    grid_mapping:  crs</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 657</li><li><span class='xr-has-index'>lon</span>: 984</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-19da673b-bc1c-4cca-9258-664145bacbff' class='xr-array-in' type='checkbox' checked><label for='section-19da673b-bc1c-4cca-9258-664145bacbff' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>255 255 255 255 255 255 255 255 255 ... 124 111 89 97 98 88 81 120 255</span></div><div class='xr-array-data'><pre>array([[255, 255, 255, ..., 255, 255, 255],
        [255, 255, 255, ..., 255, 255, 255],
        [255, 255, 255, ..., 255, 255, 255],
        ...,
        [ 83, 100,  99, ..., 124, 108, 255],
        [121, 120, 112, ..., 124, 123, 255],
-       [113,  93,  93, ...,  81, 120, 255]], dtype=uint8)</pre></div></div></li><li class='xr-section-item'><input id='section-73159696-f92a-4599-b7e0-67e0f8a12f1d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-73159696-f92a-4599-b7e0-67e0f8a12f1d' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01</div><input id='attrs-54b560be-d479-46c9-a432-e0cad87dd126' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-54b560be-d479-46c9-a432-e0cad87dd126' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2270a9b1-e59b-4876-b2d0-63af8a9db468' class='xr-var-data-in' type='checkbox'><label for='data-2270a9b1-e59b-4876-b2d0-63af8a9db468' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-01-01T00:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-5f79b045-0017-4643-95cc-cd3cdd77fa8c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5f79b045-0017-4643-95cc-cd3cdd77fa8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09b69609-ac7f-4890-b3f3-a4c2e4d67446' class='xr-var-data-in' type='checkbox'><label for='data-09b69609-ac7f-4890-b3f3-a4c2e4d67446' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.63 46.63 46.63 ... 44.68 44.68</div><input id='attrs-4b3bc925-b531-4fcf-9730-ca8c8eed7fd6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b3bc925-b531-4fcf-9730-ca8c8eed7fd6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0152f99a-b5a0-41d6-879a-03c246cc11a5' class='xr-var-data-in' type='checkbox'><label for='data-0152f99a-b5a0-41d6-879a-03c246cc11a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.633732, 46.630756, 46.62778 , ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-79a0ea28-7cf0-4e2f-bd95-7990684a5fda' class='xr-section-summary-in' type='checkbox'  ><label for='section-79a0ea28-7cf0-4e2f-bd95-7990684a5fda' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9061e530-d7ef-4b64-b68f-c659107ceb8a' class='xr-index-data-in' type='checkbox'/><label for='index-9061e530-d7ef-4b64-b68f-c659107ceb8a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
+       [113,  93,  93, ...,  81, 120, 255]], dtype=uint8)</pre></div></div></li><li class='xr-section-item'><input id='section-58f73da7-920a-4ec6-9816-add9306b42aa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-58f73da7-920a-4ec6-9816-add9306b42aa' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01</div><input id='attrs-1cdd66db-5157-4964-a91f-0ecdae1a1b24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1cdd66db-5157-4964-a91f-0ecdae1a1b24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97ddd03a-19ae-4da8-b6ef-bc1fafe2864a' class='xr-var-data-in' type='checkbox'><label for='data-97ddd03a-19ae-4da8-b6ef-bc1fafe2864a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-01-01T00:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-8a666fc3-181a-48c9-861c-de7f07bb6ed7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a666fc3-181a-48c9-861c-de7f07bb6ed7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed47ed80-6474-461e-91be-bd4089ec8b88' class='xr-var-data-in' type='checkbox'><label for='data-ed47ed80-6474-461e-91be-bd4089ec8b88' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.63 46.63 46.63 ... 44.68 44.68</div><input id='attrs-8f5a7c40-1de0-41b0-af90-b76fa41b1f82' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f5a7c40-1de0-41b0-af90-b76fa41b1f82' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0838428f-49f2-432d-b636-837f458b5115' class='xr-var-data-in' type='checkbox'><label for='data-0838428f-49f2-432d-b636-837f458b5115' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.633732, 46.630756, 46.62778 , ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f4ffbcb0-a003-4aac-b131-c30538d736ac' class='xr-section-summary-in' type='checkbox'  ><label for='section-f4ffbcb0-a003-4aac-b131-c30538d736ac' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3c741819-08d0-42f9-8b6d-416727d93118' class='xr-index-data-in' type='checkbox'/><label for='index-3c741819-08d0-42f9-8b6d-416727d93118' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
          8.51066566666671,  8.513641857142915,  8.516618047619119,
         8.519594238095323,  8.522570428571527,   8.52554661904773,
         8.528522809523935,
@@ -4500,7 +4500,7 @@ <h2>Selection methods<a class="headerlink" href="#selection-methods" title="Perm
        11.409475190489406,  11.41245138096561, 11.415427571441814,
        11.418403761918018, 11.421379952394222, 11.424356142870426,
         11.42733233334663],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b5103d94-e3d8-4715-b76c-14e1dd16b7dc' class='xr-index-data-in' type='checkbox'/><label for='index-b5103d94-e3d8-4715-b76c-14e1dd16b7dc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.633731904761966, 46.630755714285776, 46.627779523809586,
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-948603a6-3348-4d4c-b63c-d2ba1ee5cb64' class='xr-index-data-in' type='checkbox'/><label for='index-948603a6-3348-4d4c-b63c-d2ba1ee5cb64' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.633731904761966, 46.630755714285776, 46.627779523809586,
        46.624803333333396,  46.62182714285721,  46.61885095238102,
         46.61587476190483,  46.61289857142864,  46.60992238095245,
         46.60694619047626,
@@ -4509,7 +4509,7 @@ <h2>Selection methods<a class="headerlink" href="#selection-methods" title="Perm
         44.69920809523846,  44.69623190476227,  44.69325571428608,
         44.69027952380989,   44.6873033333337,  44.68432714285751,
         44.68135095238132],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=657))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5ac20858-6e34-4521-bce6-b9b6275a7aa5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5ac20858-6e34-4521-bce6-b9b6275a7aa5' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div></li></ul></div></div></div></div>
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=657))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4373a4b1-e45d-48f6-85eb-c36a1948269c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4373a4b1-e45d-48f6-85eb-c36a1948269c' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <p>Time is easy to be used as there is a 1 to 1 correspondence with values in the index, float values are not that easy to be used and a small discrepancy can make a big difference in terms of results.</p>
 <p>Coordinates are always affected by precision issues; the best option to quickly get a point over the coordinates is to set the sampling method (method=’’) that will search for the closest point according to the specified one.</p>
@@ -4901,7 +4901,7 @@ <h2>Selection methods<a class="headerlink" href="#selection-methods" title="Perm
     NDVI     (time) uint8 90 122 99 78 108 81 106 ... 181 223 231 195 215 234
 Attributes:
     Conventions:  CF-1.8
-    institution:  openEO platform</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-bddc5975-a636-40a3-91ba-957d19ae3b3c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bddc5975-a636-40a3-91ba-957d19ae3b3c' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 20</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-cb37a9eb-fa06-44cf-b9c0-1a797e8bcfb7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cb37a9eb-fa06-44cf-b9c0-1a797e8bcfb7' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-8e051086-1cd5-49a1-9ba8-2a4bbc2670df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e051086-1cd5-49a1-9ba8-2a4bbc2670df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba4660d9-ddf6-4009-be81-4793bab1d4fb' class='xr-var-data-in' type='checkbox'><label for='data-ba4660d9-ddf6-4009-be81-4793bab1d4fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
+    institution:  openEO platform</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-cf677b81-d802-499e-9393-3e085221559b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cf677b81-d802-499e-9393-3e085221559b' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 20</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-87cef546-6197-45ca-a9f9-2cf360b86993' class='xr-section-summary-in' type='checkbox'  checked><label for='section-87cef546-6197-45ca-a9f9-2cf360b86993' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-6e79544f-7e57-47c5-9e45-771692a61536' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e79544f-7e57-47c5-9e45-771692a61536' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98e2c6a5-8557-44d3-8cec-7ecb0329a393' class='xr-var-data-in' type='checkbox'><label for='data-98e2c6a5-8557-44d3-8cec-7ecb0329a393' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
        &#x27;2022-01-21T00:00:00.000000000&#x27;, &#x27;2022-02-01T00:00:00.000000000&#x27;,
        &#x27;2022-02-11T00:00:00.000000000&#x27;, &#x27;2022-02-21T00:00:00.000000000&#x27;,
        &#x27;2022-03-01T00:00:00.000000000&#x27;, &#x27;2022-03-11T00:00:00.000000000&#x27;,
@@ -4911,13 +4911,13 @@ <h2>Selection methods<a class="headerlink" href="#selection-methods" title="Perm
        &#x27;2022-05-21T00:00:00.000000000&#x27;, &#x27;2022-06-01T00:00:00.000000000&#x27;,
        &#x27;2022-06-11T00:00:00.000000000&#x27;, &#x27;2022-06-21T00:00:00.000000000&#x27;,
        &#x27;2022-07-01T00:00:00.000000000&#x27;, &#x27;2022-07-11T00:00:00.000000000&#x27;],
-      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.799</div><input id='attrs-04953dbd-ad2c-4462-b840-b650223b516a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-04953dbd-ad2c-4462-b840-b650223b516a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7af38fd8-0351-45d6-a99d-e7bd68d1c779' class='xr-var-data-in' type='checkbox'><label for='data-7af38fd8-0351-45d6-a99d-e7bd68d1c779' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array(8.79935614)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.3</div><input id='attrs-3a43568d-98b6-4a29-a434-f4f09c7bf113' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a43568d-98b6-4a29-a434-f4f09c7bf113' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9917c38a-1b36-4030-a74b-d7430c59acb3' class='xr-var-data-in' type='checkbox'><label for='data-9917c38a-1b36-4030-a74b-d7430c59acb3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array(46.30039857)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-44229c28-2c6a-4c7d-8ecd-22a944048fca' class='xr-section-summary-in' type='checkbox'  checked><label for='section-44229c28-2c6a-4c7d-8ecd-22a944048fca' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-97d4c30e-6e5b-407c-866f-7addd64496ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-97d4c30e-6e5b-407c-866f-7addd64496ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29d0102e-6a76-4531-84af-9624bf76e5ba' class='xr-var-data-in' type='checkbox'><label for='data-29d0102e-6a76-4531-84af-9624bf76e5ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;, DATUM[&quot;World Geodetic System 1984&quot;, SPHEROID[&quot;WGS 84&quot;, 6378137.0, 298.257223563, AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]], AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]], PRIMEM[&quot;Greenwich&quot;, 0.0, AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]], UNIT[&quot;degree&quot;, 0.017453292519943295], AXIS[&quot;Geodetic longitude&quot;, EAST], AXIS[&quot;Geodetic latitude&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;, DATUM[&quot;World Geodetic System 1984&quot;, SPHEROID[&quot;WGS 84&quot;, 6378137.0, 298.257223563, AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]], AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]], PRIMEM[&quot;Greenwich&quot;, 0.0, AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]], UNIT[&quot;degree&quot;, 0.017453292519943295], AXIS[&quot;Geodetic longitude&quot;, EAST], AXIS[&quot;Geodetic latitude&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=|S1]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NDVI</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>90 122 99 78 ... 231 195 215 234</div><input id='attrs-6c883467-53ba-4ddb-bc93-06817037fa51' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c883467-53ba-4ddb-bc93-06817037fa51' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2593ffad-5889-4a13-9930-943da97d07e6' class='xr-var-data-in' type='checkbox'><label for='data-2593ffad-5889-4a13-9930-943da97d07e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div><div class='xr-var-data'><pre>array([ 90, 122,  99,  78, 108,  81, 106,  94,  97, 104, 137, 129, 120, 170,
-       181, 223, 231, 195, 215, 234], dtype=uint8)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d1d947b2-0191-4bde-9ff6-c97e403bbe23' class='xr-section-summary-in' type='checkbox'  ><label for='section-d1d947b2-0191-4bde-9ff6-c97e403bbe23' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cf97998e-e77c-4384-aab1-d6965bc1fe28' class='xr-index-data-in' type='checkbox'/><label for='index-cf97998e-e77c-4384-aab1-d6965bc1fe28' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.799</div><input id='attrs-283bdf35-3736-43c6-9ce3-090807ac6838' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-283bdf35-3736-43c6-9ce3-090807ac6838' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14b578be-5c1b-4c93-8b49-9f1761346da9' class='xr-var-data-in' type='checkbox'><label for='data-14b578be-5c1b-4c93-8b49-9f1761346da9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array(8.79935614)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.3</div><input id='attrs-d55d1215-cab4-4b39-a8ea-ad26f398893d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d55d1215-cab4-4b39-a8ea-ad26f398893d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38b8e94c-ed71-4ee7-bff2-bfb10a056876' class='xr-var-data-in' type='checkbox'><label for='data-38b8e94c-ed71-4ee7-bff2-bfb10a056876' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array(46.30039857)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fbda3908-48d8-4454-a34f-2bbb88e2598f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fbda3908-48d8-4454-a34f-2bbb88e2598f' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5324c3f9-7eed-4667-8fa2-562125774936' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5324c3f9-7eed-4667-8fa2-562125774936' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9527e95-969a-4b02-bbc6-55e57e69c5e0' class='xr-var-data-in' type='checkbox'><label for='data-e9527e95-969a-4b02-bbc6-55e57e69c5e0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;, DATUM[&quot;World Geodetic System 1984&quot;, SPHEROID[&quot;WGS 84&quot;, 6378137.0, 298.257223563, AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]], AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]], PRIMEM[&quot;Greenwich&quot;, 0.0, AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]], UNIT[&quot;degree&quot;, 0.017453292519943295], AXIS[&quot;Geodetic longitude&quot;, EAST], AXIS[&quot;Geodetic latitude&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;, DATUM[&quot;World Geodetic System 1984&quot;, SPHEROID[&quot;WGS 84&quot;, 6378137.0, 298.257223563, AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]], AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]], PRIMEM[&quot;Greenwich&quot;, 0.0, AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]], UNIT[&quot;degree&quot;, 0.017453292519943295], AXIS[&quot;Geodetic longitude&quot;, EAST], AXIS[&quot;Geodetic latitude&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=|S1]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NDVI</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>90 122 99 78 ... 231 195 215 234</div><input id='attrs-901ba0d6-e1cf-440b-ba63-0d6dabc2da42' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-901ba0d6-e1cf-440b-ba63-0d6dabc2da42' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dddfc42c-a039-4b67-832c-61d8002c2331' class='xr-var-data-in' type='checkbox'><label for='data-dddfc42c-a039-4b67-832c-61d8002c2331' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div><div class='xr-var-data'><pre>array([ 90, 122,  99,  78, 108,  81, 106,  94,  97, 104, 137, 129, 120, 170,
+       181, 223, 231, 195, 215, 234], dtype=uint8)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-712734a9-e88c-41b1-bade-c58567c87470' class='xr-section-summary-in' type='checkbox'  ><label for='section-712734a9-e88c-41b1-bade-c58567c87470' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b6c7157f-12c1-4b1a-8bf6-56b9dcbac944' class='xr-index-data-in' type='checkbox'/><label for='index-b6c7157f-12c1-4b1a-8bf6-56b9dcbac944' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
                &#x27;2022-02-11&#x27;, &#x27;2022-02-21&#x27;, &#x27;2022-03-01&#x27;, &#x27;2022-03-11&#x27;,
                &#x27;2022-03-21&#x27;, &#x27;2022-04-01&#x27;, &#x27;2022-04-11&#x27;, &#x27;2022-04-21&#x27;,
                &#x27;2022-05-01&#x27;, &#x27;2022-05-11&#x27;, &#x27;2022-05-21&#x27;, &#x27;2022-06-01&#x27;,
                &#x27;2022-06-11&#x27;, &#x27;2022-06-21&#x27;, &#x27;2022-07-01&#x27;, &#x27;2022-07-11&#x27;],
-              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-76d5ada9-3330-41e4-b487-0c01e9487157' class='xr-section-summary-in' type='checkbox'  checked><label for='section-76d5ada9-3330-41e4-b487-0c01e9487157' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.8</dd><dt><span>institution :</span></dt><dd>openEO platform</dd></dl></div></li></ul></div></div></div></div>
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1c7e03ea-ffe4-4299-84a2-2d1d3886bb54' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1c7e03ea-ffe4-4299-84a2-2d1d3886bb54' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.8</dd><dt><span>institution :</span></dt><dd>openEO platform</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <div class="admonition warning">
 <p class="admonition-title">Warning</p>
@@ -5328,7 +5328,7 @@ <h2>Selection methods<a class="headerlink" href="#selection-methods" title="Perm
     NDVI     (time) uint8 87 118 71 103 37 79 91 ... 182 206 228 239 181 221 230
 Attributes:
     Conventions:  CF-1.8
-    institution:  openEO platform</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6ee36605-f663-45f9-a499-b2d60c7724c9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6ee36605-f663-45f9-a499-b2d60c7724c9' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 20</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-56e8ecec-a78b-4c9a-b328-730ad3ed39b6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-56e8ecec-a78b-4c9a-b328-730ad3ed39b6' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-06d4e486-4dec-4f8c-8b23-dfc6a72489c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06d4e486-4dec-4f8c-8b23-dfc6a72489c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-952cb18b-8210-4377-ba47-d7e60168da55' class='xr-var-data-in' type='checkbox'><label for='data-952cb18b-8210-4377-ba47-d7e60168da55' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
+    institution:  openEO platform</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6c5c92f4-443a-4537-8b19-085e667eb5e5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6c5c92f4-443a-4537-8b19-085e667eb5e5' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 20</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c35ed9f9-dd96-462b-8b1e-44e5985956fc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c35ed9f9-dd96-462b-8b1e-44e5985956fc' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-b113c933-c722-4ece-bdde-8a1b36ca0fff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b113c933-c722-4ece-bdde-8a1b36ca0fff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e11f1a9e-64c9-452f-806a-7f73e3b442b9' class='xr-var-data-in' type='checkbox'><label for='data-e11f1a9e-64c9-452f-806a-7f73e3b442b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
        &#x27;2022-01-21T00:00:00.000000000&#x27;, &#x27;2022-02-01T00:00:00.000000000&#x27;,
        &#x27;2022-02-11T00:00:00.000000000&#x27;, &#x27;2022-02-21T00:00:00.000000000&#x27;,
        &#x27;2022-03-01T00:00:00.000000000&#x27;, &#x27;2022-03-11T00:00:00.000000000&#x27;,
@@ -5338,13 +5338,13 @@ <h2>Selection methods<a class="headerlink" href="#selection-methods" title="Perm
        &#x27;2022-05-21T00:00:00.000000000&#x27;, &#x27;2022-06-01T00:00:00.000000000&#x27;,
        &#x27;2022-06-11T00:00:00.000000000&#x27;, &#x27;2022-06-21T00:00:00.000000000&#x27;,
        &#x27;2022-07-01T00:00:00.000000000&#x27;, &#x27;2022-07-11T00:00:00.000000000&#x27;],
-      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.799</div><input id='attrs-f363c38a-b467-4e59-b852-0363e815af06' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f363c38a-b467-4e59-b852-0363e815af06' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35b98e5f-d97c-4925-8363-308e9d8b3d2f' class='xr-var-data-in' type='checkbox'><label for='data-35b98e5f-d97c-4925-8363-308e9d8b3d2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array(8.79935614)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.34</div><input id='attrs-3e07533e-4ff5-46f9-aad3-ab4bcece9186' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e07533e-4ff5-46f9-aad3-ab4bcece9186' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59ee9482-a8c5-4d0c-b089-95186afab006' class='xr-var-data-in' type='checkbox'><label for='data-59ee9482-a8c5-4d0c-b089-95186afab006' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array(46.33611286)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3792d591-d7d5-49d7-8218-e71e84d731c7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3792d591-d7d5-49d7-8218-e71e84d731c7' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a12147bc-01f1-46f1-bcab-fda75578e607' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a12147bc-01f1-46f1-bcab-fda75578e607' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-76080c54-eefa-4738-8d57-60712c25cb79' class='xr-var-data-in' type='checkbox'><label for='data-76080c54-eefa-4738-8d57-60712c25cb79' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;, DATUM[&quot;World Geodetic System 1984&quot;, SPHEROID[&quot;WGS 84&quot;, 6378137.0, 298.257223563, AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]], AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]], PRIMEM[&quot;Greenwich&quot;, 0.0, AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]], UNIT[&quot;degree&quot;, 0.017453292519943295], AXIS[&quot;Geodetic longitude&quot;, EAST], AXIS[&quot;Geodetic latitude&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;, DATUM[&quot;World Geodetic System 1984&quot;, SPHEROID[&quot;WGS 84&quot;, 6378137.0, 298.257223563, AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]], AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]], PRIMEM[&quot;Greenwich&quot;, 0.0, AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]], UNIT[&quot;degree&quot;, 0.017453292519943295], AXIS[&quot;Geodetic longitude&quot;, EAST], AXIS[&quot;Geodetic latitude&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=|S1]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NDVI</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>87 118 71 103 ... 239 181 221 230</div><input id='attrs-bd75cf26-38f6-48ce-a47d-dfbff758781c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd75cf26-38f6-48ce-a47d-dfbff758781c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b3e8967-c06d-497a-9b78-a2668da55373' class='xr-var-data-in' type='checkbox'><label for='data-4b3e8967-c06d-497a-9b78-a2668da55373' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div><div class='xr-var-data'><pre>array([ 87, 118,  71, 103,  37,  79,  91,  72,  84,  98, 118, 142, 132, 182,
-       206, 228, 239, 181, 221, 230], dtype=uint8)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-65662816-dfc1-4a41-8c1d-0198930a70a0' class='xr-section-summary-in' type='checkbox'  ><label for='section-65662816-dfc1-4a41-8c1d-0198930a70a0' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4e518321-c9e0-4468-b9a7-ab219f8a40cc' class='xr-index-data-in' type='checkbox'/><label for='index-4e518321-c9e0-4468-b9a7-ab219f8a40cc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.799</div><input id='attrs-b5e7f536-5c5b-43e8-a86b-e5981a447e79' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b5e7f536-5c5b-43e8-a86b-e5981a447e79' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd6b241e-10f2-46cc-84e6-42400b12a1c8' class='xr-var-data-in' type='checkbox'><label for='data-fd6b241e-10f2-46cc-84e6-42400b12a1c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array(8.79935614)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.34</div><input id='attrs-d2d8d197-9ad7-4b7b-ba22-8cfa81093f3f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2d8d197-9ad7-4b7b-ba22-8cfa81093f3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90fcf6e2-a552-4c9d-b4b0-41e5b2cade0f' class='xr-var-data-in' type='checkbox'><label for='data-90fcf6e2-a552-4c9d-b4b0-41e5b2cade0f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array(46.33611286)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-37094c46-f688-47f6-ad9b-16a240d67e8d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-37094c46-f688-47f6-ad9b-16a240d67e8d' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7d90032f-1bb7-4172-ac35-448bb17cd792' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d90032f-1bb7-4172-ac35-448bb17cd792' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e659949-dfe6-42f5-a4e3-ca2384499477' class='xr-var-data-in' type='checkbox'><label for='data-2e659949-dfe6-42f5-a4e3-ca2384499477' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;, DATUM[&quot;World Geodetic System 1984&quot;, SPHEROID[&quot;WGS 84&quot;, 6378137.0, 298.257223563, AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]], AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]], PRIMEM[&quot;Greenwich&quot;, 0.0, AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]], UNIT[&quot;degree&quot;, 0.017453292519943295], AXIS[&quot;Geodetic longitude&quot;, EAST], AXIS[&quot;Geodetic latitude&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;, DATUM[&quot;World Geodetic System 1984&quot;, SPHEROID[&quot;WGS 84&quot;, 6378137.0, 298.257223563, AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]], AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]], PRIMEM[&quot;Greenwich&quot;, 0.0, AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]], UNIT[&quot;degree&quot;, 0.017453292519943295], AXIS[&quot;Geodetic longitude&quot;, EAST], AXIS[&quot;Geodetic latitude&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=|S1]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NDVI</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>87 118 71 103 ... 239 181 221 230</div><input id='attrs-14511695-0c35-4883-8a4e-ed4713511851' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14511695-0c35-4883-8a4e-ed4713511851' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ede1ba6-6fd5-4639-8ce5-5383bc1e74e2' class='xr-var-data-in' type='checkbox'><label for='data-5ede1ba6-6fd5-4639-8ce5-5383bc1e74e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div><div class='xr-var-data'><pre>array([ 87, 118,  71, 103,  37,  79,  91,  72,  84,  98, 118, 142, 132, 182,
+       206, 228, 239, 181, 221, 230], dtype=uint8)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-39cf0c6d-7ba8-4c81-ba5e-dfa566ba2b6d' class='xr-section-summary-in' type='checkbox'  ><label for='section-39cf0c6d-7ba8-4c81-ba5e-dfa566ba2b6d' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-842ba839-5d91-442b-90ae-2e9d02855df0' class='xr-index-data-in' type='checkbox'/><label for='index-842ba839-5d91-442b-90ae-2e9d02855df0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
                &#x27;2022-02-11&#x27;, &#x27;2022-02-21&#x27;, &#x27;2022-03-01&#x27;, &#x27;2022-03-11&#x27;,
                &#x27;2022-03-21&#x27;, &#x27;2022-04-01&#x27;, &#x27;2022-04-11&#x27;, &#x27;2022-04-21&#x27;,
                &#x27;2022-05-01&#x27;, &#x27;2022-05-11&#x27;, &#x27;2022-05-21&#x27;, &#x27;2022-06-01&#x27;,
                &#x27;2022-06-11&#x27;, &#x27;2022-06-21&#x27;, &#x27;2022-07-01&#x27;, &#x27;2022-07-11&#x27;],
-              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bb4d02da-6bb9-444d-b7cd-5905cb06ba25' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bb4d02da-6bb9-444d-b7cd-5905cb06ba25' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.8</dd><dt><span>institution :</span></dt><dd>openEO platform</dd></dl></div></li></ul></div></div></div></div>
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0f1d53a5-7bd2-4a6d-a869-81fb9912170b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0f1d53a5-7bd2-4a6d-a869-81fb9912170b' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.8</dd><dt><span>institution :</span></dt><dd>openEO platform</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <p>That is why we use a <code class="docutils literal notranslate"><span class="pre">method</span></code>! It makes your life easier to deal with inexact matches.</p>
 <p>As the exercise is focused on an Area Of Interest, this can be obtained through a bounding box defined with slices.</p>
@@ -5752,7 +5752,7 @@ <h2>Selection methods<a class="headerlink" href="#selection-methods" title="Perm
 Attributes:
     long_name:     NDVI
     units:         
-    grid_mapping:  crs</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 20</li><li><span class='xr-has-index'>lat</span>: 612</li><li><span class='xr-has-index'>lon</span>: 984</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-b7b7feb6-6ee3-4e35-adda-7ada18b5c66a' class='xr-array-in' type='checkbox' checked><label for='section-b7b7feb6-6ee3-4e35-adda-7ada18b5c66a' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>255 255 255 255 255 255 255 255 ... 139 125 130 144 172 175 166 255</span></div><div class='xr-array-data'><pre>array([[[255, 255, ..., 255, 255],
+    grid_mapping:  crs</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 20</li><li><span class='xr-has-index'>lat</span>: 612</li><li><span class='xr-has-index'>lon</span>: 984</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e6dcb139-08f3-4af2-9004-fc4c79c3976e' class='xr-array-in' type='checkbox' checked><label for='section-e6dcb139-08f3-4af2-9004-fc4c79c3976e' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>255 255 255 255 255 255 255 255 ... 139 125 130 144 172 175 166 255</span></div><div class='xr-array-data'><pre>array([[[255, 255, ..., 255, 255],
         [255, 255, ..., 255, 255],
         ...,
         [121, 120, ..., 123, 255],
@@ -5776,7 +5776,7 @@ <h2>Selection methods<a class="headerlink" href="#selection-methods" title="Perm
         [198, 200, ..., 208, 255],
         ...,
         [166, 153, ..., 157, 255],
-        [159, 141, ..., 166, 255]]], dtype=uint8)</pre></div></div></li><li class='xr-section-item'><input id='section-ecdfcead-d4bc-420e-9507-b6aaaaeaca1a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ecdfcead-d4bc-420e-9507-b6aaaaeaca1a' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-5004890f-e116-4126-8e89-8d8220b03553' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5004890f-e116-4126-8e89-8d8220b03553' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af5bde1f-eefe-43b5-bce7-c015843e50ef' class='xr-var-data-in' type='checkbox'><label for='data-af5bde1f-eefe-43b5-bce7-c015843e50ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
+        [159, 141, ..., 166, 255]]], dtype=uint8)</pre></div></div></li><li class='xr-section-item'><input id='section-f75834af-04ba-4a20-8d5e-effc5f88ba8f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f75834af-04ba-4a20-8d5e-effc5f88ba8f' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-551d98bc-a163-428c-8b4e-a7de9bba7057' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-551d98bc-a163-428c-8b4e-a7de9bba7057' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d235921e-5bbf-434d-b0f1-4c38ea71e18e' class='xr-var-data-in' type='checkbox'><label for='data-d235921e-5bbf-434d-b0f1-4c38ea71e18e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
        &#x27;2022-01-21T00:00:00.000000000&#x27;, &#x27;2022-02-01T00:00:00.000000000&#x27;,
        &#x27;2022-02-11T00:00:00.000000000&#x27;, &#x27;2022-02-21T00:00:00.000000000&#x27;,
        &#x27;2022-03-01T00:00:00.000000000&#x27;, &#x27;2022-03-11T00:00:00.000000000&#x27;,
@@ -5786,12 +5786,12 @@ <h2>Selection methods<a class="headerlink" href="#selection-methods" title="Perm
        &#x27;2022-05-21T00:00:00.000000000&#x27;, &#x27;2022-06-01T00:00:00.000000000&#x27;,
        &#x27;2022-06-11T00:00:00.000000000&#x27;, &#x27;2022-06-21T00:00:00.000000000&#x27;,
        &#x27;2022-07-01T00:00:00.000000000&#x27;, &#x27;2022-07-11T00:00:00.000000000&#x27;],
-      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-7fe14a5f-1cd3-40bf-86c2-5336cf1fc0cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7fe14a5f-1cd3-40bf-86c2-5336cf1fc0cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-854b6db5-0ae2-4a7a-bc4f-261104ca6f2b' class='xr-var-data-in' type='checkbox'><label for='data-854b6db5-0ae2-4a7a-bc4f-261104ca6f2b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.5 46.5 46.49 ... 44.68 44.68</div><input id='attrs-57279d8e-8648-472a-acec-2700ed6b9cd2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-57279d8e-8648-472a-acec-2700ed6b9cd2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-146c51a8-859a-4d74-835b-1813ef945aa9' class='xr-var-data-in' type='checkbox'><label for='data-146c51a8-859a-4d74-835b-1813ef945aa9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.499803, 46.496827, 46.493851, ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-808440e6-4b3a-4929-843a-c1fc776b8a7a' class='xr-section-summary-in' type='checkbox'  ><label for='section-808440e6-4b3a-4929-843a-c1fc776b8a7a' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-fe67bba0-4ea1-4856-9e12-ada461c9def6' class='xr-index-data-in' type='checkbox'/><label for='index-fe67bba0-4ea1-4856-9e12-ada461c9def6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-f9ea5ce0-8e88-409e-b6fa-08d03244e5c5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f9ea5ce0-8e88-409e-b6fa-08d03244e5c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b4c2d89-ce9b-43ff-bf37-cad1f4f7b93e' class='xr-var-data-in' type='checkbox'><label for='data-6b4c2d89-ce9b-43ff-bf37-cad1f4f7b93e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.5 46.5 46.49 ... 44.68 44.68</div><input id='attrs-af4cadef-dcab-47d5-b7ff-587c915dd12b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af4cadef-dcab-47d5-b7ff-587c915dd12b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57d5ab0d-52c9-45e3-9075-1be21a79dac1' class='xr-var-data-in' type='checkbox'><label for='data-57d5ab0d-52c9-45e3-9075-1be21a79dac1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.499803, 46.496827, 46.493851, ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-279be27a-cecb-4ca2-9148-aa7f5a959c14' class='xr-section-summary-in' type='checkbox'  ><label for='section-279be27a-cecb-4ca2-9148-aa7f5a959c14' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6aad6a1f-be26-4660-a036-a4127a6d3ae2' class='xr-index-data-in' type='checkbox'/><label for='index-6aad6a1f-be26-4660-a036-a4127a6d3ae2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
                &#x27;2022-02-11&#x27;, &#x27;2022-02-21&#x27;, &#x27;2022-03-01&#x27;, &#x27;2022-03-11&#x27;,
                &#x27;2022-03-21&#x27;, &#x27;2022-04-01&#x27;, &#x27;2022-04-11&#x27;, &#x27;2022-04-21&#x27;,
                &#x27;2022-05-01&#x27;, &#x27;2022-05-11&#x27;, &#x27;2022-05-21&#x27;, &#x27;2022-06-01&#x27;,
                &#x27;2022-06-11&#x27;, &#x27;2022-06-21&#x27;, &#x27;2022-07-01&#x27;, &#x27;2022-07-11&#x27;],
-              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a7402a6e-a380-4c73-abec-642d5e7a5add' class='xr-index-data-in' type='checkbox'/><label for='index-a7402a6e-a380-4c73-abec-642d5e7a5add' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-92cbf462-8c55-4d6d-9365-ee5ceaa5ba08' class='xr-index-data-in' type='checkbox'/><label for='index-92cbf462-8c55-4d6d-9365-ee5ceaa5ba08' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
          8.51066566666671,  8.513641857142915,  8.516618047619119,
         8.519594238095323,  8.522570428571527,   8.52554661904773,
         8.528522809523935,
@@ -5800,7 +5800,7 @@ <h2>Selection methods<a class="headerlink" href="#selection-methods" title="Perm
        11.409475190489406,  11.41245138096561, 11.415427571441814,
        11.418403761918018, 11.421379952394222, 11.424356142870426,
         11.42733233334663],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bc27f587-36aa-496c-83b9-d1e58fed18d0' class='xr-index-data-in' type='checkbox'/><label for='index-bc27f587-36aa-496c-83b9-d1e58fed18d0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.49980333333342, 46.49682714285723, 46.49385095238104,
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8171be1c-cf16-4b6b-85c5-9ab37ea72ca4' class='xr-index-data-in' type='checkbox'/><label for='index-8171be1c-cf16-4b6b-85c5-9ab37ea72ca4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.49980333333342, 46.49682714285723, 46.49385095238104,
        46.49087476190485, 46.48789857142866, 46.48492238095247,
        46.48194619047628, 46.47897000000009, 46.47599380952389,
         46.4730176190477,
@@ -5809,7 +5809,7 @@ <h2>Selection methods<a class="headerlink" href="#selection-methods" title="Perm
        44.69920809523846, 44.69623190476227, 44.69325571428608,
        44.69027952380989,  44.6873033333337, 44.68432714285751,
        44.68135095238132],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=612))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a7bdc62b-c9e6-473e-9a58-aeb272d93805' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a7bdc62b-c9e6-473e-9a58-aeb272d93805' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div></li></ul></div></div></div></div>
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=612))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-396db7cc-6e78-4667-941d-6fcdb1b1f725' class='xr-section-summary-in' type='checkbox'  checked><label for='section-396db7cc-6e78-4667-941d-6fcdb1b1f725' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <div class="admonition tip">
 <p class="admonition-title">Tip</p>
@@ -5827,7 +5827,7 @@ <h2>Plotting<a class="headerlink" href="#plotting" title="Permalink to this head
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.QuadMesh at 0x7f526111ee90&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.QuadMesh at 0x7f5c734d0dd0&gt;
 </pre></div>
 </div>
 <img alt="../_images/111da70b9766b9d801a5f8fc587db228a284def8456454c6a0cfb3e23585941b.png" src="../_images/111da70b9766b9d801a5f8fc587db228a284def8456454c6a0cfb3e23585941b.png" />
@@ -6309,7 +6309,7 @@ <h2>NDVI characteristics from the Product User Manual (PUM)<a class="headerlink"
 Coordinates:
   * time     (time) datetime64[ns] 2022-01-01 2022-01-11 ... 2022-07-11
   * lon      (lon) float64 8.502 8.505 8.508 8.511 ... 11.42 11.42 11.42 11.43
-  * lat      (lat) float64 46.5 46.5 46.49 46.49 ... 44.69 44.69 44.68 44.68</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 20</li><li><span class='xr-has-index'>lat</span>: 612</li><li><span class='xr-has-index'>lon</span>: 984</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-42ca1008-6534-4ed3-8172-8575c59d9c23' class='xr-array-in' type='checkbox' checked><label for='section-42ca1008-6534-4ed3-8172-8575c59d9c23' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.94 0.94 0.94 0.94 0.94 0.94 ... 0.44 0.496 0.608 0.62 0.584 0.94</span></div><div class='xr-array-data'><pre>array([[[0.94 , 0.94 , 0.94 , ..., 0.94 , 0.94 , 0.94 ],
+  * lat      (lat) float64 46.5 46.5 46.49 46.49 ... 44.69 44.69 44.68 44.68</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 20</li><li><span class='xr-has-index'>lat</span>: 612</li><li><span class='xr-has-index'>lon</span>: 984</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-0349fdfd-35f8-467b-a18b-b4ccca6da762' class='xr-array-in' type='checkbox' checked><label for='section-0349fdfd-35f8-467b-a18b-b4ccca6da762' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.94 0.94 0.94 0.94 0.94 0.94 ... 0.44 0.496 0.608 0.62 0.584 0.94</span></div><div class='xr-array-data'><pre>array([[[0.94 , 0.94 , 0.94 , ..., 0.94 , 0.94 , 0.94 ],
         [0.94 , 0.94 , 0.94 , ..., 0.94 , 0.94 , 0.94 ],
         [0.94 , 0.94 , 0.94 , ..., 0.94 , 0.94 , 0.94 ],
         ...,
@@ -6349,7 +6349,7 @@ <h2>NDVI characteristics from the Product User Manual (PUM)<a class="headerlink"
         ...,
         [0.58 , 0.568, 0.568, ..., 0.392, 0.4  , 0.94 ],
         [0.584, 0.532, 0.528, ..., 0.548, 0.548, 0.94 ],
-        [0.556, 0.484, 0.488, ..., 0.62 , 0.584, 0.94 ]]])</pre></div></div></li><li class='xr-section-item'><input id='section-78c156b4-0bda-4666-aa2b-1d542e5d5f2c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-78c156b4-0bda-4666-aa2b-1d542e5d5f2c' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-3469a561-b043-4b0e-a19c-04a97c2b7bc6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3469a561-b043-4b0e-a19c-04a97c2b7bc6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aace1386-6260-44be-83d6-376ccad65dca' class='xr-var-data-in' type='checkbox'><label for='data-aace1386-6260-44be-83d6-376ccad65dca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
+        [0.556, 0.484, 0.488, ..., 0.62 , 0.584, 0.94 ]]])</pre></div></div></li><li class='xr-section-item'><input id='section-89e7289e-a379-4c1b-b0b0-a6a169b5de75' class='xr-section-summary-in' type='checkbox'  checked><label for='section-89e7289e-a379-4c1b-b0b0-a6a169b5de75' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-5ec9a31e-05ce-40e0-a6d6-ba11ff05aa33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ec9a31e-05ce-40e0-a6d6-ba11ff05aa33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66d6fa30-5774-499a-bac5-8dce65565ebe' class='xr-var-data-in' type='checkbox'><label for='data-66d6fa30-5774-499a-bac5-8dce65565ebe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
        &#x27;2022-01-21T00:00:00.000000000&#x27;, &#x27;2022-02-01T00:00:00.000000000&#x27;,
        &#x27;2022-02-11T00:00:00.000000000&#x27;, &#x27;2022-02-21T00:00:00.000000000&#x27;,
        &#x27;2022-03-01T00:00:00.000000000&#x27;, &#x27;2022-03-11T00:00:00.000000000&#x27;,
@@ -6359,12 +6359,12 @@ <h2>NDVI characteristics from the Product User Manual (PUM)<a class="headerlink"
        &#x27;2022-05-21T00:00:00.000000000&#x27;, &#x27;2022-06-01T00:00:00.000000000&#x27;,
        &#x27;2022-06-11T00:00:00.000000000&#x27;, &#x27;2022-06-21T00:00:00.000000000&#x27;,
        &#x27;2022-07-01T00:00:00.000000000&#x27;, &#x27;2022-07-11T00:00:00.000000000&#x27;],
-      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-a8c0f35d-cb23-4ac6-8938-5f6faf975e64' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a8c0f35d-cb23-4ac6-8938-5f6faf975e64' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2deedfe9-5124-44cc-9626-6777647dd975' class='xr-var-data-in' type='checkbox'><label for='data-2deedfe9-5124-44cc-9626-6777647dd975' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.5 46.5 46.49 ... 44.68 44.68</div><input id='attrs-fdda42ac-1892-46fc-9eee-23a1557f915f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fdda42ac-1892-46fc-9eee-23a1557f915f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-288d86ac-7089-4941-850f-bc581dc34d2b' class='xr-var-data-in' type='checkbox'><label for='data-288d86ac-7089-4941-850f-bc581dc34d2b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.499803, 46.496827, 46.493851, ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dab35d08-01c7-4864-93cc-161817930f15' class='xr-section-summary-in' type='checkbox'  ><label for='section-dab35d08-01c7-4864-93cc-161817930f15' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-26b409b6-58dd-46b1-ae14-647b6dc3179f' class='xr-index-data-in' type='checkbox'/><label for='index-26b409b6-58dd-46b1-ae14-647b6dc3179f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-ef579056-9df7-4e57-bfcd-959347b05dad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ef579056-9df7-4e57-bfcd-959347b05dad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2509b4a-8188-44ee-861a-9de321656b2b' class='xr-var-data-in' type='checkbox'><label for='data-f2509b4a-8188-44ee-861a-9de321656b2b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.5 46.5 46.49 ... 44.68 44.68</div><input id='attrs-f7205a3c-e90a-4d60-9fce-436d645a4f59' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7205a3c-e90a-4d60-9fce-436d645a4f59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f45db244-0e70-4768-82a6-739a05144d03' class='xr-var-data-in' type='checkbox'><label for='data-f45db244-0e70-4768-82a6-739a05144d03' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.499803, 46.496827, 46.493851, ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-79c789af-6652-48e2-a154-5c385346796c' class='xr-section-summary-in' type='checkbox'  ><label for='section-79c789af-6652-48e2-a154-5c385346796c' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f8483026-a744-4fc7-a9d9-68256d257b5e' class='xr-index-data-in' type='checkbox'/><label for='index-f8483026-a744-4fc7-a9d9-68256d257b5e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
                &#x27;2022-02-11&#x27;, &#x27;2022-02-21&#x27;, &#x27;2022-03-01&#x27;, &#x27;2022-03-11&#x27;,
                &#x27;2022-03-21&#x27;, &#x27;2022-04-01&#x27;, &#x27;2022-04-11&#x27;, &#x27;2022-04-21&#x27;,
                &#x27;2022-05-01&#x27;, &#x27;2022-05-11&#x27;, &#x27;2022-05-21&#x27;, &#x27;2022-06-01&#x27;,
                &#x27;2022-06-11&#x27;, &#x27;2022-06-21&#x27;, &#x27;2022-07-01&#x27;, &#x27;2022-07-11&#x27;],
-              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c56d49f8-267a-4a74-a1d7-ba866c718ed9' class='xr-index-data-in' type='checkbox'/><label for='index-c56d49f8-267a-4a74-a1d7-ba866c718ed9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7b7263e8-9e97-4532-8658-ae71c2b1bb37' class='xr-index-data-in' type='checkbox'/><label for='index-7b7263e8-9e97-4532-8658-ae71c2b1bb37' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
          8.51066566666671,  8.513641857142915,  8.516618047619119,
         8.519594238095323,  8.522570428571527,   8.52554661904773,
         8.528522809523935,
@@ -6373,7 +6373,7 @@ <h2>NDVI characteristics from the Product User Manual (PUM)<a class="headerlink"
        11.409475190489406,  11.41245138096561, 11.415427571441814,
        11.418403761918018, 11.421379952394222, 11.424356142870426,
         11.42733233334663],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ab3080dd-2dec-40ac-b01a-26451ae20bf9' class='xr-index-data-in' type='checkbox'/><label for='index-ab3080dd-2dec-40ac-b01a-26451ae20bf9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.49980333333342, 46.49682714285723, 46.49385095238104,
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7c432125-93e1-4e3e-aca6-5895f881b265' class='xr-index-data-in' type='checkbox'/><label for='index-7c432125-93e1-4e3e-aca6-5895f881b265' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.49980333333342, 46.49682714285723, 46.49385095238104,
        46.49087476190485, 46.48789857142866, 46.48492238095247,
        46.48194619047628, 46.47897000000009, 46.47599380952389,
         46.4730176190477,
@@ -6382,7 +6382,7 @@ <h2>NDVI characteristics from the Product User Manual (PUM)<a class="headerlink"
        44.69920809523846, 44.69623190476227, 44.69325571428608,
        44.69027952380989,  44.6873033333337, 44.68432714285751,
        44.68135095238132],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=612))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2a34e99c-deb9-436f-958b-16cbc8319589' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2a34e99c-deb9-436f-958b-16cbc8319589' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=612))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-510ad67d-9083-4918-a262-688c0d0ed5bc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-510ad67d-9083-4918-a262-688c0d0ed5bc' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
 </div>
 <p>The universal function (ufunc) from numpy and scipy can be applied too directly to the data.</p>
 <div class="cell docutils container">
@@ -6804,7 +6804,7 @@ <h2>NDVI characteristics from the Product User Manual (PUM)<a class="headerlink"
 Attributes:
     long_name:     NDVI
     units:         
-    grid_mapping:  crs</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 20</li><li><span class='xr-has-index'>lat</span>: 612</li><li><span class='xr-has-index'>lon</span>: 984</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e4cdb883-5ddc-4385-ba73-d8bfdc7e6973' class='xr-array-in' type='checkbox' checked><label for='section-e4cdb883-5ddc-4385-ba73-d8bfdc7e6973' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.94 0.94 0.94 0.94 0.94 0.94 ... 0.44 0.496 0.608 0.62 0.584 0.94</span></div><div class='xr-array-data'><pre>array([[[0.94 , 0.94 , 0.94 , ..., 0.94 , 0.94 , 0.94 ],
+    grid_mapping:  crs</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 20</li><li><span class='xr-has-index'>lat</span>: 612</li><li><span class='xr-has-index'>lon</span>: 984</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-64bcc46f-21b6-4535-8ec0-0a1f5e6bce3f' class='xr-array-in' type='checkbox' checked><label for='section-64bcc46f-21b6-4535-8ec0-0a1f5e6bce3f' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.94 0.94 0.94 0.94 0.94 0.94 ... 0.44 0.496 0.608 0.62 0.584 0.94</span></div><div class='xr-array-data'><pre>array([[[0.94 , 0.94 , 0.94 , ..., 0.94 , 0.94 , 0.94 ],
         [0.94 , 0.94 , 0.94 , ..., 0.94 , 0.94 , 0.94 ],
         [0.94 , 0.94 , 0.94 , ..., 0.94 , 0.94 , 0.94 ],
         ...,
@@ -6844,7 +6844,7 @@ <h2>NDVI characteristics from the Product User Manual (PUM)<a class="headerlink"
         ...,
         [0.58 , 0.568, 0.568, ..., 0.392, 0.4  , 0.94 ],
         [0.584, 0.532, 0.528, ..., 0.548, 0.548, 0.94 ],
-        [0.556, 0.484, 0.488, ..., 0.62 , 0.584, 0.94 ]]])</pre></div></div></li><li class='xr-section-item'><input id='section-7e70d2b0-979b-404e-bbd0-f0ff210b200f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7e70d2b0-979b-404e-bbd0-f0ff210b200f' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-20153de7-8e5f-42e7-86ef-87e40f915aa8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-20153de7-8e5f-42e7-86ef-87e40f915aa8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1cb5b442-2605-4141-864f-5a3a48a5ccf4' class='xr-var-data-in' type='checkbox'><label for='data-1cb5b442-2605-4141-864f-5a3a48a5ccf4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
+        [0.556, 0.484, 0.488, ..., 0.62 , 0.584, 0.94 ]]])</pre></div></div></li><li class='xr-section-item'><input id='section-c133d147-3d76-4ce9-a26f-9f79f1ef6012' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c133d147-3d76-4ce9-a26f-9f79f1ef6012' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-0a7313f7-b30f-4bb1-b591-9b2701bf92eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a7313f7-b30f-4bb1-b591-9b2701bf92eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce8ecf93-01c2-4436-b5c9-4fd7073c9850' class='xr-var-data-in' type='checkbox'><label for='data-ce8ecf93-01c2-4436-b5c9-4fd7073c9850' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
        &#x27;2022-01-21T00:00:00.000000000&#x27;, &#x27;2022-02-01T00:00:00.000000000&#x27;,
        &#x27;2022-02-11T00:00:00.000000000&#x27;, &#x27;2022-02-21T00:00:00.000000000&#x27;,
        &#x27;2022-03-01T00:00:00.000000000&#x27;, &#x27;2022-03-11T00:00:00.000000000&#x27;,
@@ -6854,12 +6854,12 @@ <h2>NDVI characteristics from the Product User Manual (PUM)<a class="headerlink"
        &#x27;2022-05-21T00:00:00.000000000&#x27;, &#x27;2022-06-01T00:00:00.000000000&#x27;,
        &#x27;2022-06-11T00:00:00.000000000&#x27;, &#x27;2022-06-21T00:00:00.000000000&#x27;,
        &#x27;2022-07-01T00:00:00.000000000&#x27;, &#x27;2022-07-11T00:00:00.000000000&#x27;],
-      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-f7f193c8-a259-4086-a21c-38b1b8da8bcf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7f193c8-a259-4086-a21c-38b1b8da8bcf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a1b2b4a-4a4a-479a-b578-1649efffa323' class='xr-var-data-in' type='checkbox'><label for='data-3a1b2b4a-4a4a-479a-b578-1649efffa323' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.5 46.5 46.49 ... 44.68 44.68</div><input id='attrs-4795f216-84ae-4d29-85aa-a15f8da1b9c5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4795f216-84ae-4d29-85aa-a15f8da1b9c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67150f89-9ed7-4539-a1df-39904265f9b8' class='xr-var-data-in' type='checkbox'><label for='data-67150f89-9ed7-4539-a1df-39904265f9b8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.499803, 46.496827, 46.493851, ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-084adec7-5326-4778-8bec-a59bbd990248' class='xr-section-summary-in' type='checkbox'  ><label for='section-084adec7-5326-4778-8bec-a59bbd990248' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c207832f-b278-4d60-9b03-867e57b4f2b3' class='xr-index-data-in' type='checkbox'/><label for='index-c207832f-b278-4d60-9b03-867e57b4f2b3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-25d2ae42-1185-474f-befd-5683f338be07' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25d2ae42-1185-474f-befd-5683f338be07' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3504f829-cbaf-429e-9bfb-8501f3f159f7' class='xr-var-data-in' type='checkbox'><label for='data-3504f829-cbaf-429e-9bfb-8501f3f159f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.5 46.5 46.49 ... 44.68 44.68</div><input id='attrs-dbaa3296-e146-4ccc-a531-3cab8cd7c25c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dbaa3296-e146-4ccc-a531-3cab8cd7c25c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4666b49-126a-4aa3-98ca-520d11725889' class='xr-var-data-in' type='checkbox'><label for='data-e4666b49-126a-4aa3-98ca-520d11725889' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.499803, 46.496827, 46.493851, ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a3039374-cf90-48ea-bb6c-0857fd47cef0' class='xr-section-summary-in' type='checkbox'  ><label for='section-a3039374-cf90-48ea-bb6c-0857fd47cef0' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-10a85a3e-d927-4544-a05b-893c247f187a' class='xr-index-data-in' type='checkbox'/><label for='index-10a85a3e-d927-4544-a05b-893c247f187a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
                &#x27;2022-02-11&#x27;, &#x27;2022-02-21&#x27;, &#x27;2022-03-01&#x27;, &#x27;2022-03-11&#x27;,
                &#x27;2022-03-21&#x27;, &#x27;2022-04-01&#x27;, &#x27;2022-04-11&#x27;, &#x27;2022-04-21&#x27;,
                &#x27;2022-05-01&#x27;, &#x27;2022-05-11&#x27;, &#x27;2022-05-21&#x27;, &#x27;2022-06-01&#x27;,
                &#x27;2022-06-11&#x27;, &#x27;2022-06-21&#x27;, &#x27;2022-07-01&#x27;, &#x27;2022-07-11&#x27;],
-              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-12725f8b-a7f0-48f7-9d86-599394170fcf' class='xr-index-data-in' type='checkbox'/><label for='index-12725f8b-a7f0-48f7-9d86-599394170fcf' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-830587de-e971-4f62-86b2-19bfe4cbc02e' class='xr-index-data-in' type='checkbox'/><label for='index-830587de-e971-4f62-86b2-19bfe4cbc02e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
          8.51066566666671,  8.513641857142915,  8.516618047619119,
         8.519594238095323,  8.522570428571527,   8.52554661904773,
         8.528522809523935,
@@ -6868,7 +6868,7 @@ <h2>NDVI characteristics from the Product User Manual (PUM)<a class="headerlink"
        11.409475190489406,  11.41245138096561, 11.415427571441814,
        11.418403761918018, 11.421379952394222, 11.424356142870426,
         11.42733233334663],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8f743211-3c5e-4acb-b9ea-8c45936d4557' class='xr-index-data-in' type='checkbox'/><label for='index-8f743211-3c5e-4acb-b9ea-8c45936d4557' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.49980333333342, 46.49682714285723, 46.49385095238104,
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0331ef1f-e2df-4c5a-988f-7009d739dd8f' class='xr-index-data-in' type='checkbox'/><label for='index-0331ef1f-e2df-4c5a-988f-7009d739dd8f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.49980333333342, 46.49682714285723, 46.49385095238104,
        46.49087476190485, 46.48789857142866, 46.48492238095247,
        46.48194619047628, 46.47897000000009, 46.47599380952389,
         46.4730176190477,
@@ -6877,7 +6877,7 @@ <h2>NDVI characteristics from the Product User Manual (PUM)<a class="headerlink"
        44.69920809523846, 44.69623190476227, 44.69325571428608,
        44.69027952380989,  44.6873033333337, 44.68432714285751,
        44.68135095238132],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=612))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-16014c26-5998-448b-a858-c43822460e4d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-16014c26-5998-448b-a858-c43822460e4d' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div></li></ul></div></div></div></div>
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=612))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b5db43db-17a8-4993-b8f1-7454349571e1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b5db43db-17a8-4993-b8f1-7454349571e1' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NDVI</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
@@ -7301,7 +7301,7 @@ <h2>NDVI characteristics from the Product User Manual (PUM)<a class="headerlink"
 Coordinates:
   * time     (time) datetime64[ns] 2022-01-01 2022-01-11 ... 2022-07-11
   * lon      (lon) float64 8.502 8.505 8.508 8.511 ... 11.42 11.42 11.42 11.43
-  * lat      (lat) float64 46.5 46.5 46.49 46.49 ... 44.69 44.69 44.68 44.68</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 20</li><li><span class='xr-has-index'>lat</span>: 612</li><li><span class='xr-has-index'>lon</span>: 984</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-741093b1-a71a-43f3-90d7-c0711164876d' class='xr-array-in' type='checkbox' checked><label for='section-741093b1-a71a-43f3-90d7-c0711164876d' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.94 0.94 0.94 0.94 0.94 0.94 ... 0.44 0.496 0.608 0.62 0.584 0.94</span></div><div class='xr-array-data'><pre>array([[[0.94 , 0.94 , 0.94 , ..., 0.94 , 0.94 , 0.94 ],
+  * lat      (lat) float64 46.5 46.5 46.49 46.49 ... 44.69 44.69 44.68 44.68</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 20</li><li><span class='xr-has-index'>lat</span>: 612</li><li><span class='xr-has-index'>lon</span>: 984</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-495938a7-0c86-407a-811a-8bafc75137d2' class='xr-array-in' type='checkbox' checked><label for='section-495938a7-0c86-407a-811a-8bafc75137d2' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.94 0.94 0.94 0.94 0.94 0.94 ... 0.44 0.496 0.608 0.62 0.584 0.94</span></div><div class='xr-array-data'><pre>array([[[0.94 , 0.94 , 0.94 , ..., 0.94 , 0.94 , 0.94 ],
         [0.94 , 0.94 , 0.94 , ..., 0.94 , 0.94 , 0.94 ],
         [0.94 , 0.94 , 0.94 , ..., 0.94 , 0.94 , 0.94 ],
         ...,
@@ -7341,7 +7341,7 @@ <h2>NDVI characteristics from the Product User Manual (PUM)<a class="headerlink"
         ...,
         [0.58 , 0.568, 0.568, ..., 0.392, 0.4  , 0.94 ],
         [0.584, 0.532, 0.528, ..., 0.548, 0.548, 0.94 ],
-        [0.556, 0.484, 0.488, ..., 0.62 , 0.584, 0.94 ]]])</pre></div></div></li><li class='xr-section-item'><input id='section-5f4c8cc5-f115-4817-bd61-13d9a1339e75' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5f4c8cc5-f115-4817-bd61-13d9a1339e75' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-114f38e1-2186-43da-8936-61645d57d223' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-114f38e1-2186-43da-8936-61645d57d223' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85ce64f2-e2cc-4575-a4ba-e801825f306e' class='xr-var-data-in' type='checkbox'><label for='data-85ce64f2-e2cc-4575-a4ba-e801825f306e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
+        [0.556, 0.484, 0.488, ..., 0.62 , 0.584, 0.94 ]]])</pre></div></div></li><li class='xr-section-item'><input id='section-bd2b4746-a3c8-4467-aefe-0d3e756a2b5c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bd2b4746-a3c8-4467-aefe-0d3e756a2b5c' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-07-11</div><input id='attrs-71a26c29-41f7-4c5f-a64d-209b7936baff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-71a26c29-41f7-4c5f-a64d-209b7936baff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2093b075-bcb7-4e5a-88c6-4afb1d7700a7' class='xr-var-data-in' type='checkbox'><label for='data-2093b075-bcb7-4e5a-88c6-4afb1d7700a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
        &#x27;2022-01-21T00:00:00.000000000&#x27;, &#x27;2022-02-01T00:00:00.000000000&#x27;,
        &#x27;2022-02-11T00:00:00.000000000&#x27;, &#x27;2022-02-21T00:00:00.000000000&#x27;,
        &#x27;2022-03-01T00:00:00.000000000&#x27;, &#x27;2022-03-11T00:00:00.000000000&#x27;,
@@ -7351,12 +7351,12 @@ <h2>NDVI characteristics from the Product User Manual (PUM)<a class="headerlink"
        &#x27;2022-05-21T00:00:00.000000000&#x27;, &#x27;2022-06-01T00:00:00.000000000&#x27;,
        &#x27;2022-06-11T00:00:00.000000000&#x27;, &#x27;2022-06-21T00:00:00.000000000&#x27;,
        &#x27;2022-07-01T00:00:00.000000000&#x27;, &#x27;2022-07-11T00:00:00.000000000&#x27;],
-      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-2bc35b89-1427-41f5-a1da-10abcfce3b79' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2bc35b89-1427-41f5-a1da-10abcfce3b79' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99d36c46-25f1-40b4-a553-6d9ff14f14d2' class='xr-var-data-in' type='checkbox'><label for='data-99d36c46-25f1-40b4-a553-6d9ff14f14d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.5 46.5 46.49 ... 44.68 44.68</div><input id='attrs-ce01f690-d02d-4130-8e5c-639618743c86' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce01f690-d02d-4130-8e5c-639618743c86' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98973efc-1ee3-4c0c-b3ab-fe1a6822d76a' class='xr-var-data-in' type='checkbox'><label for='data-98973efc-1ee3-4c0c-b3ab-fe1a6822d76a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.499803, 46.496827, 46.493851, ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-04552f0b-6a49-487a-804f-a9b52ca193a6' class='xr-section-summary-in' type='checkbox'  ><label for='section-04552f0b-6a49-487a-804f-a9b52ca193a6' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-84d10933-2b84-4b9e-a9ab-70fef5dc893f' class='xr-index-data-in' type='checkbox'/><label for='index-84d10933-2b84-4b9e-a9ab-70fef5dc893f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-a9590959-746f-4b9e-b572-b39256002fae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a9590959-746f-4b9e-b572-b39256002fae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef900f00-7bca-438a-ad05-3b6cbf613ec4' class='xr-var-data-in' type='checkbox'><label for='data-ef900f00-7bca-438a-ad05-3b6cbf613ec4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.5 46.5 46.49 ... 44.68 44.68</div><input id='attrs-88468583-a314-4b9c-86ed-99cc8aed3895' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88468583-a314-4b9c-86ed-99cc8aed3895' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b33f1bea-e97c-42e5-808d-cb4c59f2f7c1' class='xr-var-data-in' type='checkbox'><label for='data-b33f1bea-e97c-42e5-808d-cb4c59f2f7c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.499803, 46.496827, 46.493851, ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dccce53f-db33-46c9-8317-8e16277a1b0f' class='xr-section-summary-in' type='checkbox'  ><label for='section-dccce53f-db33-46c9-8317-8e16277a1b0f' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d3b7a3a0-3e5b-40e3-b301-88634af43715' class='xr-index-data-in' type='checkbox'/><label for='index-d3b7a3a0-3e5b-40e3-b301-88634af43715' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
                &#x27;2022-02-11&#x27;, &#x27;2022-02-21&#x27;, &#x27;2022-03-01&#x27;, &#x27;2022-03-11&#x27;,
                &#x27;2022-03-21&#x27;, &#x27;2022-04-01&#x27;, &#x27;2022-04-11&#x27;, &#x27;2022-04-21&#x27;,
                &#x27;2022-05-01&#x27;, &#x27;2022-05-11&#x27;, &#x27;2022-05-21&#x27;, &#x27;2022-06-01&#x27;,
                &#x27;2022-06-11&#x27;, &#x27;2022-06-21&#x27;, &#x27;2022-07-01&#x27;, &#x27;2022-07-11&#x27;],
-              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9d809b7e-9f6e-44f5-9fad-1d69a7381eba' class='xr-index-data-in' type='checkbox'/><label for='index-9d809b7e-9f6e-44f5-9fad-1d69a7381eba' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-dc8589d8-acc1-429b-9190-4362a0062030' class='xr-index-data-in' type='checkbox'/><label for='index-dc8589d8-acc1-429b-9190-4362a0062030' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
          8.51066566666671,  8.513641857142915,  8.516618047619119,
         8.519594238095323,  8.522570428571527,   8.52554661904773,
         8.528522809523935,
@@ -7365,7 +7365,7 @@ <h2>NDVI characteristics from the Product User Manual (PUM)<a class="headerlink"
        11.409475190489406,  11.41245138096561, 11.415427571441814,
        11.418403761918018, 11.421379952394222, 11.424356142870426,
         11.42733233334663],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-dca820bc-cc0c-45f9-b640-b1cfa3a90961' class='xr-index-data-in' type='checkbox'/><label for='index-dca820bc-cc0c-45f9-b640-b1cfa3a90961' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.49980333333342, 46.49682714285723, 46.49385095238104,
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4962b0a3-6329-4f44-ba29-6d68f4040065' class='xr-index-data-in' type='checkbox'/><label for='index-4962b0a3-6329-4f44-ba29-6d68f4040065' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.49980333333342, 46.49682714285723, 46.49385095238104,
        46.49087476190485, 46.48789857142866, 46.48492238095247,
        46.48194619047628, 46.47897000000009, 46.47599380952389,
         46.4730176190477,
@@ -7374,7 +7374,7 @@ <h2>NDVI characteristics from the Product User Manual (PUM)<a class="headerlink"
        44.69920809523846, 44.69623190476227, 44.69325571428608,
        44.69027952380989,  44.6873033333337, 44.68432714285751,
        44.68135095238132],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=612))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-800bdad0-ba43-4486-8b3e-d2804b0399b4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-800bdad0-ba43-4486-8b3e-d2804b0399b4' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=612))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-780ebd99-12e4-44cd-86e4-51428821272c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-780ebd99-12e4-44cd-86e4-51428821272c' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
 </div>
 </section>
 <section id="statistics">
@@ -7751,7 +7751,7 @@ <h2>Statistics<a class="headerlink" href="#statistics" title="Permalink to this
   fill: currentColor;
 }
 </style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;NDVI&#x27; ()&gt;
-array(-0.08)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-b0d08104-b872-498a-bdfc-ae8bb016b7b4' class='xr-array-in' type='checkbox' checked><label for='section-b0d08104-b872-498a-bdfc-ae8bb016b7b4' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-0.08</span></div><div class='xr-array-data'><pre>array(-0.08)</pre></div></div></li><li class='xr-section-item'><input id='section-6e4c591b-e6ef-48dd-9ad7-06523a2d99f0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6e4c591b-e6ef-48dd-9ad7-06523a2d99f0' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-4c78aff1-272d-4332-a60c-669782773075' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4c78aff1-272d-4332-a60c-669782773075' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-0489c6e4-a568-4916-96c1-aec0cc6ce1f3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0489c6e4-a568-4916-96c1-aec0cc6ce1f3' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
+array(-0.08)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-097a31b1-f578-4d3e-add2-215c2114fc6d' class='xr-array-in' type='checkbox' checked><label for='section-097a31b1-f578-4d3e-add2-215c2114fc6d' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-0.08</span></div><div class='xr-array-data'><pre>array(-0.08)</pre></div></div></li><li class='xr-section-item'><input id='section-2c9d3127-d085-44ba-a679-2e63dfdbc181' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2c9d3127-d085-44ba-a679-2e63dfdbc181' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-05b750c6-c03c-44aa-9d33-3aaa93d9ada2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-05b750c6-c03c-44aa-9d33-3aaa93d9ada2' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-b04ede0b-6a63-4e48-b7e7-4b4e86078c5e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b04ede0b-6a63-4e48-b7e7-4b4e86078c5e' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
 </div>
 <p>You can make a statistical operation over a dimension. For instance, let’s retrieve the maximum value for each available time.</p>
 <div class="cell docutils container">
@@ -8134,13 +8134,13 @@ <h2>Statistics<a class="headerlink" href="#statistics" title="Permalink to this
        [0.556, 0.528, 0.532, ..., 0.72 , 0.64 , 0.94 ]])
 Coordinates:
   * lon      (lon) float64 8.502 8.505 8.508 8.511 ... 11.42 11.42 11.42 11.43
-  * lat      (lat) float64 46.5 46.5 46.49 46.49 ... 44.69 44.69 44.68 44.68</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 612</li><li><span class='xr-has-index'>lon</span>: 984</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7505f6fe-5a7e-49cf-8426-faa2d3f26769' class='xr-array-in' type='checkbox' checked><label for='section-7505f6fe-5a7e-49cf-8426-faa2d3f26769' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.94 0.94 0.94 0.94 0.94 0.94 0.94 ... 0.692 0.94 0.656 0.72 0.64 0.94</span></div><div class='xr-array-data'><pre>array([[0.94 , 0.94 , 0.94 , ..., 0.94 , 0.94 , 0.94 ],
+  * lat      (lat) float64 46.5 46.5 46.49 46.49 ... 44.69 44.69 44.68 44.68</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 612</li><li><span class='xr-has-index'>lon</span>: 984</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-021b0f42-dc33-4dd6-a199-5590ea83235c' class='xr-array-in' type='checkbox' checked><label for='section-021b0f42-dc33-4dd6-a199-5590ea83235c' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.94 0.94 0.94 0.94 0.94 0.94 0.94 ... 0.692 0.94 0.656 0.72 0.64 0.94</span></div><div class='xr-array-data'><pre>array([[0.94 , 0.94 , 0.94 , ..., 0.94 , 0.94 , 0.94 ],
        [0.94 , 0.94 , 0.94 , ..., 0.94 , 0.94 , 0.94 ],
        [0.94 , 0.94 , 0.94 , ..., 0.94 , 0.94 , 0.94 ],
        ...,
        [0.596, 0.584, 0.604, ..., 0.728, 0.804, 0.94 ],
        [0.584, 0.604, 0.588, ..., 0.708, 0.68 , 0.94 ],
-       [0.556, 0.528, 0.532, ..., 0.72 , 0.64 , 0.94 ]])</pre></div></div></li><li class='xr-section-item'><input id='section-fdb57358-0c80-4964-83c5-466d317cc9d1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fdb57358-0c80-4964-83c5-466d317cc9d1' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-a2b43a12-a864-4a0a-895a-a3e35ac7cbc0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2b43a12-a864-4a0a-895a-a3e35ac7cbc0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04cd6754-3249-454e-9888-6aca669de9d5' class='xr-var-data-in' type='checkbox'><label for='data-04cd6754-3249-454e-9888-6aca669de9d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.5 46.5 46.49 ... 44.68 44.68</div><input id='attrs-8eeab697-92ea-47da-9baf-5f00cc2e2b1b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8eeab697-92ea-47da-9baf-5f00cc2e2b1b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-00807e71-70b2-4ea4-839c-9b98bc2b45dc' class='xr-var-data-in' type='checkbox'><label for='data-00807e71-70b2-4ea4-839c-9b98bc2b45dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.499803, 46.496827, 46.493851, ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3e68aac3-5a7f-4737-8a1d-37aa7d9c1b10' class='xr-section-summary-in' type='checkbox'  ><label for='section-3e68aac3-5a7f-4737-8a1d-37aa7d9c1b10' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4f162a65-3302-4c0c-8f6e-66868bd97d59' class='xr-index-data-in' type='checkbox'/><label for='index-4f162a65-3302-4c0c-8f6e-66868bd97d59' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
+       [0.556, 0.528, 0.532, ..., 0.72 , 0.64 , 0.94 ]])</pre></div></div></li><li class='xr-section-item'><input id='section-1cc5f355-b1c5-4ca1-a88a-8fe2e2f611b0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1cc5f355-b1c5-4ca1-a88a-8fe2e2f611b0' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-e377b442-707f-4bbf-baa1-e18d2b4e49b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e377b442-707f-4bbf-baa1-e18d2b4e49b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8e11e69-3e52-4f97-ba20-b269c5f2a7ef' class='xr-var-data-in' type='checkbox'><label for='data-d8e11e69-3e52-4f97-ba20-b269c5f2a7ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.5 46.5 46.49 ... 44.68 44.68</div><input id='attrs-616ca2a1-517a-4a35-bcd5-3dea911a9176' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-616ca2a1-517a-4a35-bcd5-3dea911a9176' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9425ef4a-9613-452a-b498-abd3d9e09c74' class='xr-var-data-in' type='checkbox'><label for='data-9425ef4a-9613-452a-b498-abd3d9e09c74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.499803, 46.496827, 46.493851, ..., 44.687303, 44.684327, 44.681351])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-45dc2264-ff21-49fd-a39c-43841e631338' class='xr-section-summary-in' type='checkbox'  ><label for='section-45dc2264-ff21-49fd-a39c-43841e631338' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-178e5038-b1bf-4ef1-bea0-39469da52b75' class='xr-index-data-in' type='checkbox'/><label for='index-178e5038-b1bf-4ef1-bea0-39469da52b75' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
          8.51066566666671,  8.513641857142915,  8.516618047619119,
         8.519594238095323,  8.522570428571527,   8.52554661904773,
         8.528522809523935,
@@ -8149,7 +8149,7 @@ <h2>Statistics<a class="headerlink" href="#statistics" title="Permalink to this
        11.409475190489406,  11.41245138096561, 11.415427571441814,
        11.418403761918018, 11.421379952394222, 11.424356142870426,
         11.42733233334663],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2ac58c03-24da-4732-bab6-4bc413fbad63' class='xr-index-data-in' type='checkbox'/><label for='index-2ac58c03-24da-4732-bab6-4bc413fbad63' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.49980333333342, 46.49682714285723, 46.49385095238104,
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3e63710f-ca5c-4a1e-baaa-da62eb5d6a46' class='xr-index-data-in' type='checkbox'/><label for='index-3e63710f-ca5c-4a1e-baaa-da62eb5d6a46' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.49980333333342, 46.49682714285723, 46.49385095238104,
        46.49087476190485, 46.48789857142866, 46.48492238095247,
        46.48194619047628, 46.47897000000009, 46.47599380952389,
         46.4730176190477,
@@ -8158,7 +8158,7 @@ <h2>Statistics<a class="headerlink" href="#statistics" title="Permalink to this
        44.69920809523846, 44.69623190476227, 44.69325571428608,
        44.69027952380989,  44.6873033333337, 44.68432714285751,
        44.68135095238132],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=612))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cc30ec94-7d99-43cd-a4de-32c8fd6c35e1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cc30ec94-7d99-43cd-a4de-32c8fd6c35e1' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=612))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-aa65ecf7-9f1d-48a3-94b6-6481fcbcd20d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-aa65ecf7-9f1d-48a3-94b6-6481fcbcd20d' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
 </div>
 </section>
 <section id="aggregation">
@@ -8586,7 +8586,7 @@ <h2>Aggregation<a class="headerlink" href="#aggregation" title="Permalink to thi
 Coordinates:
   * lon      (lon) float64 8.502 8.505 8.508 8.511 ... 11.42 11.42 11.42 11.43
   * lat      (lat) float64 46.5 46.5 46.49 46.49 ... 44.69 44.69 44.68 44.68
-  * month    (month) int64 1 2 3 4 5 6 7</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>month</span>: 7</li><li><span class='xr-has-index'>lat</span>: 612</li><li><span class='xr-has-index'>lon</span>: 984</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-f36f4a2d-dcc6-41a2-bf0a-b4fe7b8e282c' class='xr-array-in' type='checkbox' checked><label for='section-f36f4a2d-dcc6-41a2-bf0a-b4fe7b8e282c' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.94 0.94 0.94 0.94 0.94 0.94 ... 0.374 0.432 0.536 0.592 0.508 0.94</span></div><div class='xr-array-data'><pre>array([[[0.94      , 0.94      , 0.94      , ..., 0.792     ,
+  * month    (month) int64 1 2 3 4 5 6 7</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>month</span>: 7</li><li><span class='xr-has-index'>lat</span>: 612</li><li><span class='xr-has-index'>lon</span>: 984</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-985b88d4-705d-49f6-a1b3-e21a76e92c25' class='xr-array-in' type='checkbox' checked><label for='section-985b88d4-705d-49f6-a1b3-e21a76e92c25' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.94 0.94 0.94 0.94 0.94 0.94 ... 0.374 0.432 0.536 0.592 0.508 0.94</span></div><div class='xr-array-data'><pre>array([[[0.94      , 0.94      , 0.94      , ..., 0.792     ,
          0.65066667, 0.94      ],
         [0.94      , 0.94      , 0.94      , ..., 0.64266667,
          0.63866667, 0.94      ],
@@ -8626,7 +8626,7 @@ <h2>Aggregation<a class="headerlink" href="#aggregation" title="Permalink to thi
         [0.536     , 0.526     , 0.532     , ..., 0.498     ,
          0.532     , 0.94      ],
         [0.51      , 0.482     , 0.51      , ..., 0.592     ,
-         0.508     , 0.94      ]]])</pre></div></div></li><li class='xr-section-item'><input id='section-9ff9a626-bed5-4095-92e9-4011bdce248d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9ff9a626-bed5-4095-92e9-4011bdce248d' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-d2fd5198-c6da-42f0-af9b-9e584de48463' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2fd5198-c6da-42f0-af9b-9e584de48463' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-000320c4-9443-48df-9fb2-4557fd8182cb' class='xr-var-data-in' type='checkbox'><label for='data-000320c4-9443-48df-9fb2-4557fd8182cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.5 46.5 46.49 ... 44.68 44.68</div><input id='attrs-1d4b83a7-0e6f-4b33-afbe-aada4cf3af3f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1d4b83a7-0e6f-4b33-afbe-aada4cf3af3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26822ea8-43c9-4421-bc09-871cdf5a00e5' class='xr-var-data-in' type='checkbox'><label for='data-26822ea8-43c9-4421-bc09-871cdf5a00e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.499803, 46.496827, 46.493851, ..., 44.687303, 44.684327, 44.681351])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>month</span></div><div class='xr-var-dims'>(month)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7</div><input id='attrs-96f245d2-f875-4f5d-9aab-73931ea8ba00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96f245d2-f875-4f5d-9aab-73931ea8ba00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc33eb77-9b01-46ad-bbe8-ac35d2202711' class='xr-var-data-in' type='checkbox'><label for='data-cc33eb77-9b01-46ad-bbe8-ac35d2202711' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4, 5, 6, 7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fd3791e8-afad-411d-8295-88b898729428' class='xr-section-summary-in' type='checkbox'  ><label for='section-fd3791e8-afad-411d-8295-88b898729428' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a06083ed-f357-4783-b214-90c269494a2f' class='xr-index-data-in' type='checkbox'/><label for='index-a06083ed-f357-4783-b214-90c269494a2f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
+         0.508     , 0.94      ]]])</pre></div></div></li><li class='xr-section-item'><input id='section-bf118904-6a82-4a61-a7a6-7929f63fabc1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bf118904-6a82-4a61-a7a6-7929f63fabc1' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.502 8.505 8.508 ... 11.42 11.43</div><input id='attrs-20daf6e5-31fc-4789-8420-676af2397027' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-20daf6e5-31fc-4789-8420-676af2397027' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7bf3521d-6477-4689-be06-88521cd1a54e' class='xr-var-data-in' type='checkbox'><label for='data-7bf3521d-6477-4689-be06-88521cd1a54e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 8.501737,  8.504713,  8.507689, ..., 11.42138 , 11.424356, 11.427332])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.5 46.5 46.49 ... 44.68 44.68</div><input id='attrs-89fafaaf-a1d2-487b-a91c-f2ec7f3d9de4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89fafaaf-a1d2-487b-a91c-f2ec7f3d9de4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60c67d8e-8ce2-4393-83b9-890986e154db' class='xr-var-data-in' type='checkbox'><label for='data-60c67d8e-8ce2-4393-83b9-890986e154db' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([46.499803, 46.496827, 46.493851, ..., 44.687303, 44.684327, 44.681351])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>month</span></div><div class='xr-var-dims'>(month)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7</div><input id='attrs-76fcda61-82b4-4911-b167-360ae60875f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-76fcda61-82b4-4911-b167-360ae60875f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43df9d10-9b88-4d18-8c2c-991f1dd703f1' class='xr-var-data-in' type='checkbox'><label for='data-43df9d10-9b88-4d18-8c2c-991f1dd703f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4, 5, 6, 7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d6e82df2-4f53-46fa-b116-029d8a064fe7' class='xr-section-summary-in' type='checkbox'  ><label for='section-d6e82df2-4f53-46fa-b116-029d8a064fe7' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-902c38bc-7fce-46bd-8745-1bafdf2129e5' class='xr-index-data-in' type='checkbox'/><label for='index-902c38bc-7fce-46bd-8745-1bafdf2129e5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 8.501737095238099,  8.504713285714303,  8.507689476190507,
          8.51066566666671,  8.513641857142915,  8.516618047619119,
         8.519594238095323,  8.522570428571527,   8.52554661904773,
         8.528522809523935,
@@ -8635,7 +8635,7 @@ <h2>Aggregation<a class="headerlink" href="#aggregation" title="Permalink to thi
        11.409475190489406,  11.41245138096561, 11.415427571441814,
        11.418403761918018, 11.421379952394222, 11.424356142870426,
         11.42733233334663],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1667cc5e-559c-4385-b97f-f43a8ce39910' class='xr-index-data-in' type='checkbox'/><label for='index-1667cc5e-559c-4385-b97f-f43a8ce39910' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.49980333333342, 46.49682714285723, 46.49385095238104,
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=984))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3d6bbbe3-d541-43ff-914d-a3b8d5568ded' class='xr-index-data-in' type='checkbox'/><label for='index-3d6bbbe3-d541-43ff-914d-a3b8d5568ded' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([46.49980333333342, 46.49682714285723, 46.49385095238104,
        46.49087476190485, 46.48789857142866, 46.48492238095247,
        46.48194619047628, 46.47897000000009, 46.47599380952389,
         46.4730176190477,
@@ -8644,7 +8644,7 @@ <h2>Aggregation<a class="headerlink" href="#aggregation" title="Permalink to thi
        44.69920809523846, 44.69623190476227, 44.69325571428608,
        44.69027952380989,  44.6873033333337, 44.68432714285751,
        44.68135095238132],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=612))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>month</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0b9116b0-28e7-41be-a6b4-f2db0321fba5' class='xr-index-data-in' type='checkbox'/><label for='index-0b9116b0-28e7-41be-a6b4-f2db0321fba5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4, 5, 6, 7], dtype=&#x27;int64&#x27;, name=&#x27;month&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ecdbf254-f9c3-496d-bdf8-0b11ed974828' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ecdbf254-f9c3-496d-bdf8-0b11ed974828' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=612))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>month</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d208a29f-ebc8-40bb-bf34-329778a133cc' class='xr-index-data-in' type='checkbox'/><label for='index-d208a29f-ebc8-40bb-bf34-329778a133cc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4, 5, 6, 7], dtype=&#x27;int64&#x27;, name=&#x27;month&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-85f66fda-4c88-420e-9a6c-89ed17a2b6d4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-85f66fda-4c88-420e-9a6c-89ed17a2b6d4' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
 </div>
 <p>As we have data from January to July, the time dimension is now <code class="docutils literal notranslate"><span class="pre">month</span></code> and takes values from <code class="docutils literal notranslate"><span class="pre">1</span></code> to <code class="docutils literal notranslate"><span class="pre">7</span></code>.</p>
 <div class="cell docutils container">
@@ -9024,7 +9024,7 @@ <h2>Aggregation<a class="headerlink" href="#aggregation" title="Permalink to thi
 Attributes:
     standard_name:  t
     long_name:      t
-    axis:           T</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'month'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>month</span>: 7</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-281ed344-bc90-4cd3-b3ad-cd986cf62e92' class='xr-array-in' type='checkbox' checked><label for='section-281ed344-bc90-4cd3-b3ad-cd986cf62e92' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1 2 3 4 5 6 7</span></div><div class='xr-array-data'><pre>array([1, 2, 3, 4, 5, 6, 7])</pre></div></div></li><li class='xr-section-item'><input id='section-3b2ecab3-c848-4dc0-95d1-4d79b85bb19b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3b2ecab3-c848-4dc0-95d1-4d79b85bb19b' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>month</span></div><div class='xr-var-dims'>(month)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7</div><input id='attrs-8fa503f2-401b-4b24-bfa3-b4a9507348ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8fa503f2-401b-4b24-bfa3-b4a9507348ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-248161e3-f082-427b-8094-e079a7841d2a' class='xr-var-data-in' type='checkbox'><label for='data-248161e3-f082-427b-8094-e079a7841d2a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4, 5, 6, 7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9a09f436-e215-47fd-b0eb-3e00ba1460d8' class='xr-section-summary-in' type='checkbox'  ><label for='section-9a09f436-e215-47fd-b0eb-3e00ba1460d8' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>month</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-601f0f6b-8f2c-4d5e-8210-cdd1da0c6494' class='xr-index-data-in' type='checkbox'/><label for='index-601f0f6b-8f2c-4d5e-8210-cdd1da0c6494' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4, 5, 6, 7], dtype=&#x27;int64&#x27;, name=&#x27;month&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a9e6f3b4-f6dc-42e7-850a-16b8d1c404ed' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a9e6f3b4-f6dc-42e7-850a-16b8d1c404ed' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div></li></ul></div></div></div></div>
+    axis:           T</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'month'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>month</span>: 7</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-18b57b46-7881-449e-a2eb-c346b390997a' class='xr-array-in' type='checkbox' checked><label for='section-18b57b46-7881-449e-a2eb-c346b390997a' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1 2 3 4 5 6 7</span></div><div class='xr-array-data'><pre>array([1, 2, 3, 4, 5, 6, 7])</pre></div></div></li><li class='xr-section-item'><input id='section-fbb30d57-1771-44b1-a66f-322ce1e18e41' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fbb30d57-1771-44b1-a66f-322ce1e18e41' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>month</span></div><div class='xr-var-dims'>(month)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7</div><input id='attrs-92d320e5-c9b3-45cd-8301-3dc518bd661b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-92d320e5-c9b3-45cd-8301-3dc518bd661b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6bfd565b-ff31-4cb2-85f5-3aff1135db93' class='xr-var-data-in' type='checkbox'><label for='data-6bfd565b-ff31-4cb2-85f5-3aff1135db93' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4, 5, 6, 7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ca86a32b-8f94-407c-94eb-398a943f40aa' class='xr-section-summary-in' type='checkbox'  ><label for='section-ca86a32b-8f94-407c-94eb-398a943f40aa' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>month</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-673dfe16-8b8d-4046-8eaf-91c95197ff3d' class='xr-index-data-in' type='checkbox'/><label for='index-673dfe16-8b8d-4046-8eaf-91c95197ff3d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4, 5, 6, 7], dtype=&#x27;int64&#x27;, name=&#x27;month&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-980dabee-ccaa-4f99-a039-cdbead245204' class='xr-section-summary-in' type='checkbox'  checked><label for='section-980dabee-ccaa-4f99-a039-cdbead245204' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div></li></ul></div></div></div></div>
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@@ -9045,7 +9045,7 @@ <h2>Mask<a class="headerlink" href="#mask" title="Permalink to this heading">#</
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@@ -9073,7 +9073,7 @@ <h2>Mask<a class="headerlink" href="#mask" title="Permalink to this heading">#</
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diff --git a/part3/chunking_introduction.html b/part3/chunking_introduction.html
index b816f4e..09dea7a 100644
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"_model_name": "EdgeModel", "_view_count": null, "_view_module": "jupyter-cytoscape", "_view_module_version": "^1.3.3", "_view_name": "EdgeView", "classes": " directed ", "data": {"source": "-5447277515809126995", "target": "-8091090132527373915"}, "pannable": true, "removed": false, "selectable": false, "selected": false}}, "47489829a5b142cca5983ed5dc09570f": {"model_name": "EdgeModel", "model_module": "jupyter-cytoscape", "model_module_version": "^1.3.3", "state": {"_model_module": "jupyter-cytoscape", "_model_module_version": "^1.3.3", "_model_name": "EdgeModel", "_view_count": null, "_view_module": "jupyter-cytoscape", "_view_module_version": "^1.3.3", "_view_name": "EdgeView", "classes": " directed ", "data": {"source": "-2998885498921680700", "target": "-5447277515809126995"}, "pannable": true, "removed": false, "selectable": false, "selected": false}}, "dc63f44beece407c853d72cd6a431f8e": {"model_name": "EdgeModel", "model_module": "jupyter-cytoscape", "model_module_version": "^1.3.3", "state": {"_model_module": "jupyter-cytoscape", "_model_module_version": "^1.3.3", "_model_name": "EdgeModel", "_view_count": null, "_view_module": "jupyter-cytoscape", "_view_module_version": "^1.3.3", "_view_name": "EdgeView", "classes": " directed ", "data": {"source": "-6251404420957700037", "target": "-1583449376425375490"}, "pannable": true, "removed": false, "selectable": false, "selected": false}}, "016b9eea695b4ef188ded906cb589354": {"model_name": "EdgeModel", "model_module": "jupyter-cytoscape", "model_module_version": "^1.3.3", "state": {"_model_module": "jupyter-cytoscape", "_model_module_version": "^1.3.3", "_model_name": "EdgeModel", "_view_count": null, "_view_module": "jupyter-cytoscape", "_view_module_version": "^1.3.3", "_view_name": "EdgeView", "classes": " directed ", "data": {"source": "-2998885498921680700", "target": "-6251404420957700037"}, "pannable": true, "removed": false, "selectable": false, "selected": false}}}, "version_major": 2, "version_minor": 0}</script>
-    <script crossorigin="anonymous" integrity="sha256-Ae2Vz/4ePdIu6ZyI/5ZGsYnb+m0JlOmKPjt6XZ9JJkA=" src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.3.4/require.min.js"></script>
-    <script crossorigin="anonymous" data-jupyter-widgets-cdn="https://cdn.jsdelivr.net/npm/" src="https://cdn.jsdelivr.net/npm/@jupyter-widgets/html-manager@1.0.6/dist/embed-amd.js"></script>
     <script>DOCUMENTATION_OPTIONS.pagename = 'part3/chunking_introduction';</script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
@@ -479,21 +476,29 @@ <h2> Contents </h2>
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#packages">Packages</a></li>
 </ul>
 </li>
-<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#global-lts">Global LTS</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#title-here">title here</a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#what-is-a-chunk">What is a <strong>chunk</strong></a></li>
-<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#using-chunks-within-a-single-file">Using chunks within a single file</a></li>
-<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#operations-on-a-chunked-dataset">Operations on a chunked dataset</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#modifying-chunks">Modifying chunks</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#defining-the-chunk-at-the-creatioin-of-xarray">Defining the chunk at the creatioin of Xarray</a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#so-why-chunks">So, why chunks?</a><ul class="nav section-nav flex-column">
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#chunks-and-files">Chunks and files</a></li>
 </ul>
 </li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#zarr-storage-format">Zarr storage format</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#load-data-using-stackstac-with-specific-chunk">Load data using stackstac (with specific chunk)</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#coomputing-snow-index">Coomputing Snow index</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#clip-the-data">Clip the data</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#lets-save-the-intermediate-result-of-a-few-days-in-a-zarr-format">Lets save the intermediate result of a few days in a zarr format</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#before-saving-we-clean-the-chunk-size-clean-attribute-and-save-the-data-in-xarray-dataset-format">Before saving, we clean the chunk size, clean attribute and save the data in Xarray DataSet format</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#load-the-temporaly-data-saved-as-zarr-back-to-xarray">Load the temporaly data saved as zarr back to Xarray</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#group-by-to-a-day-and-plot-the-results">Group by to a day, and plot the results</a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#opening-multiple-netcdf-files-and-kerchunk">Opening multiple NetCDF files and Kerchunk</a><ul class="nav section-nav flex-column">
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#exploiting-native-file-chunks-for-reading-datasets">Exploiting native file chunks for reading datasets</a></li>
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#extract-chunk-information">Extract chunk information</a></li>
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#combine-all-lts-files-into-one-kerchunked-single-ensemble-dataset">Combine all LTS files into one kerchunked single ensemble dataset</a></li>
 </ul>
 </li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#operations-on-a-chunked-dataset">Operations on a chunked dataset</a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#conclusion">Conclusion</a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#packages-citation">Packages citation</a></li>
 </ul>
@@ -571,2685 +576,215 @@ <h3>Packages<a class="headerlink" href="#packages" title="Permalink to this head
 <p>In this episode, Python packages are imported when we start to use them. However, for best software practices, we recommend you to install and import all the necessary libraries at the top of your Jupyter notebook.</p>
 </section>
 </section>
-<section id="global-lts">
-<h2>Global LTS<a class="headerlink" href="#global-lts" title="Permalink to this heading">#</a></h2>
-<p>In the previous episode, we used Long Term statistics time-series for the region of Lombardy e.g. a very small area. Now we would like to use the original dataset that has a global coverage. Let us first open a single file (for January 1999-2019) to understand how much larger the global dataset is.</p>
+<section id="title-here">
+<h2>title here<a class="headerlink" href="#title-here" title="Permalink to this heading">#</a></h2>
+<p>we are …</p>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">fsspec</span>
-<span class="kn">import</span> <span class="nn">s3fs</span>
-<span class="kn">import</span> <span class="nn">xarray</span> <span class="k">as</span> <span class="nn">xr</span>
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">pystac_client</span>
+<span class="kn">import</span> <span class="nn">geopandas</span> <span class="k">as</span> <span class="nn">gpd</span>
+<span class="kn">from</span> <span class="nn">shapely.geometry</span> <span class="kn">import</span> <span class="n">mapping</span>
+<span class="kn">import</span> <span class="nn">stackstac</span>
+<span class="kn">import</span> <span class="nn">warnings</span>
+<span class="n">warnings</span><span class="o">.</span><span class="n">filterwarnings</span><span class="p">(</span><span class="s2">&quot;ignore&quot;</span><span class="p">)</span>
 </pre></div>
 </div>
 </div>
 </div>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">fs</span> <span class="o">=</span> <span class="n">s3fs</span><span class="o">.</span><span class="n">S3FileSystem</span><span class="p">(</span><span class="n">anon</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
-      <span class="n">client_kwargs</span><span class="o">=</span><span class="p">{</span>
-         <span class="s1">&#39;endpoint_url&#39;</span><span class="p">:</span> <span class="s1">&#39;https://object-store.cloud.muni.cz&#39;</span>
-      <span class="p">})</span>
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="o">%%time</span>
+<span class="n">aoi</span> <span class="o">=</span> <span class="n">gpd</span><span class="o">.</span><span class="n">read_file</span><span class="p">(</span><span class="s1">&#39;data/catchment_outline.geojson&#39;</span><span class="p">,</span> <span class="n">crs</span><span class="o">=</span><span class="s2">&quot;EPGS:4326&quot;</span><span class="p">)</span>
+<span class="n">aoi_geojson</span> <span class="o">=</span> <span class="n">mapping</span><span class="p">(</span><span class="n">aoi</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">geometry</span><span class="p">)</span>
+<span class="n">URL</span> <span class="o">=</span> <span class="s2">&quot;https://earth-search.aws.element84.com/v1&quot;</span>
+<span class="n">catalog</span> <span class="o">=</span> <span class="n">pystac_client</span><span class="o">.</span><span class="n">Client</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">URL</span><span class="p">)</span>
+<span class="n">items</span> <span class="o">=</span> <span class="n">catalog</span><span class="o">.</span><span class="n">search</span><span class="p">(</span>
+    <span class="n">intersects</span><span class="o">=</span><span class="n">aoi_geojson</span><span class="p">,</span>
+    <span class="n">collections</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;sentinel-2-l2a&quot;</span><span class="p">],</span>
+    <span class="n">datetime</span><span class="o">=</span><span class="s2">&quot;2019-02-01/2019-06-10&quot;</span>
+<span class="p">)</span><span class="o">.</span><span class="n">item_collection</span><span class="p">()</span>
+<span class="n">sentinel2_l2a</span> <span class="o">=</span> <span class="n">stackstac</span><span class="o">.</span><span class="n">stack</span><span class="p">(</span><span class="n">items</span><span class="p">)</span>
 </pre></div>
 </div>
 </div>
-</div>
-<div class="cell docutils container">
-<div class="cell_input docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">s3path</span> <span class="o">=</span> <span class="s1">&#39;s3://foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1221_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;</span>
+<div class="cell_output docutils container">
+<div class="output traceback highlight-ipythontb notranslate"><div class="highlight"><pre><span></span><span class="gt">---------------------------------------------------------------------------</span>
+<span class="ne">CPLE_OpenFailedError</span><span class="g g-Whitespace">                      </span>Traceback (most recent call last)
+<span class="nn">File fiona/ogrext.pyx:136,</span> in <span class="ni">fiona.ogrext.gdal_open_vector</span><span class="nt">()</span>
+
+<span class="nn">File fiona/_err.pyx:291,</span> in <span class="ni">fiona._err.exc_wrap_pointer</span><span class="nt">()</span>
+
+<span class="ne">CPLE_OpenFailedError</span>: data/catchment_outline.geojson: No such file or directory
+
+<span class="n">During</span> <span class="n">handling</span> <span class="n">of</span> <span class="n">the</span> <span class="n">above</span> <span class="n">exception</span><span class="p">,</span> <span class="n">another</span> <span class="n">exception</span> <span class="n">occurred</span><span class="p">:</span>
+
+<span class="ne">DriverError</span><span class="g g-Whitespace">                               </span>Traceback (most recent call last)
+<span class="n">File</span> <span class="o">&lt;</span><span class="n">timed</span> <span class="n">exec</span><span class="o">&gt;</span><span class="p">:</span><span class="mi">1</span>
+
+<span class="nn">File ~/micromamba/envs/bids23/lib/python3.11/site-packages/geopandas/io/file.py:297,</span> in <span class="ni">_read_file</span><span class="nt">(filename, bbox, mask, rows, engine, **kwargs)</span>
+<span class="g g-Whitespace">    </span><span class="mi">294</span>     <span class="k">else</span><span class="p">:</span>
+<span class="g g-Whitespace">    </span><span class="mi">295</span>         <span class="n">path_or_bytes</span> <span class="o">=</span> <span class="n">filename</span>
+<span class="ne">--&gt; </span><span class="mi">297</span>     <span class="k">return</span> <span class="n">_read_file_fiona</span><span class="p">(</span>
+<span class="g g-Whitespace">    </span><span class="mi">298</span>         <span class="n">path_or_bytes</span><span class="p">,</span> <span class="n">from_bytes</span><span class="p">,</span> <span class="n">bbox</span><span class="o">=</span><span class="n">bbox</span><span class="p">,</span> <span class="n">mask</span><span class="o">=</span><span class="n">mask</span><span class="p">,</span> <span class="n">rows</span><span class="o">=</span><span class="n">rows</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span>
+<span class="g g-Whitespace">    </span><span class="mi">299</span>     <span class="p">)</span>
+<span class="g g-Whitespace">    </span><span class="mi">301</span> <span class="k">else</span><span class="p">:</span>
+<span class="g g-Whitespace">    </span><span class="mi">302</span>     <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;unknown engine &#39;</span><span class="si">{</span><span class="n">engine</span><span class="si">}</span><span class="s2">&#39;&quot;</span><span class="p">)</span>
+
+<span class="nn">File ~/micromamba/envs/bids23/lib/python3.11/site-packages/geopandas/io/file.py:338,</span> in <span class="ni">_read_file_fiona</span><span class="nt">(path_or_bytes, from_bytes, bbox, mask, rows, where, **kwargs)</span>
+<span class="g g-Whitespace">    </span><span class="mi">335</span>     <span class="n">reader</span> <span class="o">=</span> <span class="n">fiona</span><span class="o">.</span><span class="n">open</span>
+<span class="g g-Whitespace">    </span><span class="mi">337</span> <span class="k">with</span> <span class="n">fiona_env</span><span class="p">():</span>
+<span class="ne">--&gt; </span><span class="mi">338</span>     <span class="k">with</span> <span class="n">reader</span><span class="p">(</span><span class="n">path_or_bytes</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="k">as</span> <span class="n">features</span><span class="p">:</span>
+<span class="g g-Whitespace">    </span><span class="mi">339</span>         <span class="n">crs</span> <span class="o">=</span> <span class="n">features</span><span class="o">.</span><span class="n">crs_wkt</span>
+<span class="g g-Whitespace">    </span><span class="mi">340</span>         <span class="c1"># attempt to get EPSG code</span>
+
+<span class="nn">File ~/micromamba/envs/bids23/lib/python3.11/site-packages/fiona/env.py:457,</span> in <span class="ni">ensure_env_with_credentials.&lt;locals&gt;.wrapper</span><span class="nt">(*args, **kwds)</span>
+<span class="g g-Whitespace">    </span><span class="mi">454</span>     <span class="n">session</span> <span class="o">=</span> <span class="n">DummySession</span><span class="p">()</span>
+<span class="g g-Whitespace">    </span><span class="mi">456</span> <span class="k">with</span> <span class="n">env_ctor</span><span class="p">(</span><span class="n">session</span><span class="o">=</span><span class="n">session</span><span class="p">):</span>
+<span class="ne">--&gt; </span><span class="mi">457</span>     <span class="k">return</span> <span class="n">f</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwds</span><span class="p">)</span>
+
+<span class="nn">File ~/micromamba/envs/bids23/lib/python3.11/site-packages/fiona/__init__.py:292,</span> in <span class="ni">open</span><span class="nt">(fp, mode, driver, schema, crs, encoding, layer, vfs, enabled_drivers, crs_wkt, allow_unsupported_drivers, **kwargs)</span>
+<span class="g g-Whitespace">    </span><span class="mi">289</span>     <span class="n">path</span> <span class="o">=</span> <span class="n">parse_path</span><span class="p">(</span><span class="n">fp</span><span class="p">)</span>
+<span class="g g-Whitespace">    </span><span class="mi">291</span> <span class="k">if</span> <span class="n">mode</span> <span class="ow">in</span> <span class="p">(</span><span class="s2">&quot;a&quot;</span><span class="p">,</span> <span class="s2">&quot;r&quot;</span><span class="p">):</span>
+<span class="ne">--&gt; </span><span class="mi">292</span>     <span class="n">colxn</span> <span class="o">=</span> <span class="n">Collection</span><span class="p">(</span>
+<span class="g g-Whitespace">    </span><span class="mi">293</span>         <span class="n">path</span><span class="p">,</span>
+<span class="g g-Whitespace">    </span><span class="mi">294</span>         <span class="n">mode</span><span class="p">,</span>
+<span class="g g-Whitespace">    </span><span class="mi">295</span>         <span class="n">driver</span><span class="o">=</span><span class="n">driver</span><span class="p">,</span>
+<span class="g g-Whitespace">    </span><span class="mi">296</span>         <span class="n">encoding</span><span class="o">=</span><span class="n">encoding</span><span class="p">,</span>
+<span class="g g-Whitespace">    </span><span class="mi">297</span>         <span class="n">layer</span><span class="o">=</span><span class="n">layer</span><span class="p">,</span>
+<span class="g g-Whitespace">    </span><span class="mi">298</span>         <span class="n">enabled_drivers</span><span class="o">=</span><span class="n">enabled_drivers</span><span class="p">,</span>
+<span class="g g-Whitespace">    </span><span class="mi">299</span>         <span class="n">allow_unsupported_drivers</span><span class="o">=</span><span class="n">allow_unsupported_drivers</span><span class="p">,</span>
+<span class="g g-Whitespace">    </span><span class="mi">300</span>         <span class="o">**</span><span class="n">kwargs</span>
+<span class="g g-Whitespace">    </span><span class="mi">301</span>     <span class="p">)</span>
+<span class="g g-Whitespace">    </span><span class="mi">302</span> <span class="k">elif</span> <span class="n">mode</span> <span class="o">==</span> <span class="s2">&quot;w&quot;</span><span class="p">:</span>
+<span class="g g-Whitespace">    </span><span class="mi">303</span>     <span class="n">colxn</span> <span class="o">=</span> <span class="n">Collection</span><span class="p">(</span>
+<span class="g g-Whitespace">    </span><span class="mi">304</span>         <span class="n">path</span><span class="p">,</span>
+<span class="g g-Whitespace">    </span><span class="mi">305</span>         <span class="n">mode</span><span class="p">,</span>
+   <span class="p">(</span><span class="o">...</span><span class="p">)</span>
+<span class="g g-Whitespace">    </span><span class="mi">314</span>         <span class="o">**</span><span class="n">kwargs</span>
+<span class="g g-Whitespace">    </span><span class="mi">315</span>     <span class="p">)</span>
+
+<span class="nn">File ~/micromamba/envs/bids23/lib/python3.11/site-packages/fiona/collection.py:243,</span> in <span class="ni">Collection.__init__</span><span class="nt">(self, path, mode, driver, schema, crs, encoding, layer, vsi, archive, enabled_drivers, crs_wkt, ignore_fields, ignore_geometry, include_fields, wkt_version, allow_unsupported_drivers, **kwargs)</span>
+<span class="g g-Whitespace">    </span><span class="mi">241</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">mode</span> <span class="o">==</span> <span class="s2">&quot;r&quot;</span><span class="p">:</span>
+<span class="g g-Whitespace">    </span><span class="mi">242</span>     <span class="bp">self</span><span class="o">.</span><span class="n">session</span> <span class="o">=</span> <span class="n">Session</span><span class="p">()</span>
+<span class="ne">--&gt; </span><span class="mi">243</span>     <span class="bp">self</span><span class="o">.</span><span class="n">session</span><span class="o">.</span><span class="n">start</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
+<span class="g g-Whitespace">    </span><span class="mi">244</span> <span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">mode</span> <span class="ow">in</span> <span class="p">(</span><span class="s2">&quot;a&quot;</span><span class="p">,</span> <span class="s2">&quot;w&quot;</span><span class="p">):</span>
+<span class="g g-Whitespace">    </span><span class="mi">245</span>     <span class="bp">self</span><span class="o">.</span><span class="n">session</span> <span class="o">=</span> <span class="n">WritingSession</span><span class="p">()</span>
+
+<span class="nn">File fiona/ogrext.pyx:588,</span> in <span class="ni">fiona.ogrext.Session.start</span><span class="nt">()</span>
+
+<span class="nn">File fiona/ogrext.pyx:143,</span> in <span class="ni">fiona.ogrext.gdal_open_vector</span><span class="nt">()</span>
+
+<span class="ne">DriverError</span>: data/catchment_outline.geojson: No such file or directory
 </pre></div>
 </div>
 </div>
 </div>
-<p>As shown in the <a class="reference internal" href="data_discovery.html"><span class="doc std std-doc">Data discovery</span></a> chapter, when we have several files to read at once, we need to use Xarray <code class="docutils literal notranslate"><span class="pre">open_mfdataset</span></code> instead of <code class="docutils literal notranslate"><span class="pre">open_dataset</span></code>. It takes a list in input, and not a single element. We can also use <code class="docutils literal notranslate"><span class="pre">open_mfdataset</span></code> with one file as done below, just as an introduction.</p>
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+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">sentinel2_l2a</span>
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-Wall time: 2.62 s
+<div class="output traceback highlight-ipythontb notranslate"><div class="highlight"><pre><span></span><span class="gt">---------------------------------------------------------------------------</span>
+<span class="ne">NameError</span><span class="g g-Whitespace">                                 </span>Traceback (most recent call last)
+<span class="n">Cell</span> <span class="n">In</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">line</span> <span class="mi">1</span>
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-Dimensions:  (lon: 40320, lat: 15680)
-Coordinates:
-  * lon      (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0
-  * lat      (lat) float64 80.0 79.99 79.98 79.97 ... -59.97 -59.98 -59.99
-Data variables:
-    crs      |S1 ...
-    min      (lat, lon) float32 dask.array&lt;chunksize=(1207, 3102), meta=np.ndarray&gt;
-    median   (lat, lon) float32 dask.array&lt;chunksize=(1207, 3102), meta=np.ndarray&gt;
-    max      (lat, lon) float32 dask.array&lt;chunksize=(1207, 3102), meta=np.ndarray&gt;
-    mean     (lat, lon) float32 dask.array&lt;chunksize=(1207, 3102), meta=np.ndarray&gt;
-    stdev    (lat, lon) float32 dask.array&lt;chunksize=(1207, 3102), meta=np.ndarray&gt;
-    nobs     (lat, lon) float32 dask.array&lt;chunksize=(1207, 3102), meta=np.ndarray&gt;
-Attributes: (12/19)
-    Conventions:          CF-1.6
-    parent_identifier:    urn:cgls:global:ndvi_stats_all
-    identifier:           urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-1...
-    long_name:            Normalized Difference Vegetation Index
-    title:                Normalized Difference Vegetation Index: Long Term S...
-    product_version:      V3.0.1
-    ...                   ...
-    source:               Derived from EO satellite imagery
-    processing_mode:      Offline
-    references:           https://land.copernicus.eu/global/products/ndvi
-    copyright:            Copernicus Service information 2021
-    archive_facility:     VITO
-    history:              2021-03-01 - Processing line NDVI LTS</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-073bdaf2-5225-4934-b92c-dc8f7ffee6e7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-073bdaf2-5225-4934-b92c-dc8f7ffee6e7' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 40320</li><li><span class='xr-has-index'>lat</span>: 15680</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-fd40b460-4a0a-4a5c-81e0-499214537c2d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fd40b460-4a0a-4a5c-81e0-499214537c2d' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-726c95a0-7459-4c6e-ace0-8aca7bc9badf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-726c95a0-7459-4c6e-ace0-8aca7bc9badf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dda498dd-231a-446d-8581-be8923e43d04' class='xr-var-data-in' type='checkbox'><label for='data-dda498dd-231a-446d-8581-be8923e43d04' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>lon</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-180.      , -179.991071, -179.982143, ...,  179.973214,  179.982143,
-        179.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.99 79.98 ... -59.98 -59.99</div><input id='attrs-dc0fd206-ca68-4dc2-81bb-09215acae284' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc0fd206-ca68-4dc2-81bb-09215acae284' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a206c5ba-00c7-4b12-819d-b949cc72c320' class='xr-var-data-in' type='checkbox'><label for='data-a206c5ba-00c7-4b12-819d-b949cc72c320' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>lat</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 80.      ,  79.991071,  79.982143, ..., -59.973214, -59.982143,
-       -59.991071])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-30b09cb0-0fb1-447e-bc9a-97c66fa91263' class='xr-section-summary-in' type='checkbox'  checked><label for='section-30b09cb0-0fb1-447e-bc9a-97c66fa91263' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b433b8f1-c5bb-4387-ab41-82e1dc7927fb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b433b8f1-c5bb-4387-ab41-82e1dc7927fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1e1655f-5750-4bc0-a29d-6f536f1d93f6' class='xr-var-data-in' type='checkbox'><label for='data-c1e1655f-5750-4bc0-a29d-6f536f1d93f6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>coordinate reference system</dd><dt><span>_CoordinateAxisTypes :</span></dt><dd>GeoX GeoY</dd><dt><span>_CoordinateTransformType :</span></dt><dd>Projection</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9108&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>-180.0000000000 0.0089285714 0.0 80.0000000000 0.0 -0.0089285714</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=|S1]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-fd5501dc-731a-4390-bd78-576a3947f25b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd5501dc-731a-4390-bd78-576a3947f25b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6c2855c-399a-45e1-91f2-9b32cdd9ce3b' class='xr-var-data-in' type='checkbox'><label for='data-c6c2855c-399a-45e1-91f2-9b32cdd9ce3b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>long_name :</span></dt><dd>Minimum Normalized Difference Vegetation Index over time period</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254 255]</dd><dt><span>units :</span></dt><dd></dd><dt><span>valid_range :</span></dt><dd>[  0 250]</dd><dt><span>cell_methods :</span></dt><dd>area: mean time: minimum</dd></dl></div><div class='xr-var-data'><table>
-    <tr>
-        <td>
-            <table style="border-collapse: collapse;">
-                <thead>
-                    <tr>
-                        <td> </td>
-                        <th> Array </th>
-                        <th> Chunk </th>
-                    </tr>
-                </thead>
-                <tbody>
-                    
-                    <tr>
-                        <th> Bytes </th>
-                        <td> 2.36 GiB </td>
-                        <td> 14.28 MiB </td>
-                    </tr>
-                    
-                    <tr>
-                        <th> Shape </th>
-                        <td> (15680, 40320) </td>
-                        <td> (1207, 3102) </td>
-                    </tr>
-                    <tr>
-                        <th> Dask graph </th>
-                        <td colspan="2"> 169 chunks in 2 graph layers </td>
-                    </tr>
-                    <tr>
-                        <th> Data type </th>
-                        <td colspan="2"> float32 numpy.ndarray </td>
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-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>median</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-671d7944-8d10-49de-84c4-ef8c862b1e15' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-671d7944-8d10-49de-84c4-ef8c862b1e15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf70f82f-d180-4749-9a00-def6f945c9f1' class='xr-var-data-in' type='checkbox'><label for='data-bf70f82f-d180-4749-9a00-def6f945c9f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>long_name :</span></dt><dd>Median Normalized Difference Vegetation Index over time period</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254 255]</dd><dt><span>units :</span></dt><dd></dd><dt><span>valid_range :</span></dt><dd>[  0 250]</dd><dt><span>cell_methods :</span></dt><dd>area: mean time: median</dd></dl></div><div class='xr-var-data'><table>
-    <tr>
-        <td>
-            <table style="border-collapse: collapse;">
-                <thead>
-                    <tr>
-                        <td> </td>
-                        <th> Array </th>
-                        <th> Chunk </th>
-                    </tr>
-                </thead>
-                <tbody>
-                    
-                    <tr>
-                        <th> Bytes </th>
-                        <td> 2.36 GiB </td>
-                        <td> 14.28 MiB </td>
-                    </tr>
-                    
-                    <tr>
-                        <th> Shape </th>
-                        <td> (15680, 40320) </td>
-                        <td> (1207, 3102) </td>
-                    </tr>
-                    <tr>
-                        <th> Dask graph </th>
-                        <td colspan="2"> 169 chunks in 2 graph layers </td>
-                    </tr>
-                    <tr>
-                        <th> Data type </th>
-                        <td colspan="2"> float32 numpy.ndarray </td>
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-            <table style="border-collapse: collapse;">
-                <thead>
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-                        <th> Array </th>
-                        <th> Chunk </th>
-                    </tr>
-                </thead>
-                <tbody>
-                    
-                    <tr>
-                        <th> Bytes </th>
-                        <td> 2.36 GiB </td>
-                        <td> 14.28 MiB </td>
-                    </tr>
-                    
-                    <tr>
-                        <th> Shape </th>
-                        <td> (15680, 40320) </td>
-                        <td> (1207, 3102) </td>
-                    </tr>
-                    <tr>
-                        <th> Dask graph </th>
-                        <td colspan="2"> 169 chunks in 2 graph layers </td>
-                    </tr>
-                    <tr>
-                        <th> Data type </th>
-                        <td colspan="2"> float32 numpy.ndarray </td>
-                    </tr>
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-</svg>
-        </td>
-    </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-a40be900-ed20-4af8-9cdb-ed5a8dc8871a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a40be900-ed20-4af8-9cdb-ed5a8dc8871a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-faacff7d-1b49-4d12-9858-d58925cfbfe1' class='xr-var-data-in' type='checkbox'><label for='data-faacff7d-1b49-4d12-9858-d58925cfbfe1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>long_name :</span></dt><dd>Mean Normalized Difference Vegetation Index over time period</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254 255]</dd><dt><span>units :</span></dt><dd></dd><dt><span>valid_range :</span></dt><dd>[  0 250]</dd><dt><span>cell_methods :</span></dt><dd>area: mean time: mean</dd></dl></div><div class='xr-var-data'><table>
-    <tr>
-        <td>
-            <table style="border-collapse: collapse;">
-                <thead>
-                    <tr>
-                        <td> </td>
-                        <th> Array </th>
-                        <th> Chunk </th>
-                    </tr>
-                </thead>
-                <tbody>
-                    
-                    <tr>
-                        <th> Bytes </th>
-                        <td> 2.36 GiB </td>
-                        <td> 14.28 MiB </td>
-                    </tr>
-                    
-                    <tr>
-                        <th> Shape </th>
-                        <td> (15680, 40320) </td>
-                        <td> (1207, 3102) </td>
-                    </tr>
-                    <tr>
-                        <th> Dask graph </th>
-                        <td colspan="2"> 169 chunks in 2 graph layers </td>
-                    </tr>
-                    <tr>
-                        <th> Data type </th>
-                        <td colspan="2"> float32 numpy.ndarray </td>
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-                </tbody>
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-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stdev</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-7b6a584e-0aa4-4f86-8f57-5f7719613b29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b6a584e-0aa4-4f86-8f57-5f7719613b29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-746527ac-ef93-499d-a346-957c5896f1c9' class='xr-var-data-in' type='checkbox'><label for='data-746527ac-ef93-499d-a346-957c5896f1c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>long_name :</span></dt><dd>Standard deviation Normalized Difference Vegetation Index over time period</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254 255]</dd><dt><span>units :</span></dt><dd></dd><dt><span>valid_range :</span></dt><dd>[  0 250]</dd><dt><span>cell_methods :</span></dt><dd>area: mean time: standard_deviation</dd></dl></div><div class='xr-var-data'><table>
-    <tr>
-        <td>
-            <table style="border-collapse: collapse;">
-                <thead>
-                    <tr>
-                        <td> </td>
-                        <th> Array </th>
-                        <th> Chunk </th>
-                    </tr>
-                </thead>
-                <tbody>
-                    
-                    <tr>
-                        <th> Bytes </th>
-                        <td> 2.36 GiB </td>
-                        <td> 14.28 MiB </td>
-                    </tr>
-                    
-                    <tr>
-                        <th> Shape </th>
-                        <td> (15680, 40320) </td>
-                        <td> (1207, 3102) </td>
-                    </tr>
-                    <tr>
-                        <th> Dask graph </th>
-                        <td colspan="2"> 169 chunks in 2 graph layers </td>
-                    </tr>
-                    <tr>
-                        <th> Data type </th>
-                        <td colspan="2"> float32 numpy.ndarray </td>
-                    </tr>
-                </tbody>
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-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nobs</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-41bb02aa-8e15-4125-878b-0d16d3f488c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-41bb02aa-8e15-4125-878b-0d16d3f488c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0f9801c-80a3-411d-addf-f843999e5d05' class='xr-var-data-in' type='checkbox'><label for='data-b0f9801c-80a3-411d-addf-f843999e5d05' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index number_of_observations</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>units :</span></dt><dd></dd><dt><span>valid_range :</span></dt><dd>[  1 250]</dd><dt><span>cell_methods :</span></dt><dd>area: mean</dd></dl></div><div class='xr-var-data'><table>
-    <tr>
-        <td>
-            <table style="border-collapse: collapse;">
-                <thead>
-                    <tr>
-                        <td> </td>
-                        <th> Array </th>
-                        <th> Chunk </th>
-                    </tr>
-                </thead>
-                <tbody>
-                    
-                    <tr>
-                        <th> Bytes </th>
-                        <td> 2.36 GiB </td>
-                        <td> 14.28 MiB </td>
-                    </tr>
-                    
-                    <tr>
-                        <th> Shape </th>
-                        <td> (15680, 40320) </td>
-                        <td> (1207, 3102) </td>
-                    </tr>
-                    <tr>
-                        <th> Dask graph </th>
-                        <td colspan="2"> 169 chunks in 2 graph layers </td>
-                    </tr>
-                    <tr>
-                        <th> Data type </th>
-                        <td colspan="2"> float32 numpy.ndarray </td>
-                    </tr>
-                </tbody>
-            </table>
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-        <td>
-        <svg width="170" height="96" style="stroke:rgb(0,0,0);stroke-width:1" >
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-</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-25fabb2d-6f78-4d63-aff6-b7d7b67596e5' class='xr-section-summary-in' type='checkbox'  ><label for='section-25fabb2d-6f78-4d63-aff6-b7d7b67596e5' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bb2829f2-1bb9-4ad0-8ddb-dee344a25e4a' class='xr-index-data-in' type='checkbox'/><label for='index-bb2829f2-1bb9-4ad0-8ddb-dee344a25e4a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -180.0, -179.99107142857142, -179.98214285714283,
-       -179.97321428571425, -179.96428571428567, -179.95535714285708,
-        -179.9464285714285, -179.93749999999991, -179.92857142857133,
-       -179.91964285714275,
-       ...
-         179.9107142862053,   179.9196428576339,  179.92857142906246,
-          179.937500000491,  179.94642857191963,  179.95535714334824,
-         179.9642857147768,  179.97321428620535,  179.98214285763396,
-        179.99107142906257],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=40320))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-878e4d76-38a5-491d-b27f-2f1cd802b082' class='xr-index-data-in' type='checkbox'/><label for='index-878e4d76-38a5-491d-b27f-2f1cd802b082' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               80.0,   79.99107142857143,   79.98214285714286,
-         79.97321428571429,   79.96428571428572,   79.95535714285715,
-         79.94642857142858,   79.93750000000001,   79.92857142857144,
-         79.91964285714288,
-       ...
-       -59.910714285682474,  -59.91964285711106,  -59.92857142853961,
-        -59.93749999996817,  -59.94642857139675, -59.955357142825335,
-        -59.96428571425389, -59.973214285682445,  -59.98214285711103,
-        -59.99107142853961],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=15680))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0b030f3a-4eac-43b7-9f0c-22a0fc1f2bfe' class='xr-section-summary-in' type='checkbox'  ><label for='section-0b030f3a-4eac-43b7-9f0c-22a0fc1f2bfe' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>parent_identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all</dd><dt><span>identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-1221_GLOBE_V3.0.1</dd><dt><span>long_name :</span></dt><dd>Normalized Difference Vegetation Index</dd><dt><span>title :</span></dt><dd>Normalized Difference Vegetation Index: Long Term Statistics 1KM: GLOBE 1999-2019 1221</dd><dt><span>product_version :</span></dt><dd>V3.0.1</dd><dt><span>time_coverage_start :</span></dt><dd>1999-01-01T00:00:00Z</dd><dt><span>time_coverage_end :</span></dt><dd>2019-12-31T23:59:59Z</dd><dt><span>platform :</span></dt><dd>SPOT-4, SPOT-5, Proba-V</dd><dt><span>sensor :</span></dt><dd>VEGETATION-1, VEGETATION-2, VEGETATION</dd><dt><span>orbit_type :</span></dt><dd>LEO</dd><dt><span>processing_level :</span></dt><dd>L4</dd><dt><span>institution :</span></dt><dd>VITO NV</dd><dt><span>source :</span></dt><dd>Derived from EO satellite imagery</dd><dt><span>processing_mode :</span></dt><dd>Offline</dd><dt><span>references :</span></dt><dd>https://land.copernicus.eu/global/products/ndvi</dd><dt><span>copyright :</span></dt><dd>Copernicus Service information 2021</dd><dt><span>archive_facility :</span></dt><dd>VITO</dd><dt><span>history :</span></dt><dd>2021-03-01 - Processing line NDVI LTS</dd></dl></div></li></ul></div></div></div></div>
 </div>
-<p>Using <code class="docutils literal notranslate"><span class="pre">open_mfdataset</span></code> automatically switch from Numpy Arrays to Dask Arrays as the data structure used by Xarray.</p>
-<div class="alert alert-warning">
-    <i class="fa-check-circle fa" style="font-size: 22px;color:#666;"></i> <b>Go Further</b>
-    <br>
-    <ul>
-        <li>You can try to open the same file with xr.open_dataset(fs.open(s3path))</li> 
-        <li>Compare the xarray output between open_mfdataset and open_dataset, what do you see as difference?</li>
-            </ul>
-</div></section>
+</div>
+</section>
 <section id="what-is-a-chunk">
 <h2>What is a <strong>chunk</strong><a class="headerlink" href="#what-is-a-chunk" title="Permalink to this heading">#</a></h2>
-<p>If you look carefully to <code class="docutils literal notranslate"><span class="pre">LTS</span></code>, each Data Variable is a <code class="docutils literal notranslate"><span class="pre">dask.array</span></code> with a chunk size of <code class="docutils literal notranslate"><span class="pre">(15680,</span> <span class="pre">40320)</span></code>. So basically accessing one data variable would load arrays of dimensions <code class="docutils literal notranslate"><span class="pre">(15680,</span> <span class="pre">40320)</span></code> into the computer’s RAM. You can see this information and more details by clicking the icon as indicated in the image below.</p>
+<p>If you look carefully to <code class="docutils literal notranslate"><span class="pre">sentinel2_l2a</span></code>,  xarray.DataArray is a <code class="docutils literal notranslate"><span class="pre">dask.array</span></code> with a chunk size of <code class="docutils literal notranslate"><span class="pre">(1,</span> <span class="pre">1,</span> <span class="pre">1024,</span> <span class="pre">1024)</span></code>. The full data would load arrays of dimensions <code class="docutils literal notranslate"><span class="pre">(101,</span> <span class="pre">32,</span> <span class="pre">20982,</span> <span class="pre">10980)</span></code>, 746 592 of the ‘chunk’, in total 5.42 TiB into the computer’s RAM.</p>
+<p>We can see the Dask Array information by clicking the icon as circled blue in the image below.</p>
 <p><img alt="Dask.array" src="../_images/datasize.png" /></p>
-<p>When you open one or several netCDF files with <code class="docutils literal notranslate"><span class="pre">open_mdfataset</span></code>, by default, the chunks correspond to the entire size of the variable data array read from each file. When you need to analyze large files, a computer’s memory may not be sufficient anymore (see in this example, 2.36GiB for one chunk!).</p>
+<p>By clicking Red circled triangle icon, we can have detailed informations on the xarray, such as Coordinates, Indexes and Attributes.</p>
+<p>When you create Xarray object using stackstac, we can easily turns STAC collection into a lazy xarray.DataArray, in chunk form, so then it is backed by dask.</p>
+<p>The size and shape of chunk which we will use defines the parallelisation done by Dask, thus Picking a good chunksize will have significant effects on performance.</p>
 <p>This is where understanding and using chunking correctly comes into play.</p>
 <p><strong>Chunking</strong> is splitting a dataset into small pieces.</p>
-<p>Original dataset is in one piece,<br />
-<img alt="Dask.array" src="../_images/notchunked.png" /></p>
+<p>Original dataset, in one piece,<br />
+<img src="../figures/notchunked.png" width="200" height="100"></p>
 <p>and we split it into several smaller pieces.<br />
-<img alt="Dask.array" src="../_images/chunked.png" /></p>
+<img src="../figures/chunked.png" width="200" height="100"></p>
 <p>We split it into pieces so that we can process our data block by block or <strong>chunk</strong> by <strong>chunk</strong>.</p>
-<p>In our case, for the moment, the dataset is composed of several files, so already several pieces (or just one in the example above), and Xarray just creates one chunk for each variable of each file.</p>
-</section>
-<section id="using-chunks-within-a-single-file">
-<h2>Using chunks within a single file<a class="headerlink" href="#using-chunks-within-a-single-file" title="Permalink to this heading">#</a></h2>
-<p>When we want to read one or several big files, or files containing large arrays (the above 2.36GiB per array is already quite big), we will almost certainly need chunks so that we can process arrays piece by piece.</p>
-<p>This is usually done with Xarray using the <code class="docutils literal notranslate"><span class="pre">chunks</span></code> kwarg when opening a file with <code class="docutils literal notranslate"><span class="pre">xr.open_dataset</span></code> or with <code class="docutils literal notranslate"><span class="pre">xr.open_mfdataset</span></code>.</p>
+<p>In our case, for the moment, we used stackstac without specifying ‘chunk’ explicitly.   The dataset is composed of 8MiB each, each contains, 1 time step, 1 band, 1024 x 1024 on x and y direction.<br />
+<img src="../figures/chunk_original.png" width="200" height="100"></p>
+<p>If we have too small chunk size, we will divide our work flow in too small pieces, which can create too many communications, too many ‘distirbution’ overheads.
+If we have too big chunk size, we may not be able to hold the enough memory and our workflow may die.</p>
+<p>The right size of chunk depends on your computation and the machine you use.</p>
+<p>Here, 8MiB, is very small compare to usual RAM size available. For example, dask’s default array size is 128MiB.</p>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">LTS</span> <span class="o">=</span> <span class="n">xr</span><span class="o">.</span><span class="n">open_dataset</span><span class="p">(</span><span class="n">fs</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">s3path</span><span class="p">),</span> <span class="n">chunks</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;lon&quot;</span><span class="p">:</span> <span class="mi">40320</span> <span class="o">/</span> <span class="mi">2</span><span class="p">,</span> <span class="s2">&quot;lat&quot;</span><span class="p">:</span> <span class="mi">15680</span> <span class="o">/</span> <span class="mi">2</span><span class="p">})</span>
-<span class="n">LTS</span>
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">dask</span>
+<span class="n">dask</span><span class="o">.</span><span class="n">config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;array.chunk-size&#39;</span><span class="p">)</span>
 </pre></div>
 </div>
 </div>
-<div class="cell_output docutils container">
-<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/home/runner/micromamba/envs/bids23/lib/python3.11/site-packages/xarray/core/dataset.py:278: UserWarning: The specified chunks separate the stored chunks along dimension &quot;lat&quot; starting at index 7840. This could degrade performance. Instead, consider rechunking after loading.
-  warnings.warn(
-/home/runner/micromamba/envs/bids23/lib/python3.11/site-packages/xarray/core/dataset.py:278: UserWarning: The specified chunks separate the stored chunks along dimension &quot;lon&quot; starting at index 20160. This could degrade performance. Instead, consider rechunking after loading.
-  warnings.warn(
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-Dimensions:  (lon: 40320, lat: 15680)
-Coordinates:
-  * lon      (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0
-  * lat      (lat) float64 80.0 79.99 79.98 79.97 ... -59.97 -59.98 -59.99
-Data variables:
-    crs      |S1 ...
-    min      (lat, lon) float32 dask.array&lt;chunksize=(7840, 20160), meta=np.ndarray&gt;
-    median   (lat, lon) float32 dask.array&lt;chunksize=(7840, 20160), meta=np.ndarray&gt;
-    max      (lat, lon) float32 dask.array&lt;chunksize=(7840, 20160), meta=np.ndarray&gt;
-    mean     (lat, lon) float32 dask.array&lt;chunksize=(7840, 20160), meta=np.ndarray&gt;
-    stdev    (lat, lon) float32 dask.array&lt;chunksize=(7840, 20160), meta=np.ndarray&gt;
-    nobs     (lat, lon) float32 dask.array&lt;chunksize=(7840, 20160), meta=np.ndarray&gt;
-Attributes: (12/19)
-    Conventions:          CF-1.6
-    parent_identifier:    urn:cgls:global:ndvi_stats_all
-    identifier:           urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-1...
-    long_name:            Normalized Difference Vegetation Index
-    title:                Normalized Difference Vegetation Index: Long Term S...
-    product_version:      V3.0.1
-    ...                   ...
-    source:               Derived from EO satellite imagery
-    processing_mode:      Offline
-    references:           https://land.copernicus.eu/global/products/ndvi
-    copyright:            Copernicus Service information 2021
-    archive_facility:     VITO
-    history:              2021-03-01 - Processing line NDVI LTS</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b87215a7-929b-4604-91d8-8a6fa644273d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b87215a7-929b-4604-91d8-8a6fa644273d' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 40320</li><li><span class='xr-has-index'>lat</span>: 15680</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a64f2359-ff83-4cb4-93d6-2fbaa4bc5513' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a64f2359-ff83-4cb4-93d6-2fbaa4bc5513' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-cc498173-1069-43cf-bd3e-8abc92b7e4a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc498173-1069-43cf-bd3e-8abc92b7e4a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-abf95fd2-e865-40be-8e33-648ebe7e5114' class='xr-var-data-in' type='checkbox'><label for='data-abf95fd2-e865-40be-8e33-648ebe7e5114' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>lon</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-180.      , -179.991071, -179.982143, ...,  179.973214,  179.982143,
-        179.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.99 79.98 ... -59.98 -59.99</div><input id='attrs-d454897e-619c-405d-8b10-92054165a722' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d454897e-619c-405d-8b10-92054165a722' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4cd30d3-a003-43e5-b16f-1b53c28fa0fd' class='xr-var-data-in' type='checkbox'><label for='data-f4cd30d3-a003-43e5-b16f-1b53c28fa0fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>lat</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 80.      ,  79.991071,  79.982143, ..., -59.973214, -59.982143,
-       -59.991071])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-aae1773a-878c-47fb-a953-769b6b03d4a2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-aae1773a-878c-47fb-a953-769b6b03d4a2' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-529cda49-858b-45fa-b791-7b34dc859a20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-529cda49-858b-45fa-b791-7b34dc859a20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f28ef609-2900-4b33-b270-f5ed98e51645' class='xr-var-data-in' type='checkbox'><label for='data-f28ef609-2900-4b33-b270-f5ed98e51645' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>coordinate reference system</dd><dt><span>_CoordinateAxisTypes :</span></dt><dd>GeoX GeoY</dd><dt><span>_CoordinateTransformType :</span></dt><dd>Projection</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9108&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>-180.0000000000 0.0089285714 0.0 80.0000000000 0.0 -0.0089285714</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=|S1]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(7840, 20160), meta=np.ndarray&gt;</div><input id='attrs-88d4e4d0-645e-4274-97eb-bf3baf1b4277' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88d4e4d0-645e-4274-97eb-bf3baf1b4277' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-990e2a42-95bb-442f-aedb-862b351c4445' class='xr-var-data-in' type='checkbox'><label for='data-990e2a42-95bb-442f-aedb-862b351c4445' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>long_name :</span></dt><dd>Minimum Normalized Difference Vegetation Index over time period</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254 255]</dd><dt><span>units :</span></dt><dd></dd><dt><span>valid_range :</span></dt><dd>[  0 250]</dd><dt><span>cell_methods :</span></dt><dd>area: mean time: minimum</dd></dl></div><div class='xr-var-data'><table>
-    <tr>
-        <td>
-            <table style="border-collapse: collapse;">
-                <thead>
-                    <tr>
-                        <td> </td>
-                        <th> Array </th>
-                        <th> Chunk </th>
-                    </tr>
-                </thead>
-                <tbody>
-                    
-                    <tr>
-                        <th> Bytes </th>
-                        <td> 2.36 GiB </td>
-                        <td> 602.93 MiB </td>
-                    </tr>
-                    
-                    <tr>
-                        <th> Shape </th>
-                        <td> (15680, 40320) </td>
-                        <td> (7840, 20160) </td>
-                    </tr>
-                    <tr>
-                        <th> Dask graph </th>
-                        <td colspan="2"> 4 chunks in 2 graph layers </td>
-                    </tr>
-                    <tr>
-                        <th> Data type </th>
-                        <td colspan="2"> float32 numpy.ndarray </td>
-                    </tr>
-                </tbody>
-            </table>
-        </td>
-        <td>
-        <svg width="170" height="96" style="stroke:rgb(0,0,0);stroke-width:1" >
-
-  <!-- Horizontal lines -->
-  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
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-</svg>
-        </td>
-    </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>median</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(7840, 20160), meta=np.ndarray&gt;</div><input id='attrs-6d354874-a4b0-4acc-b838-97a2b18da382' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d354874-a4b0-4acc-b838-97a2b18da382' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bac6edf9-abd4-419c-b04c-d1b0ab4fc241' class='xr-var-data-in' type='checkbox'><label for='data-bac6edf9-abd4-419c-b04c-d1b0ab4fc241' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>long_name :</span></dt><dd>Median Normalized Difference Vegetation Index over time period</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254 255]</dd><dt><span>units :</span></dt><dd></dd><dt><span>valid_range :</span></dt><dd>[  0 250]</dd><dt><span>cell_methods :</span></dt><dd>area: mean time: median</dd></dl></div><div class='xr-var-data'><table>
-    <tr>
-        <td>
-            <table style="border-collapse: collapse;">
-                <thead>
-                    <tr>
-                        <td> </td>
-                        <th> Array </th>
-                        <th> Chunk </th>
-                    </tr>
-                </thead>
-                <tbody>
-                    
-                    <tr>
-                        <th> Bytes </th>
-                        <td> 2.36 GiB </td>
-                        <td> 602.93 MiB </td>
-                    </tr>
-                    
-                    <tr>
-                        <th> Shape </th>
-                        <td> (15680, 40320) </td>
-                        <td> (7840, 20160) </td>
-                    </tr>
-                    <tr>
-                        <th> Dask graph </th>
-                        <td colspan="2"> 4 chunks in 2 graph layers </td>
-                    </tr>
-                    <tr>
-                        <th> Data type </th>
-                        <td colspan="2"> float32 numpy.ndarray </td>
-                    </tr>
-                </tbody>
-            </table>
-        </td>
-        <td>
-        <svg width="170" height="96" style="stroke:rgb(0,0,0);stroke-width:1" >
-
-  <!-- Horizontal lines -->
-  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
-  <line x1="0" y1="23" x2="120" y2="23" />
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-</svg>
-        </td>
-    </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(7840, 20160), meta=np.ndarray&gt;</div><input id='attrs-e7600ee3-b5bf-4cc3-bb45-d8fb4376acb1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7600ee3-b5bf-4cc3-bb45-d8fb4376acb1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59759031-04c7-4f10-91d4-408e80e656a3' class='xr-var-data-in' type='checkbox'><label for='data-59759031-04c7-4f10-91d4-408e80e656a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>long_name :</span></dt><dd>Maximum Normalized Difference Vegetation Index over time period</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254 255]</dd><dt><span>units :</span></dt><dd></dd><dt><span>valid_range :</span></dt><dd>[  0 250]</dd><dt><span>cell_methods :</span></dt><dd>area: mean time: maximum</dd></dl></div><div class='xr-var-data'><table>
-    <tr>
-        <td>
-            <table style="border-collapse: collapse;">
-                <thead>
-                    <tr>
-                        <td> </td>
-                        <th> Array </th>
-                        <th> Chunk </th>
-                    </tr>
-                </thead>
-                <tbody>
-                    
-                    <tr>
-                        <th> Bytes </th>
-                        <td> 2.36 GiB </td>
-                        <td> 602.93 MiB </td>
-                    </tr>
-                    
-                    <tr>
-                        <th> Shape </th>
-                        <td> (15680, 40320) </td>
-                        <td> (7840, 20160) </td>
-                    </tr>
-                    <tr>
-                        <th> Dask graph </th>
-                        <td colspan="2"> 4 chunks in 2 graph layers </td>
-                    </tr>
-                    <tr>
-                        <th> Data type </th>
-                        <td colspan="2"> float32 numpy.ndarray </td>
-                    </tr>
-                </tbody>
-            </table>
-        </td>
-        <td>
-        <svg width="170" height="96" style="stroke:rgb(0,0,0);stroke-width:1" >
-
-  <!-- Horizontal lines -->
-  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
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-    </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(7840, 20160), meta=np.ndarray&gt;</div><input id='attrs-3de91165-31ac-4469-ae8c-420029005c61' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3de91165-31ac-4469-ae8c-420029005c61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d6a7beb-6ff1-47a5-80df-93013cbfd9e9' class='xr-var-data-in' type='checkbox'><label for='data-0d6a7beb-6ff1-47a5-80df-93013cbfd9e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>long_name :</span></dt><dd>Mean Normalized Difference Vegetation Index over time period</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254 255]</dd><dt><span>units :</span></dt><dd></dd><dt><span>valid_range :</span></dt><dd>[  0 250]</dd><dt><span>cell_methods :</span></dt><dd>area: mean time: mean</dd></dl></div><div class='xr-var-data'><table>
-    <tr>
-        <td>
-            <table style="border-collapse: collapse;">
-                <thead>
-                    <tr>
-                        <td> </td>
-                        <th> Array </th>
-                        <th> Chunk </th>
-                    </tr>
-                </thead>
-                <tbody>
-                    
-                    <tr>
-                        <th> Bytes </th>
-                        <td> 2.36 GiB </td>
-                        <td> 602.93 MiB </td>
-                    </tr>
-                    
-                    <tr>
-                        <th> Shape </th>
-                        <td> (15680, 40320) </td>
-                        <td> (7840, 20160) </td>
-                    </tr>
-                    <tr>
-                        <th> Dask graph </th>
-                        <td colspan="2"> 4 chunks in 2 graph layers </td>
-                    </tr>
-                    <tr>
-                        <th> Data type </th>
-                        <td colspan="2"> float32 numpy.ndarray </td>
-                    </tr>
-                </tbody>
-            </table>
-        </td>
-        <td>
-        <svg width="170" height="96" style="stroke:rgb(0,0,0);stroke-width:1" >
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-                        <td> 602.93 MiB </td>
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-                    <tr>
-                        <th> Shape </th>
-                        <td> (15680, 40320) </td>
-                        <td> (7840, 20160) </td>
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-                        <th> Dask graph </th>
-                        <td colspan="2"> 4 chunks in 2 graph layers </td>
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-                    <tr>
-                        <th> Data type </th>
-                        <td colspan="2"> float32 numpy.ndarray </td>
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-                        <td> 2.36 GiB </td>
-                        <td> 602.93 MiB </td>
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-                    
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-                        <th> Shape </th>
-                        <td> (15680, 40320) </td>
-                        <td> (7840, 20160) </td>
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-                        <th> Dask graph </th>
-                        <td colspan="2"> 4 chunks in 2 graph layers </td>
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-                    <tr>
-                        <th> Data type </th>
-                        <td colspan="2"> float32 numpy.ndarray </td>
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-</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-8abcf152-0d15-4629-b329-b8d64d2fa678' class='xr-section-summary-in' type='checkbox'  ><label for='section-8abcf152-0d15-4629-b329-b8d64d2fa678' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3a45913f-4b25-4de3-bd02-313d7506dade' class='xr-index-data-in' type='checkbox'/><label for='index-3a45913f-4b25-4de3-bd02-313d7506dade' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -180.0, -179.99107142857142, -179.98214285714283,
-       -179.97321428571425, -179.96428571428567, -179.95535714285708,
-        -179.9464285714285, -179.93749999999991, -179.92857142857133,
-       -179.91964285714275,
-       ...
-         179.9107142862053,   179.9196428576339,  179.92857142906246,
-          179.937500000491,  179.94642857191963,  179.95535714334824,
-         179.9642857147768,  179.97321428620535,  179.98214285763396,
-        179.99107142906257],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=40320))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3f40743d-cedf-4e58-980b-cd48658d764c' class='xr-index-data-in' type='checkbox'/><label for='index-3f40743d-cedf-4e58-980b-cd48658d764c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               80.0,   79.99107142857143,   79.98214285714286,
-         79.97321428571429,   79.96428571428572,   79.95535714285715,
-         79.94642857142858,   79.93750000000001,   79.92857142857144,
-         79.91964285714288,
-       ...
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-        -59.96428571425389, -59.973214285682445,  -59.98214285711103,
-        -59.99107142853961],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=15680))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-043066b3-3f05-4727-bcb5-0c655582fd12' class='xr-section-summary-in' type='checkbox'  ><label for='section-043066b3-3f05-4727-bcb5-0c655582fd12' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>parent_identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all</dd><dt><span>identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-1221_GLOBE_V3.0.1</dd><dt><span>long_name :</span></dt><dd>Normalized Difference Vegetation Index</dd><dt><span>title :</span></dt><dd>Normalized Difference Vegetation Index: Long Term Statistics 1KM: GLOBE 1999-2019 1221</dd><dt><span>product_version :</span></dt><dd>V3.0.1</dd><dt><span>time_coverage_start :</span></dt><dd>1999-01-01T00:00:00Z</dd><dt><span>time_coverage_end :</span></dt><dd>2019-12-31T23:59:59Z</dd><dt><span>platform :</span></dt><dd>SPOT-4, SPOT-5, Proba-V</dd><dt><span>sensor :</span></dt><dd>VEGETATION-1, VEGETATION-2, VEGETATION</dd><dt><span>orbit_type :</span></dt><dd>LEO</dd><dt><span>processing_level :</span></dt><dd>L4</dd><dt><span>institution :</span></dt><dd>VITO NV</dd><dt><span>source :</span></dt><dd>Derived from EO satellite imagery</dd><dt><span>processing_mode :</span></dt><dd>Offline</dd><dt><span>references :</span></dt><dd>https://land.copernicus.eu/global/products/ndvi</dd><dt><span>copyright :</span></dt><dd>Copernicus Service information 2021</dd><dt><span>archive_facility :</span></dt><dd>VITO</dd><dt><span>history :</span></dt><dd>2021-03-01 - Processing line NDVI LTS</dd></dl></div></li></ul></div></div></div></div>
 </div>
-<p>If you look into details of any variable in the representation above, you’ll see that each array is chunked into 4 pieces, 602.96 MiB each, which is already more manageable in memory.</p>
-<p>Xarray <code class="docutils literal notranslate"><span class="pre">Dataset</span></code> and <code class="docutils literal notranslate"><span class="pre">DataArray</span></code> objects also have a <code class="docutils literal notranslate"><span class="pre">chunk</span></code> function. We can use it to change our dataset chunks size.
-Lets try to ‘chunk’ our data array LTS.nobs using this command.</p>
-<p>As we would like to play with small sized array, we first select a subset of data as you’ve learned in <span class="xref myst">xarray_introduction</span>.</p>
+</section>
+<section id="modifying-chunks">
+<h2>Modifying chunks<a class="headerlink" href="#modifying-chunks" title="Permalink to this heading">#</a></h2>
+<p>Lets try to modify our chunk size.</p>
+<p>To modify chunks on your existing Xarray  <code class="docutils literal notranslate"><span class="pre">DataArray</span></code>  we can use <code class="docutils literal notranslate"><span class="pre">chunk</span></code> function of Xarray.
+We know that we only need 3 bands for computing the snow index example, so we select only ‘green’,’swir16’,’scl’ to simplyfy our example.</p>
+<p>We would like to have each time series separeated in each chunk, then keep all band informnation on one chunk, and let dask to compute x and y coordinate’s chunk size.</p>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">test</span> <span class="o">=</span> <span class="n">LTS</span><span class="o">.</span><span class="n">nobs</span><span class="o">.</span><span class="n">sel</span><span class="p">(</span><span class="n">lat</span><span class="o">=</span><span class="nb">slice</span><span class="p">(</span><span class="mf">80.</span><span class="p">,</span><span class="mf">70.</span><span class="p">),</span> <span class="n">lon</span><span class="o">=</span><span class="nb">slice</span><span class="p">(</span><span class="mf">70.</span><span class="p">,</span><span class="mi">90</span><span class="p">))</span>
-<span class="n">test</span>
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">sentinel2_l2a</span><span class="o">=</span><span class="n">sentinel2_l2a</span><span class="o">.</span><span class="n">sel</span><span class="p">(</span>
+    <span class="n">band</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;green&#39;</span><span class="p">,</span><span class="s1">&#39;swir16&#39;</span><span class="p">,</span><span class="s1">&#39;scl&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">chunk</span><span class="p">(</span>
+    <span class="n">chunks</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;time&#39;</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="s1">&#39;band&#39;</span><span class="p">:</span><span class="mi">3</span><span class="p">,</span> <span class="s1">&#39;x&#39;</span><span class="p">:</span><span class="s1">&#39;auto&#39;</span><span class="p">,</span><span class="s1">&#39;y&#39;</span><span class="p">:</span><span class="s1">&#39;auto&#39;</span><span class="p">})</span>
+<span class="n">sentinel2_l2a</span>
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-</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;nobs&#x27; (lat: 1121, lon: 2240)&gt;
-dask.array&lt;getitem, shape=(1121, 2240), dtype=float32, chunksize=(1121, 2240), chunktype=numpy.ndarray&gt;
-Coordinates:
-  * lon      (lon) float64 70.0 70.01 70.02 70.03 ... 89.96 89.97 89.98 89.99
-  * lat      (lat) float64 80.0 79.99 79.98 79.97 ... 70.03 70.02 70.01 70.0
-Attributes:
-    standard_name:  normalized_difference_vegetation_index number_of_observat...
-    grid_mapping:   crs
-    units:          
-    valid_range:    [  1 250]
-    cell_methods:   area: mean</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'nobs'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 1121</li><li><span class='xr-has-index'>lon</span>: 2240</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7860837e-5d10-4fbb-8184-b956d2139858' class='xr-array-in' type='checkbox' checked><label for='section-7860837e-5d10-4fbb-8184-b956d2139858' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1121, 2240), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>
-    <tr>
-        <td>
-            <table style="border-collapse: collapse;">
-                <thead>
-                    <tr>
-                        <td> </td>
-                        <th> Array </th>
-                        <th> Chunk </th>
-                    </tr>
-                </thead>
-                <tbody>
-                    
-                    <tr>
-                        <th> Bytes </th>
-                        <td> 9.58 MiB </td>
-                        <td> 9.58 MiB </td>
-                    </tr>
-                    
-                    <tr>
-                        <th> Shape </th>
-                        <td> (1121, 2240) </td>
-                        <td> (1121, 2240) </td>
-                    </tr>
-                    <tr>
-                        <th> Dask graph </th>
-                        <td colspan="2"> 1 chunks in 3 graph layers </td>
-                    </tr>
-                    <tr>
-                        <th> Data type </th>
-                        <td colspan="2"> float32 numpy.ndarray </td>
-                    </tr>
-                </tbody>
-            </table>
-        </td>
-        <td>
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-
-  <!-- Horizontal lines -->
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-
-  <!-- Vertical lines -->
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-
-  <!-- Text -->
-  <text x="60.000000" y="80.053571" font-size="1.0rem" font-weight="100" text-anchor="middle" >2240</text>
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-</svg>
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-</table></div></div></li><li class='xr-section-item'><input id='section-01a6b78b-73b9-4f64-873e-2d6f309f7427' class='xr-section-summary-in' type='checkbox'  checked><label for='section-01a6b78b-73b9-4f64-873e-2d6f309f7427' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>70.0 70.01 70.02 ... 89.98 89.99</div><input id='attrs-f24cac6c-57fa-44e5-8657-023816af52b6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f24cac6c-57fa-44e5-8657-023816af52b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2aca9297-7634-4dbe-88e7-e11a171d1ffd' class='xr-var-data-in' type='checkbox'><label for='data-2aca9297-7634-4dbe-88e7-e11a171d1ffd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>lon</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([70.      , 70.008929, 70.017857, ..., 89.973214, 89.982143, 89.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.99 79.98 ... 70.01 70.0</div><input id='attrs-43feb6be-587b-4a0d-984e-dd3084643fd8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-43feb6be-587b-4a0d-984e-dd3084643fd8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e0e5dee-5344-41bb-a0b1-33e02e53d387' class='xr-var-data-in' type='checkbox'><label for='data-5e0e5dee-5344-41bb-a0b1-33e02e53d387' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>lat</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([80.      , 79.991071, 79.982143, ..., 70.017857, 70.008929, 70.      ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f1e98248-b783-465c-b1e2-292976d0f639' class='xr-section-summary-in' type='checkbox'  ><label for='section-f1e98248-b783-465c-b1e2-292976d0f639' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-570c1152-90aa-44d9-8b6c-983f03be052d' class='xr-index-data-in' type='checkbox'/><label for='index-570c1152-90aa-44d9-8b6c-983f03be052d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([70.00000000034106, 70.00892857176964, 70.01785714319823,
-       70.02678571462681,  70.0357142860554, 70.04464285748398,
-       70.05357142891256, 70.06250000034115, 70.07142857176973,
-       70.08035714319831,
-       ...
-       89.91071428608251, 89.91964285751112, 89.92857142893968,
-       89.93750000036823, 89.94642857179684, 89.95535714322546,
-       89.96428571465401, 89.97321428608257, 89.98214285751118,
-       89.99107142893979],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=2240))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b5eb4f53-27f5-48f7-84bb-399ece06caf4' class='xr-index-data-in' type='checkbox'/><label for='index-b5eb4f53-27f5-48f7-84bb-399ece06caf4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             80.0, 79.99107142857143, 79.98214285714286,
-       79.97321428571429, 79.96428571428572, 79.95535714285715,
-       79.94642857142858, 79.93750000000001, 79.92857142857144,
-       79.91964285714288,
-       ...
-        70.0803571428594, 70.07142857143083, 70.06250000000226,
-       70.05357142857369, 70.04464285714512, 70.03571428571655,
-       70.02678571428798, 70.01785714285941, 70.00892857143084,
-       70.00000000000227],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=1121))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9e4bd960-2fa8-494b-935a-d4561fb2d1f1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9e4bd960-2fa8-494b-935a-d4561fb2d1f1' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index number_of_observations</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>units :</span></dt><dd></dd><dt><span>valid_range :</span></dt><dd>[  1 250]</dd><dt><span>cell_methods :</span></dt><dd>area: mean</dd></dl></div></li></ul></div></div></div></div>
 </div>
-<p>The test value has dimensions <code class="docutils literal notranslate"><span class="pre">(1121,</span> <span class="pre">2240)</span></code>.  We will chunk it on 600x600 pieces using the following command.</p>
+<p>If you look into details of any variable in the representation above, you’ll see that each x and y coordinate’s each ‘chunk’ is bigger, and we have much less chunks (6666 chunks) than example before.  Chunk size as 96 MiB,  is already more manageable than 8MiB small chunk.</p>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">test</span><span class="o">=</span><span class="n">test</span><span class="o">.</span><span class="n">chunk</span><span class="p">(</span><span class="mi">600</span><span class="p">)</span>
-<span class="n">test</span>
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">sentinel2_l2a</span><span class="o">.</span><span class="n">chunk</span><span class="p">(</span><span class="n">chunks</span> <span class="o">=</span> <span class="p">(</span> <span class="mi">1</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">12048</span><span class="p">,</span><span class="mi">2048</span><span class="p">))</span>
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-</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;nobs&#x27; (lat: 1121, lon: 2240)&gt;
-dask.array&lt;rechunk-merge, shape=(1121, 2240), dtype=float32, chunksize=(600, 600), chunktype=numpy.ndarray&gt;
-Coordinates:
-  * lon      (lon) float64 70.0 70.01 70.02 70.03 ... 89.96 89.97 89.98 89.99
-  * lat      (lat) float64 80.0 79.99 79.98 79.97 ... 70.03 70.02 70.01 70.0
-Attributes:
-    standard_name:  normalized_difference_vegetation_index number_of_observat...
-    grid_mapping:   crs
-    units:          
-    valid_range:    [  1 250]
-    cell_methods:   area: mean</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'nobs'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 1121</li><li><span class='xr-has-index'>lon</span>: 2240</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-ba8219e8-d1d6-4e7d-bb91-802d226eadd1' class='xr-array-in' type='checkbox' checked><label for='section-ba8219e8-d1d6-4e7d-bb91-802d226eadd1' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(600, 600), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>
-    <tr>
-        <td>
-            <table style="border-collapse: collapse;">
-                <thead>
-                    <tr>
-                        <td> </td>
-                        <th> Array </th>
-                        <th> Chunk </th>
-                    </tr>
-                </thead>
-                <tbody>
-                    
-                    <tr>
-                        <th> Bytes </th>
-                        <td> 9.58 MiB </td>
-                        <td> 1.37 MiB </td>
-                    </tr>
-                    
-                    <tr>
-                        <th> Shape </th>
-                        <td> (1121, 2240) </td>
-                        <td> (600, 600) </td>
-                    </tr>
-                    <tr>
-                        <th> Dask graph </th>
-                        <td colspan="2"> 8 chunks in 4 graph layers </td>
-                    </tr>
-                    <tr>
-                        <th> Data type </th>
-                        <td colspan="2"> float32 numpy.ndarray </td>
-                    </tr>
-                </tbody>
-            </table>
-        </td>
-        <td>
-        <svg width="170" height="110" style="stroke:rgb(0,0,0);stroke-width:1" >
-
-  <!-- Horizontal lines -->
-  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
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-
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-
-  <!-- Text -->
-  <text x="60.000000" y="80.053571" font-size="1.0rem" font-weight="100" text-anchor="middle" >2240</text>
-  <text x="140.000000" y="30.026786" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,140.000000,30.026786)">1121</text>
-</svg>
-        </td>
-    </tr>
-</table></div></div></li><li class='xr-section-item'><input id='section-5e1d6a0d-8309-4135-a54a-13e05c6507a3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5e1d6a0d-8309-4135-a54a-13e05c6507a3' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>70.0 70.01 70.02 ... 89.98 89.99</div><input id='attrs-a639a201-160c-4003-ab7c-50a663c4e7f1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a639a201-160c-4003-ab7c-50a663c4e7f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29a5817b-1980-4b86-9a55-0c5dbd94f9cb' class='xr-var-data-in' type='checkbox'><label for='data-29a5817b-1980-4b86-9a55-0c5dbd94f9cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>lon</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([70.      , 70.008929, 70.017857, ..., 89.973214, 89.982143, 89.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.99 79.98 ... 70.01 70.0</div><input id='attrs-25b4019e-8fee-4ecf-af26-abf7c887883a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25b4019e-8fee-4ecf-af26-abf7c887883a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f55c8e7-ab8e-4214-876e-51cb409a8d4d' class='xr-var-data-in' type='checkbox'><label for='data-1f55c8e7-ab8e-4214-876e-51cb409a8d4d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>lat</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([80.      , 79.991071, 79.982143, ..., 70.017857, 70.008929, 70.      ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-71e6f805-8b73-441b-8002-db5812d23f63' class='xr-section-summary-in' type='checkbox'  ><label for='section-71e6f805-8b73-441b-8002-db5812d23f63' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a48751f5-e8f5-45cf-9c95-66ee2fae912f' class='xr-index-data-in' type='checkbox'/><label for='index-a48751f5-e8f5-45cf-9c95-66ee2fae912f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([70.00000000034106, 70.00892857176964, 70.01785714319823,
-       70.02678571462681,  70.0357142860554, 70.04464285748398,
-       70.05357142891256, 70.06250000034115, 70.07142857176973,
-       70.08035714319831,
-       ...
-       89.91071428608251, 89.91964285751112, 89.92857142893968,
-       89.93750000036823, 89.94642857179684, 89.95535714322546,
-       89.96428571465401, 89.97321428608257, 89.98214285751118,
-       89.99107142893979],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=2240))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6d4eedec-fcda-45af-a6e0-c000b44999c0' class='xr-index-data-in' type='checkbox'/><label for='index-6d4eedec-fcda-45af-a6e0-c000b44999c0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             80.0, 79.99107142857143, 79.98214285714286,
-       79.97321428571429, 79.96428571428572, 79.95535714285715,
-       79.94642857142858, 79.93750000000001, 79.92857142857144,
-       79.91964285714288,
-       ...
-        70.0803571428594, 70.07142857143083, 70.06250000000226,
-       70.05357142857369, 70.04464285714512, 70.03571428571655,
-       70.02678571428798, 70.01785714285941, 70.00892857143084,
-       70.00000000000227],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=1121))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-de88070d-be03-4854-b7bf-2a9ac0ee9c6c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-de88070d-be03-4854-b7bf-2a9ac0ee9c6c' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index number_of_observations</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>units :</span></dt><dd></dd><dt><span>valid_range :</span></dt><dd>[  1 250]</dd><dt><span>cell_methods :</span></dt><dd>area: mean</dd></dl></div></li></ul></div></div></div></div>
-</div>
-<p>As you can see in the above graphics we got 8 <strong>chunks</strong>.  These 8 chunks are noted as (0,0) ..(0,3) (1,0),..(1,3) as you can see in the next visualisation.</p>
-</section>
-<section id="operations-on-a-chunked-dataset">
-<h2>Operations on a chunked dataset<a class="headerlink" href="#operations-on-a-chunked-dataset" title="Permalink to this heading">#</a></h2>
-<p>Let’s have a look of our chunked test dataset backend representation.</p>
-<div class="cell docutils container">
-<div class="cell_input docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">test</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">visualize</span><span class="p">()</span>
-</pre></div>
 </div>
-</div>
-<div class="cell_output docutils container">
-<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "59a8d8760f5a4de1b8ccdc0c26ffafd4"}</script></div>
-</div>
-<p><code class="docutils literal notranslate"> <span class="pre">test.data</span></code> is the backend array Python representation of Xarray’s Data Array, <a class="reference external" href="https://docs.dask.org/en/stable/array.html"><strong>Dask Array</strong></a> when using chunking, Numpy by default.</p>
-<p>We will introduce Dask arrays and Dask graphs visualization in the next section <span class="xref myst">dask_introduction</span>.</p>
-<p>Anyway, when applying <code class="docutils literal notranslate"><span class="pre">chunk</span></code> function you may have the impression that the chunks sizes just changes and everything will be fine.</p>
-<p>However, as you can see in the graph visualization above, Xarray will actually have to fetch at least one entire initial chunk that was defined when opening the Dataset at first before rechunking at a smaller size or even selecting one value. This is true when applying any funtions on any values: Xarray will work by loading entire chunks.</p>
-<p>You can imagine that it will not be very optimal if you load one file as an entire chunk, or if your initial chunks are too big (your Python Jupyter kernel may crash!), especially with large numbers of files and large files. Choosing an appropriate chunk size is really important and depends on your analysis.</p>
-<p>You can find a really nice article by Dask team on how to chose the right chunk size <a class="reference external" href="https://blog.dask.org/2021/11/02/choosing-dask-chunk-sizes">here</a>.</p>
 <div class="alert alert-warning">
     <i class="fa-check-circle fa" style="font-size: 22px;color:#666;"></i> <b>Go Further</b>
     <br>
     <br>
     You can try to apply different ways for specifying chunk.
     <ul>
-        <li> chunks = 'auto' -> Xarray relies on Dask to use an ideal size according to the preferred chunk sizes</li>
         <li> chunks = -1 -> the entire array will be used as a single chunk
-        <li> chunks = "1MiB" -> Xarray seeks the size according to a specific memory target expressed in MiB</li>
-        <li> chunks = {'lat'=-1, 'lon'= 1000} -> chunks of entire _lat_ dimension, but splitted every 1000 values on _lon_ dimension</li>
-        <li> compare the resulting chunked data's shape, size, tasks, data.visualize..... What do you see?</li>
+        <li> chunks = {'x':-1, 'y': 1000} -> chunks of entire _x_ dimension, but splitted every 1000 values on _y_ dimension</li>
+        <li> chunks = {'x':-1, 'y': 'auto'} -> Xarray relies on Dask to use an ideal size according to the preferred chunk sizes for _y_ dimension</li>
+        <li> chunks = { 'x':-1 ,'y':"500MiB" } -> Xarray seeks the size according to a specific memory target expressed in MiB</li>
+        <li> chunks = ( 1, 3, 12048,2048) -> Specifying chunk size in the order of dimension. </li>
     </ul>
 </div></section>
+<section id="defining-the-chunk-at-the-creatioin-of-xarray">
+<h2>Defining the chunk at the creatioin of Xarray<a class="headerlink" href="#defining-the-chunk-at-the-creatioin-of-xarray" title="Permalink to this heading">#</a></h2>
+<p>We can define the chunk size when we create the object.<br />
+This is usually done with Xarray using the <code class="docutils literal notranslate"><span class="pre">chunks</span></code> kwarg when opening a file with <code class="docutils literal notranslate"><span class="pre">xr.open_dataset</span></code> or with <code class="docutils literal notranslate"><span class="pre">xr.open_mfdataset</span></code>, if you create Xarray from your local file.<br />
+In our snow index example, we create Xarray from stackstac. As stackstac’s default ‘chunksize’ definition is 1024 for x and y dimension, we had that chunksize.  We can pass the chunksize option to stdeackstac and make that bigger.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="o">%%time</span>
+<span class="n">sentinel2_l2a</span> <span class="o">=</span> <span class="n">stackstac</span><span class="o">.</span><span class="n">stack</span><span class="p">(</span><span class="n">items</span>
+                                <span class="p">,</span><span class="n">assets</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;green&#39;</span><span class="p">,</span><span class="s1">&#39;swir16&#39;</span><span class="p">,</span><span class="s1">&#39;scl&#39;</span><span class="p">]</span>
+                               <span class="p">,</span><span class="n">chunksize</span><span class="o">=</span><span class="p">(</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2048</span><span class="p">,</span><span class="mi">2048</span><span class="p">)</span>
+<span class="p">)</span>
+<span class="n">sentinel2_l2a</span>
+</pre></div>
+</div>
+</div>
+</div>
+</section>
 <section id="so-why-chunks">
 <h2>So, why chunks?<a class="headerlink" href="#so-why-chunks" title="Permalink to this heading">#</a></h2>
-<p>In the end, chunks are mandatory for accessing files or dataset that are bigger than a single computer’s memory. If all the data has to be accessed, it can be done sequentially e.g. chunks are processed one after the othe).</p>
+<p>Chunks are mandatory for accessing files or dataset that are bigger than a single computer’s memory. If all the data has to be accessed, it can be done sequentially e.g. chunks are processed one after the othe).</p>
 <p>Moreover, chunks allow for distributed processing and so increased speed for your data analysis, as seen in the next episode.</p>
 <section id="chunks-and-files">
 <h3>Chunks and files<a class="headerlink" href="#chunks-and-files" title="Permalink to this heading">#</a></h3>
@@ -3261,27 +796,184 @@ <h3>Chunks and files<a class="headerlink" href="#chunks-and-files" title="Permal
 <h2>Zarr storage format<a class="headerlink" href="#zarr-storage-format" title="Permalink to this heading">#</a></h2>
 <p>This brings to our next subjects <a class="reference external" href="https://zarr.readthedocs.io/en/stable/">Zarr</a> and <a class="reference external" href="https://fsspec.github.io/kerchunk/">Kerchunk</a>.</p>
 <p>If we can have our original dataset already ‘chunked’ and accessed in an optimized way according to it’s actual byte storage on disk, we won’t need to load entire dataset every time, and our data anlayzis, even working on the entire dataset, will be greatly optimized.</p>
-<p>Let’s convert our input data into Zarr format so that we can learn what it is. We can keep the data as in DataArray or convert that into DataSet before storing them.</p>
+<p>Let’s convert our intermediate data into Zarr format so that we can learn what it is. We can keep the data as in DataArray or convert that into DataSet before storing them.</p>
+<p>We start again from loading data using stackstac, but this time we go to next step, clipping the data and computation of snow index, and lets try to save those intermediate result in a zarr file.</p>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">test</span><span class="o">.</span><span class="n">to_zarr</span><span class="p">(</span><span class="s1">&#39;test_DataArray.zarr&#39;</span><span class="p">,</span><span class="n">mode</span><span class="o">=</span><span class="s1">&#39;w&#39;</span><span class="p">)</span>
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># Data Manipulation and Analysis Libraries</span>
+<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>  
+<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span> 
+
+<span class="c1"># Geospatial Data Handling Libraries</span>
+<span class="kn">import</span> <span class="nn">geopandas</span> <span class="k">as</span> <span class="nn">gpd</span> 
+<span class="kn">from</span> <span class="nn">shapely.geometry</span> <span class="kn">import</span> <span class="n">mapping</span>  
+<span class="kn">import</span> <span class="nn">pyproj</span>
+
+<span class="c1"># Multidimensional and Satellite Data Libraries</span>
+<span class="kn">import</span> <span class="nn">xarray</span> <span class="k">as</span> <span class="nn">xr</span> 
+<span class="kn">import</span> <span class="nn">rioxarray</span> <span class="k">as</span> <span class="nn">rio</span>
+<span class="kn">import</span> <span class="nn">stackstac</span>
+
+<span class="c1"># Data Visualization Libraries</span>
+<span class="kn">import</span> <span class="nn">holoviews</span> <span class="k">as</span> <span class="nn">hv</span>
+<span class="kn">import</span> <span class="nn">hvplot.xarray</span>
+<span class="kn">import</span> <span class="nn">hvplot.pandas</span>
+
+<span class="c1"># Data parallelization and distributed computing libraries</span>
+<span class="kn">import</span> <span class="nn">dask</span>
+<span class="kn">from</span> <span class="nn">dask.distributed</span> <span class="kn">import</span> <span class="n">Client</span><span class="p">,</span> <span class="n">progress</span><span class="p">,</span> <span class="n">LocalCluster</span>
+
+<span class="c1"># STAC Catalogue Libraries</span>
+<span class="kn">import</span> <span class="nn">pystac_client</span>
+
+<span class="kn">import</span> <span class="nn">warnings</span>
+<span class="n">warnings</span><span class="o">.</span><span class="n">filterwarnings</span><span class="p">(</span><span class="s2">&quot;ignore&quot;</span><span class="p">)</span>
 </pre></div>
 </div>
 </div>
-<div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.backends.zarr.ZarrStore at 0x7f6408e46f10&gt;
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">cluster</span> <span class="o">=</span> <span class="n">LocalCluster</span><span class="p">()</span>
+<span class="n">client</span> <span class="o">=</span> <span class="n">Client</span><span class="p">(</span><span class="n">cluster</span><span class="p">)</span>
+<span class="n">client</span>
 </pre></div>
 </div>
 </div>
 </div>
+</section>
+<section id="load-data-using-stackstac-with-specific-chunk">
+<h2>Load data using stackstac (with specific chunk)<a class="headerlink" href="#load-data-using-stackstac-with-specific-chunk" title="Permalink to this heading">#</a></h2>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">test</span><span class="o">.</span><span class="n">to_dataset</span><span class="p">()</span><span class="o">.</span><span class="n">to_zarr</span><span class="p">(</span><span class="s1">&#39;test.zarr&#39;</span><span class="p">,</span><span class="n">mode</span><span class="o">=</span><span class="s1">&#39;w&#39;</span><span class="p">)</span>
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="o">%%time</span>
+<span class="n">aoi</span> <span class="o">=</span> <span class="n">gpd</span><span class="o">.</span><span class="n">read_file</span><span class="p">(</span><span class="s1">&#39;data/catchment_outline.geojson&#39;</span><span class="p">,</span> <span class="n">crs</span><span class="o">=</span><span class="s2">&quot;EPGS:4326&quot;</span><span class="p">)</span>
+<span class="n">aoi_geojson</span> <span class="o">=</span> <span class="n">mapping</span><span class="p">(</span><span class="n">aoi</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">geometry</span><span class="p">)</span>
+<span class="n">URL</span> <span class="o">=</span> <span class="s2">&quot;https://earth-search.aws.element84.com/v1&quot;</span>
+<span class="n">catalog</span> <span class="o">=</span> <span class="n">pystac_client</span><span class="o">.</span><span class="n">Client</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">URL</span><span class="p">)</span>
+<span class="n">items</span> <span class="o">=</span> <span class="n">catalog</span><span class="o">.</span><span class="n">search</span><span class="p">(</span>
+    <span class="n">intersects</span><span class="o">=</span><span class="n">aoi_geojson</span><span class="p">,</span>
+    <span class="n">collections</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;sentinel-2-l2a&quot;</span><span class="p">],</span>
+    <span class="n">datetime</span><span class="o">=</span><span class="s2">&quot;2019-02-01/2019-06-10&quot;</span>
+<span class="p">)</span><span class="o">.</span><span class="n">item_collection</span><span class="p">()</span>
+<span class="n">ds</span> <span class="o">=</span> <span class="n">stackstac</span><span class="o">.</span><span class="n">stack</span><span class="p">(</span><span class="n">items</span>
+                                <span class="p">,</span><span class="n">assets</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;green&#39;</span><span class="p">,</span><span class="s1">&#39;swir16&#39;</span><span class="p">,</span><span class="s1">&#39;scl&#39;</span><span class="p">]</span>
+                               <span class="p">,</span><span class="n">chunksize</span><span class="o">=</span><span class="p">(</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">1024</span><span class="p">,</span><span class="mi">1024</span><span class="p">)</span>
+<span class="p">)</span>
+<span class="c1">#ds</span>
 </pre></div>
 </div>
 </div>
-<div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.backends.zarr.ZarrStore at 0x7f6408db7bc0&gt;
+</div>
+</section>
+<section id="coomputing-snow-index">
+<h2>Coomputing Snow index<a class="headerlink" href="#coomputing-snow-index" title="Permalink to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">green</span> <span class="o">=</span> <span class="n">ds</span><span class="o">.</span><span class="n">sel</span><span class="p">(</span><span class="n">band</span><span class="o">=</span><span class="s1">&#39;green&#39;</span><span class="p">)</span>
+<span class="n">swir</span> <span class="o">=</span> <span class="n">ds</span><span class="o">.</span><span class="n">sel</span><span class="p">(</span><span class="n">band</span><span class="o">=</span><span class="s1">&#39;swir16&#39;</span><span class="p">)</span>
+<span class="n">scl</span> <span class="o">=</span> <span class="n">ds</span><span class="o">.</span><span class="n">sel</span><span class="p">(</span><span class="n">band</span><span class="o">=</span><span class="s1">&#39;scl&#39;</span><span class="p">)</span>
+<span class="n">ndsi</span> <span class="o">=</span> <span class="p">(</span><span class="n">green</span> <span class="o">-</span> <span class="n">swir</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="n">green</span> <span class="o">+</span> <span class="n">swir</span><span class="p">)</span>
+<span class="n">snow</span> <span class="o">=</span> <span class="n">xr</span><span class="o">.</span><span class="n">where</span><span class="p">((</span><span class="n">ndsi</span> <span class="o">&gt;</span> <span class="mf">0.42</span><span class="p">)</span> <span class="o">&amp;</span> <span class="o">~</span><span class="n">np</span><span class="o">.</span><span class="n">isnan</span><span class="p">(</span><span class="n">ndsi</span><span class="p">),</span> <span class="mi">1</span><span class="p">,</span> <span class="n">ndsi</span><span class="p">)</span>
+<span class="n">snowmap</span> <span class="o">=</span> <span class="n">xr</span><span class="o">.</span><span class="n">where</span><span class="p">((</span><span class="n">snow</span> <span class="o">&lt;=</span> <span class="mf">0.42</span><span class="p">)</span> <span class="o">&amp;</span> <span class="o">~</span><span class="n">np</span><span class="o">.</span><span class="n">isnan</span><span class="p">(</span><span class="n">snow</span><span class="p">),</span> <span class="mi">0</span><span class="p">,</span> <span class="n">snow</span><span class="p">)</span>
+<span class="n">mask</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">logical_not</span><span class="p">(</span><span class="n">scl</span><span class="o">.</span><span class="n">isin</span><span class="p">([</span><span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">,</span> <span class="mi">3</span><span class="p">]))</span> 
+<span class="n">snow_cloud</span> <span class="o">=</span> <span class="n">xr</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">mask</span><span class="p">,</span> <span class="n">snowmap</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
+<span class="c1">#snow_cloud</span>
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+<section id="clip-the-data">
+<h2>Clip the data<a class="headerlink" href="#clip-the-data" title="Permalink to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">aoi_utm32</span> <span class="o">=</span> <span class="n">aoi</span><span class="o">.</span><span class="n">to_crs</span><span class="p">(</span><span class="n">epsg</span><span class="o">=</span><span class="mi">32632</span><span class="p">)</span>
+<span class="n">geom_utm32</span> <span class="o">=</span> <span class="n">aoi_utm32</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="s1">&#39;geometry&#39;</span><span class="p">]</span>
+<span class="n">snow_cloud</span><span class="o">.</span><span class="n">rio</span><span class="o">.</span><span class="n">write_crs</span><span class="p">(</span><span class="s2">&quot;EPSG:32632&quot;</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">snow_cloud</span><span class="o">.</span><span class="n">rio</span><span class="o">.</span><span class="n">set_nodata</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">snow_cloud</span> <span class="o">=</span> <span class="n">snow_cloud</span><span class="o">.</span><span class="n">rio</span><span class="o">.</span><span class="n">clip</span><span class="p">([</span><span class="n">geom_utm32</span><span class="p">])</span>
+<span class="c1">#snow_cloud</span>
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+<section id="lets-save-the-intermediate-result-of-a-few-days-in-a-zarr-format">
+<h2>Lets save the intermediate result of a few days in a zarr format<a class="headerlink" href="#lets-save-the-intermediate-result-of-a-few-days-in-a-zarr-format" title="Permalink to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">test</span><span class="o">=</span><span class="n">snow_cloud</span><span class="o">.</span><span class="n">isel</span><span class="p">(</span><span class="n">time</span><span class="o">=</span><span class="nb">slice</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">3</span><span class="p">))</span>
+<span class="n">test</span>
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+<section id="before-saving-we-clean-the-chunk-size-clean-attribute-and-save-the-data-in-xarray-dataset-format">
+<h2>Before saving, we clean the chunk size, clean attribute and save the data in Xarray DataSet format<a class="headerlink" href="#before-saving-we-clean-the-chunk-size-clean-attribute-and-save-the-data-in-xarray-dataset-format" title="Permalink to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">test</span><span class="o">=</span><span class="n">test</span><span class="o">.</span><span class="n">chunk</span><span class="p">(</span><span class="n">chunks</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;x&#39;</span><span class="p">:</span><span class="s1">&#39;auto&#39;</span><span class="p">,</span> <span class="s1">&#39;y&#39;</span><span class="p">:</span> <span class="s1">&#39;auto&#39;</span><span class="p">})</span><span class="o">.</span><span class="n">to_dataset</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s1">&#39;data&#39;</span><span class="p">)</span>
+<span class="n">test</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="o">%%time</span>
+
+<span class="k">def</span> <span class="nf">remove_attrs</span><span class="p">(</span><span class="n">obj</span><span class="p">,</span> <span class="n">to_remove</span><span class="p">):</span>
+    <span class="n">new</span> <span class="o">=</span> <span class="n">obj</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
+    <span class="n">new</span><span class="o">.</span><span class="n">attrs</span> <span class="o">=</span> <span class="p">{</span><span class="n">k</span><span class="p">:</span> <span class="n">v</span> <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">obj</span><span class="o">.</span><span class="n">attrs</span><span class="o">.</span><span class="n">items</span><span class="p">()</span> <span class="k">if</span> <span class="n">k</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">to_remove</span><span class="p">}</span>
+
+    <span class="k">return</span> <span class="n">new</span>
+
+<span class="k">def</span> <span class="nf">encode</span><span class="p">(</span><span class="n">obj</span><span class="p">):</span>
+    <span class="n">object_coords</span> <span class="o">=</span> <span class="p">[</span><span class="n">name</span> <span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">coord</span> <span class="ow">in</span> <span class="n">obj</span><span class="o">.</span><span class="n">coords</span><span class="o">.</span><span class="n">items</span><span class="p">()</span> <span class="k">if</span> <span class="n">coord</span><span class="o">.</span><span class="n">dtype</span><span class="o">.</span><span class="n">kind</span> <span class="o">==</span> <span class="s2">&quot;O&quot;</span><span class="p">]</span>
+    <span class="k">return</span> <span class="n">obj</span><span class="o">.</span><span class="n">drop_vars</span><span class="p">(</span><span class="n">object_coords</span><span class="p">)</span><span class="o">.</span><span class="n">pipe</span><span class="p">(</span><span class="n">remove_attrs</span><span class="p">,</span> <span class="p">[</span><span class="s2">&quot;spec&quot;</span><span class="p">,</span> <span class="s2">&quot;transform&quot;</span><span class="p">])</span>
+
+
+<span class="n">test</span><span class="o">.</span><span class="n">pipe</span><span class="p">(</span><span class="n">encode</span><span class="p">)</span><span class="o">.</span><span class="n">to_zarr</span><span class="p">(</span><span class="s1">&#39;test.zarr&#39;</span><span class="p">,</span><span class="n">mode</span><span class="o">=</span><span class="s1">&#39;w&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+<section id="load-the-temporaly-data-saved-as-zarr-back-to-xarray">
+<h2>Load the temporaly data saved as zarr back to Xarray<a class="headerlink" href="#load-the-temporaly-data-saved-as-zarr-back-to-xarray" title="Permalink to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">snow_cloud</span><span class="o">=</span><span class="n">xr</span><span class="o">.</span><span class="n">open_zarr</span><span class="p">(</span><span class="s1">&#39;test.zarr&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">data</span>
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+<section id="group-by-to-a-day-and-plot-the-results">
+<h2>Group by to a day, and plot the results<a class="headerlink" href="#group-by-to-a-day-and-plot-the-results" title="Permalink to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">clipped_date</span> <span class="o">=</span> <span class="n">snow_cloud</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="n">snow_cloud</span><span class="o">.</span><span class="n">time</span><span class="o">.</span><span class="n">dt</span><span class="o">.</span><span class="n">floor</span><span class="p">(</span><span class="s1">&#39;D&#39;</span><span class="p">))</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">skipna</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">clipped_date</span> <span class="o">=</span> <span class="n">clipped_date</span><span class="o">.</span><span class="n">rename</span><span class="p">({</span><span class="s1">&#39;floor&#39;</span><span class="p">:</span> <span class="s1">&#39;date&#39;</span><span class="p">})</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">clipped_date</span><span class="o">.</span><span class="n">hvplot</span><span class="o">.</span><span class="n">image</span><span class="p">(</span>
+    <span class="n">x</span><span class="o">=</span><span class="s1">&#39;x&#39;</span><span class="p">,</span>
+    <span class="n">y</span><span class="o">=</span><span class="s1">&#39;y&#39;</span><span class="p">,</span>
+    <span class="n">groupby</span><span class="o">=</span><span class="s1">&#39;date&#39;</span><span class="p">,</span>
+    <span class="n">crs</span><span class="o">=</span><span class="n">pyproj</span><span class="o">.</span><span class="n">CRS</span><span class="o">.</span><span class="n">from_epsg</span><span class="p">(</span><span class="mi">32632</span><span class="p">),</span>
+    <span class="n">cmap</span><span class="o">=</span><span class="s1">&#39;Pastel2&#39;</span><span class="p">,</span>
+    <span class="n">clim</span><span class="o">=</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">),</span>
+    <span class="n">frame_width</span><span class="o">=</span><span class="mi">500</span><span class="p">,</span>
+    <span class="n">frame_height</span><span class="o">=</span><span class="mi">500</span><span class="p">,</span>
+    <span class="n">title</span><span class="o">=</span><span class="s1">&#39;Snowmap&#39;</span><span class="p">,</span>
+    <span class="n">geo</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">tiles</span><span class="o">=</span><span class="s1">&#39;OSM&#39;</span><span class="p">)</span>
 </pre></div>
 </div>
 </div>
@@ -3290,42 +982,28 @@ <h2>Zarr storage format<a class="headerlink" href="#zarr-storage-format" title="
     <i class="fa-check-circle fa" style="font-size: 22px;color:#666;"></i> <b>Exercise</b>
     <br>
     <ul>
+        <li>What about saving the data in Netcdf format? `ls -la test.zarr` and  `ls -la test.zarr/nobs `</li>
         <li>You can try to explore the zarr file you just created using `ls -la test.zarr` and  `ls -la test.zarr/nobs `</li>
         <li>You can explore zarr metadata file by `cat test.zarr/.zmetadata` </li>
         <li>Did you find the __chunks__ we defined previously in your zarr file? </li>
     </ul>
 </div><div class="cell docutils container">
 <div class="cell_input docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="o">!</span>du<span class="w"> </span>-sh<span class="w"> </span>test.zarr/
-</pre></div>
-</div>
-</div>
-<div class="cell_output docutils container">
-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>92K	test.zarr/
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">xr</span><span class="o">.</span><span class="n">open_zarr</span><span class="p">(</span><span class="s1">&#39;test.zarr&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">to_netcdf</span><span class="p">(</span><span class="s1">&#39;test.nc&#39;</span><span class="p">)</span>
 </pre></div>
 </div>
 </div>
 </div>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="o">!</span>ls<span class="w"> </span>-al<span class="w"> </span>test.zarr/nobs
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="o">!</span>du<span class="w"> </span>-sh<span class="w"> </span>test.zarr/<span class="w"> </span>test.nc
 </pre></div>
 </div>
 </div>
-<div class="cell_output docutils container">
-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>total 48
-drwxr-xr-x 2 runner docker 4096 Oct 31 15:26 .
-drwxr-xr-x 5 runner docker 4096 Oct 31 15:26 ..
--rw-r--r-- 1 runner docker  341 Oct 31 15:26 .zarray
--rw-r--r-- 1 runner docker  304 Oct 31 15:26 .zattrs
--rw-r--r-- 1 runner docker 1482 Oct 31 15:26 0.0
--rw-r--r-- 1 runner docker 1482 Oct 31 15:26 0.1
--rw-r--r-- 1 runner docker 1482 Oct 31 15:26 0.2
--rw-r--r-- 1 runner docker 1482 Oct 31 15:26 0.3
--rw-r--r-- 1 runner docker 1482 Oct 31 15:26 1.0
--rw-r--r-- 1 runner docker 1482 Oct 31 15:26 1.1
--rw-r--r-- 1 runner docker 1482 Oct 31 15:26 1.2
--rw-r--r-- 1 runner docker 1482 Oct 31 15:26 1.3
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="o">!</span>ls<span class="w">  </span>-la<span class="w"> </span>test.zarr/data
 </pre></div>
 </div>
 </div>
@@ -3336,44 +1014,10 @@ <h2>Zarr storage format<a class="headerlink" href="#zarr-storage-format" title="
 </pre></div>
 </div>
 </div>
-<div class="cell_output docutils container">
-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>{
-    &quot;metadata&quot;: {
-        &quot;.zattrs&quot;: {},
-        &quot;.zgroup&quot;: {
-            &quot;zarr_format&quot;: 2
-        },
-        &quot;lat/.zarray&quot;: {
-            &quot;chunks&quot;: [
-                1121
-            ],
-            &quot;compressor&quot;: {
-                &quot;blocksize&quot;: 0,
-                &quot;clevel&quot;: 5,
-                &quot;cname&quot;: &quot;lz4&quot;,
-                &quot;id&quot;: &quot;blosc&quot;,
-                &quot;shuffle&quot;: 1
-            },
-            &quot;dtype&quot;: &quot;&lt;f8&quot;,
-            &quot;fill_value&quot;: &quot;NaN&quot;,
-            &quot;filters&quot;: null,
-            &quot;order&quot;: &quot;C&quot;,
-            &quot;shape&quot;: [
-                1121
-            ],
-            &quot;zarr_format&quot;: 2
-        },
-        &quot;lat/.zattrs&quot;: {
-            &quot;DIMENSION_LABELS&quot;: &quot;lat&quot;,
-            &quot;_ARRAY_DIMENSIONS&quot;: [
-                &quot;lat&quot;
-</pre></div>
-</div>
-</div>
 </div>
 <p>Zarr format main characteristics are the following:</p>
 <ul class="simple">
-<li><p>Every chunk of a Zarr dataset is stored as a single file (see x.y files in <code class="docutils literal notranslate"><span class="pre">ls</span> <span class="pre">-al</span> <span class="pre">test.zarr/nobs</span></code>)</p></li>
+<li><p>Every chunk of a Zarr dataset is stored as a single file (see x.y files in <code class="docutils literal notranslate"><span class="pre">ls</span> <span class="pre">-al</span> <span class="pre">test.zarr/data</span></code>)</p></li>
 <li><p>Each Data array in a Zarr dataset has a two unique files containing metadata:</p>
 <ul>
 <li><p>.zattrs for dataset or dataarray general metadatas</p></li>
@@ -3411,3583 +1055,44 @@ <h3>Extract chunk information<a class="headerlink" href="#extract-chunk-informat
 <div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">remote_filename</span> <span class="o">=</span> <span class="s1">&#39;https://object-store.cloud.muni.cz/swift/v1/foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1221_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;</span>
 <span class="k">with</span> <span class="n">fsspec</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">remote_filename</span><span class="p">)</span> <span class="k">as</span> <span class="n">inf</span><span class="p">:</span>
     <span class="n">h5chunks</span> <span class="o">=</span> <span class="n">kerchunk</span><span class="o">.</span><span class="n">hdf</span><span class="o">.</span><span class="n">SingleHdf5ToZarr</span><span class="p">(</span><span class="n">inf</span><span class="p">,</span> <span class="n">remote_filename</span><span class="p">,</span> <span class="n">inline_threshold</span><span class="o">=</span><span class="mi">100</span><span class="p">)</span>
-    <span class="n">chunk_info</span> <span class="o">=</span> <span class="n">h5chunks</span><span class="o">.</span><span class="n">translate</span><span class="p">()</span>
-</pre></div>
-</div>
-</div>
-</div>
-<p>Let’s have a look at <code class="docutils literal notranslate"><span class="pre">chunk_info</span></code>. It is a Python dictionary so we can use <code class="docutils literal notranslate"><span class="pre">pprint</span></code> to print it nicely.</p>
-<p>Content is a bit complicated, but it’s only metadata in Zarr format indicating what’s in the original file, and where the chunks of the file are located (bytes offset).</p>
-<div class="cell tag_hide-output docutils container">
-<div class="cell_input above-output-prompt docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">pprint</span> <span class="kn">import</span> <span class="n">pprint</span>
-<span class="n">pprint</span><span class="p">(</span><span class="n">chunk_info</span><span class="p">)</span>
-</pre></div>
-</div>
-</div>
-<details class="hide below-input">
-<summary aria-label="Toggle hidden content">
-<span class="collapsed">Show code cell output</span>
-<span class="expanded">Hide code cell output</span>
-</summary>
-<div class="cell_output docutils container">
-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>{&#39;refs&#39;: {&#39;.zattrs&#39;: &#39;{&quot;Conventions&quot;:&quot;CF-1.6&quot;,&quot;archive_facility&quot;:&quot;VITO&quot;,&quot;copyright&quot;:&quot;Copernicus &#39;
-                     &#39;Service information 2021&quot;,&quot;history&quot;:&quot;2021-03-01 - &#39;
-                     &#39;Processing line NDVI &#39;
-                     &#39;LTS&quot;,&quot;identifier&quot;:&quot;urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-1221_GLOBE_V3.0.1&quot;,&quot;institution&quot;:&quot;VITO &#39;
-                     &#39;NV&quot;,&quot;long_name&quot;:&quot;Normalized Difference Vegetation &#39;
-                     &#39;Index&quot;,&quot;orbit_type&quot;:&quot;LEO&quot;,&quot;parent_identifier&quot;:&quot;urn:cgls:global:ndvi_stats_all&quot;,&quot;platform&quot;:&quot;SPOT-4, &#39;
-                     &#39;SPOT-5, &#39;
-                     &#39;Proba-V&quot;,&quot;processing_level&quot;:&quot;L4&quot;,&quot;processing_mode&quot;:&quot;Offline&quot;,&quot;product_version&quot;:&quot;V3.0.1&quot;,&quot;references&quot;:&quot;https:\\/\\/land.copernicus.eu\\/global\\/products\\/ndvi&quot;,&quot;sensor&quot;:&quot;VEGETATION-1, &#39;
-                     &#39;VEGETATION-2, VEGETATION&quot;,&quot;source&quot;:&quot;Derived from EO &#39;
-                     &#39;satellite &#39;
-                     &#39;imagery&quot;,&quot;time_coverage_end&quot;:&quot;2019-12-31T23:59:59Z&quot;,&quot;time_coverage_start&quot;:&quot;1999-01-01T00:00:00Z&quot;,&quot;title&quot;:&quot;Normalized &#39;
-                     &#39;Difference Vegetation Index: Long Term Statistics 1KM: &#39;
-                     &#39;GLOBE 1999-2019 1221&quot;}&#39;,
-          &#39;.zgroup&#39;: &#39;{&quot;zarr_format&quot;:2}&#39;,
-          &#39;crs/.zarray&#39;: &#39;{&quot;chunks&quot;:[],&quot;compressor&quot;:null,&quot;dtype&quot;:&quot;|S1&quot;,&quot;fill_value&quot;:&quot;IA==&quot;,&quot;filters&quot;:null,&quot;order&quot;:&quot;C&quot;,&quot;shape&quot;:[],&quot;zarr_format&quot;:2}&#39;,
-          &#39;crs/.zattrs&#39;: &#39;{&quot;GeoTransform&quot;:&quot;-180.0000000000 0.0089285714 0.0 &#39;
-                         &#39;80.0000000000 0.0 &#39;
-                         &#39;-0.0089285714&quot;,&quot;_ARRAY_DIMENSIONS&quot;:[],&quot;_CoordinateAxisTypes&quot;:&quot;GeoX &#39;
-                         &#39;GeoY&quot;,&quot;_CoordinateTransformType&quot;:&quot;Projection&quot;,&quot;grid_mapping_name&quot;:&quot;latitude_longitude&quot;,&quot;inverse_flattening&quot;:298.257223563,&quot;long_name&quot;:&quot;coordinate &#39;
-                         &#39;reference &#39;
-                         &#39;system&quot;,&quot;longitude_of_prime_meridian&quot;:0.0,&quot;semi_major_axis&quot;:6378137.0,&quot;spatial_ref&quot;:&quot;GEOGCS[\\&quot;WGS &#39;
-                         &#39;84\\&quot;,DATUM[\\&quot;WGS_1984\\&quot;,SPHEROID[\\&quot;WGS &#39;
-                         &#39;84\\&quot;,6378137,298.257223563,AUTHORITY[\\&quot;EPSG\\&quot;,\\&quot;7030\\&quot;]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY[\\&quot;EPSG\\&quot;,\\&quot;6326\\&quot;]],PRIMEM[\\&quot;Greenwich\\&quot;,0,AUTHORITY[\\&quot;EPSG\\&quot;,\\&quot;8901\\&quot;]],UNIT[\\&quot;degree\\&quot;,0.0174532925199433,AUTHORITY[\\&quot;EPSG\\&quot;,\\&quot;9108\\&quot;]],AUTHORITY[\\&quot;EPSG\\&quot;,\\&quot;4326\\&quot;]]&quot;}&#39;,
-          &#39;lat/.zarray&#39;: &#39;{&quot;chunks&quot;:[15680],&quot;compressor&quot;:null,&quot;dtype&quot;:&quot;&lt;f8&quot;,&quot;fill_value&quot;:null,&quot;filters&quot;:null,&quot;order&quot;:&quot;C&quot;,&quot;shape&quot;:[15680],&quot;zarr_format&quot;:2}&#39;,
-          &#39;lat/.zattrs&#39;: &#39;{&quot;DIMENSION_LABELS&quot;:&quot;lat&quot;,&quot;_ARRAY_DIMENSIONS&quot;:[&quot;lat&quot;],&quot;_CoordinateAxisType&quot;:&quot;Lat&quot;,&quot;axis&quot;:&quot;Y&quot;,&quot;long_name&quot;:&quot;latitude&quot;,&quot;standard_name&quot;:&quot;latitude&quot;,&quot;units&quot;:&quot;degrees_north&quot;}&#39;,
-          &#39;lat/0&#39;: [&#39;https://object-store.cloud.muni.cz/swift/v1/foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1221_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
-                    327056,
-                    125440],
-          &#39;lon/.zarray&#39;: &#39;{&quot;chunks&quot;:[40320],&quot;compressor&quot;:null,&quot;dtype&quot;:&quot;&lt;f8&quot;,&quot;fill_value&quot;:null,&quot;filters&quot;:null,&quot;order&quot;:&quot;C&quot;,&quot;shape&quot;:[40320],&quot;zarr_format&quot;:2}&#39;,
-          &#39;lon/.zattrs&#39;: &#39;{&quot;DIMENSION_LABELS&quot;:&quot;lon&quot;,&quot;_ARRAY_DIMENSIONS&quot;:[&quot;lon&quot;],&quot;_CoordinateAxisType&quot;:&quot;Lon&quot;,&quot;axis&quot;:&quot;X&quot;,&quot;long_name&quot;:&quot;longitude&quot;,&quot;standard_name&quot;:&quot;longitude&quot;,&quot;units&quot;:&quot;degrees_east&quot;}&#39;,
-          &#39;lon/0&#39;: [&#39;https://object-store.cloud.muni.cz/swift/v1/foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1221_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
-                    739,
-                    322560],
-          &#39;max/.zarray&#39;: &#39;{&quot;chunks&quot;:[1207,3102],&quot;compressor&quot;:null,&quot;dtype&quot;:&quot;|u1&quot;,&quot;fill_value&quot;:255,&quot;filters&quot;:[{&quot;elementsize&quot;:1,&quot;id&quot;:&quot;shuffle&quot;},{&quot;id&quot;:&quot;zlib&quot;,&quot;level&quot;:4}],&quot;order&quot;:&quot;C&quot;,&quot;shape&quot;:[15680,40320],&quot;zarr_format&quot;:2}&#39;,
-          &#39;max/.zattrs&#39;: &#39;{&quot;_ARRAY_DIMENSIONS&quot;:[&quot;lat&quot;,&quot;lon&quot;],&quot;add_offset&quot;:-0.08,&quot;cell_methods&quot;:&quot;area: &#39;
-                         &#39;mean time: maximum&quot;,&quot;flag_meanings&quot;:&quot;sea &#39;
-                         &#39;no_data&quot;,&quot;flag_values&quot;:[254,255],&quot;grid_mapping&quot;:&quot;crs&quot;,&quot;long_name&quot;:&quot;Maximum &#39;
-                         &#39;Normalized Difference Vegetation Index over time &#39;
-                         &#39;period&quot;,&quot;missing_value&quot;:255,&quot;scale_factor&quot;:0.004,&quot;standard_name&quot;:&quot;normalized_difference_vegetation_index&quot;,&quot;units&quot;:&quot; &#39;
-                         &#39;&quot;,&quot;valid_range&quot;:[0,250]}&#39;,
-          &#39;max/0.0&#39;: [&#39;https://object-store.cloud.muni.cz/swift/v1/foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1221_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
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-          &#39;max/0.4&#39;: [&#39;https://object-store.cloud.muni.cz/swift/v1/foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1221_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
-                      4701770,
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-          &#39;max/0.5&#39;: [&#39;https://object-store.cloud.muni.cz/swift/v1/foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1221_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
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-                      3875],
-          &#39;max/0.7&#39;: [&#39;https://object-store.cloud.muni.cz/swift/v1/foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1221_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
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-          &#39;max/0.8&#39;: [&#39;https://object-store.cloud.muni.cz/swift/v1/foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1221_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
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-          &#39;max/0.9&#39;: [&#39;https://object-store.cloud.muni.cz/swift/v1/foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1221_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
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-                        443348522,
-                        1310803],
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-                        448181356,
-                        291178],
-          &#39;stdev/9.9&#39;: [&#39;https://object-store.cloud.muni.cz/swift/v1/foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1221_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
-                        383786694,
-                        3651]},
- &#39;version&#39;: 1}
-</pre></div>
-</div>
-</div>
-</details>
-</div>
-<div class="alert alert-warning">
-    <i class="fa-check-circle fa" style="font-size: 22px;color:#666;"></i> <b>Exercise</b>
-    <br>
-    <ul>
-        <li>Did you recognise the similarities with test.zarr's zarr metadata file? </li>
-    </ul>
-</div><p>After we have collected information on the native file chunks in the original data file and consolidated our Zarr metadata, we can open the files using <code class="docutils literal notranslate"><span class="pre">zarr</span></code> and pass this chunk information into a storage option. We also need to pass <code class="docutils literal notranslate"><span class="pre">&quot;consolidated&quot;:</span> <span class="pre">False</span></code> because the original dataset does not contain any <code class="docutils literal notranslate"><span class="pre">zarr</span></code> consolidating metadata.</p>
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-            <span class="s2">&quot;fo&quot;</span><span class="p">:</span> <span class="n">chunk_info</span><span class="p">,</span>
-        <span class="p">},</span>
-        <span class="s2">&quot;consolidated&quot;</span><span class="p">:</span> <span class="kc">False</span>
-    <span class="p">}</span>
-<span class="p">)</span>
-<span class="n">LTS</span>
-</pre></div>
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-</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;
-Dimensions:  (lat: 15680, lon: 40320)
-Coordinates:
-  * lat      (lat) float64 80.0 79.99 79.98 79.97 ... -59.97 -59.98 -59.99
-  * lon      (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0
-Data variables:
-    crs      object ...
-    max      (lat, lon) float32 ...
-    mean     (lat, lon) float32 ...
-    median   (lat, lon) float32 ...
-    min      (lat, lon) float32 ...
-    nobs     (lat, lon) float32 ...
-    stdev    (lat, lon) float32 ...
-Attributes: (12/19)
-    Conventions:          CF-1.6
-    archive_facility:     VITO
-    copyright:            Copernicus Service information 2021
-    history:              2021-03-01 - Processing line NDVI LTS
-    identifier:           urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-1...
-    institution:          VITO NV
-    ...                   ...
-    references:           https://land.copernicus.eu/global/products/ndvi
-    sensor:               VEGETATION-1, VEGETATION-2, VEGETATION
-    source:               Derived from EO satellite imagery
-    time_coverage_end:    2019-12-31T23:59:59Z
-    time_coverage_start:  1999-01-01T00:00:00Z
-    title:                Normalized Difference Vegetation Index: Long Term S...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-564772fd-3653-4750-a3b9-ffebb971e325' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-564772fd-3653-4750-a3b9-ffebb971e325' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 15680</li><li><span class='xr-has-index'>lon</span>: 40320</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-0a0fec6a-3e4c-4755-96ee-bf52e0a44fc2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0a0fec6a-3e4c-4755-96ee-bf52e0a44fc2' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.99 79.98 ... -59.98 -59.99</div><input id='attrs-ad80ef75-c8dd-4de3-b144-b45640274880' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad80ef75-c8dd-4de3-b144-b45640274880' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8dfef5e-9a4b-457d-99b9-9702a7c6802c' class='xr-var-data-in' type='checkbox'><label for='data-b8dfef5e-9a4b-457d-99b9-9702a7c6802c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lat</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 80.      ,  79.991071,  79.982143, ..., -59.973214, -59.982143,
-       -59.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-694773dd-1160-4481-8115-ddf4c886dd53' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-694773dd-1160-4481-8115-ddf4c886dd53' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-241cdffc-620a-40fd-84da-ddfaa9c1eabe' class='xr-var-data-in' type='checkbox'><label for='data-241cdffc-620a-40fd-84da-ddfaa9c1eabe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lon</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-180.      , -179.991071, -179.982143, ...,  179.973214,  179.982143,
-        179.991071])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-96510d25-f2c7-40c3-bba4-db1177622561' class='xr-section-summary-in' type='checkbox'  checked><label for='section-96510d25-f2c7-40c3-bba4-db1177622561' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a085b526-6f74-48da-92ee-b70bf7b809f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a085b526-6f74-48da-92ee-b70bf7b809f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aae60d93-e394-4e9e-9e47-0ea71126d935' class='xr-var-data-in' type='checkbox'><label for='data-aae60d93-e394-4e9e-9e47-0ea71126d935' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GeoTransform :</span></dt><dd>-180.0000000000 0.0089285714 0.0 80.0000000000 0.0 -0.0089285714</dd><dt><span>_CoordinateAxisTypes :</span></dt><dd>GeoX GeoY</dd><dt><span>_CoordinateTransformType :</span></dt><dd>Projection</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>long_name :</span></dt><dd>coordinate reference system</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9108&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=object]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8f728033-f06f-4206-a461-e48f19be0a65' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f728033-f06f-4206-a461-e48f19be0a65' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b45ae4f8-8076-4fa9-ad4c-a040334f29d3' class='xr-var-data-in' type='checkbox'><label for='data-b45ae4f8-8076-4fa9-ad4c-a040334f29d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: maximum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Maximum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[632217600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ed40b94d-4f36-4e02-b30c-4d5c0fcf8551' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ed40b94d-4f36-4e02-b30c-4d5c0fcf8551' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-138b6086-66d4-4010-b92b-b50e0a1852d0' class='xr-var-data-in' type='checkbox'><label for='data-138b6086-66d4-4010-b92b-b50e0a1852d0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: mean</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Mean Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[632217600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>median</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-697b77e4-f701-4648-9c26-b1dc10a90931' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-697b77e4-f701-4648-9c26-b1dc10a90931' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad32988a-dfe5-404f-a14d-74290c9254b8' class='xr-var-data-in' type='checkbox'><label for='data-ad32988a-dfe5-404f-a14d-74290c9254b8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: median</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Median Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[632217600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0d1a1043-0138-46df-ad7c-e3693f738aa8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d1a1043-0138-46df-ad7c-e3693f738aa8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96d17567-9191-40a0-89e0-9977e713d854' class='xr-var-data-in' type='checkbox'><label for='data-96d17567-9191-40a0-89e0-9977e713d854' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: minimum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Minimum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[632217600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nobs</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b64a0e4a-aceb-4a25-a2e6-697b1b823562' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b64a0e4a-aceb-4a25-a2e6-697b1b823562' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a7da9e5-3534-4abf-87bb-16c102d75c15' class='xr-var-data-in' type='checkbox'><label for='data-1a7da9e5-3534-4abf-87bb-16c102d75c15' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index number_of_observations</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[1, 250]</dd></dl></div><div class='xr-var-data'><pre>[632217600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stdev</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b8bc4248-9379-493d-ada5-629be34cab7e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b8bc4248-9379-493d-ada5-629be34cab7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51b9d311-0bff-432b-8e81-ee44fa3dda1d' class='xr-var-data-in' type='checkbox'><label for='data-51b9d311-0bff-432b-8e81-ee44fa3dda1d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: standard_deviation</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Standard deviation Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[632217600 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ea00e121-b0ad-4f28-8196-678341366ea8' class='xr-section-summary-in' type='checkbox'  ><label for='section-ea00e121-b0ad-4f28-8196-678341366ea8' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-fce5fc5b-11b6-44e1-8504-9ea8ae4ce909' class='xr-index-data-in' type='checkbox'/><label for='index-fce5fc5b-11b6-44e1-8504-9ea8ae4ce909' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               80.0,   79.99107142857143,   79.98214285714286,
-         79.97321428571429,   79.96428571428572,   79.95535714285715,
-         79.94642857142858,   79.93750000000001,   79.92857142857144,
-         79.91964285714288,
-       ...
-       -59.910714285682474,  -59.91964285711106,  -59.92857142853961,
-        -59.93749999996817,  -59.94642857139675, -59.955357142825335,
-        -59.96428571425389, -59.973214285682445,  -59.98214285711103,
-        -59.99107142853961],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=15680))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-75d25d7f-2fa2-4b72-a4bb-9457e117d8f6' class='xr-index-data-in' type='checkbox'/><label for='index-75d25d7f-2fa2-4b72-a4bb-9457e117d8f6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -180.0, -179.99107142857142, -179.98214285714283,
-       -179.97321428571425, -179.96428571428567, -179.95535714285708,
-        -179.9464285714285, -179.93749999999991, -179.92857142857133,
-       -179.91964285714275,
-       ...
-         179.9107142862053,   179.9196428576339,  179.92857142906246,
-          179.937500000491,  179.94642857191963,  179.95535714334824,
-         179.9642857147768,  179.97321428620535,  179.98214285763396,
-        179.99107142906257],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=40320))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-de09b20f-7528-4a31-93ec-86aa30d94b27' class='xr-section-summary-in' type='checkbox'  ><label for='section-de09b20f-7528-4a31-93ec-86aa30d94b27' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>archive_facility :</span></dt><dd>VITO</dd><dt><span>copyright :</span></dt><dd>Copernicus Service information 2021</dd><dt><span>history :</span></dt><dd>2021-03-01 - Processing line NDVI LTS</dd><dt><span>identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-1221_GLOBE_V3.0.1</dd><dt><span>institution :</span></dt><dd>VITO NV</dd><dt><span>long_name :</span></dt><dd>Normalized Difference Vegetation Index</dd><dt><span>orbit_type :</span></dt><dd>LEO</dd><dt><span>parent_identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all</dd><dt><span>platform :</span></dt><dd>SPOT-4, SPOT-5, Proba-V</dd><dt><span>processing_level :</span></dt><dd>L4</dd><dt><span>processing_mode :</span></dt><dd>Offline</dd><dt><span>product_version :</span></dt><dd>V3.0.1</dd><dt><span>references :</span></dt><dd>https://land.copernicus.eu/global/products/ndvi</dd><dt><span>sensor :</span></dt><dd>VEGETATION-1, VEGETATION-2, VEGETATION</dd><dt><span>source :</span></dt><dd>Derived from EO satellite imagery</dd><dt><span>time_coverage_end :</span></dt><dd>2019-12-31T23:59:59Z</dd><dt><span>time_coverage_start :</span></dt><dd>1999-01-01T00:00:00Z</dd><dt><span>title :</span></dt><dd>Normalized Difference Vegetation Index: Long Term Statistics 1KM: GLOBE 1999-2019 1221</dd></dl></div></li></ul></div></div></div></div>
+    <span class="n">chunk_info</span> <span class="o">=</span> <span class="n">h5chunks</span><span class="o">.</span><span class="n">translate</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+</div>
+<p>Let’s have a look at <code class="docutils literal notranslate"><span class="pre">chunk_info</span></code>. It is a Python dictionary so we can use <code class="docutils literal notranslate"><span class="pre">pprint</span></code> to print it nicely.</p>
+<p>Content is a bit complicated, but it’s only metadata in Zarr format indicating what’s in the original file, and where the chunks of the file are located (bytes offset).</p>
+<div class="cell tag_hide-output docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">pprint</span> <span class="kn">import</span> <span class="n">pprint</span>
+<span class="n">pprint</span><span class="p">(</span><span class="n">chunk_info</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="alert alert-warning">
+    <i class="fa-check-circle fa" style="font-size: 22px;color:#666;"></i> <b>Exercise</b>
+    <br>
+    <ul>
+        <li>Did you recognise the similarities with test.zarr's zarr metadata file? </li>
+    </ul>
+</div><p>After we have collected information on the native file chunks in the original data file and consolidated our Zarr metadata, we can open the files using <code class="docutils literal notranslate"><span class="pre">zarr</span></code> and pass this chunk information into a storage option. We also need to pass <code class="docutils literal notranslate"><span class="pre">&quot;consolidated&quot;:</span> <span class="pre">False</span></code> because the original dataset does not contain any <code class="docutils literal notranslate"><span class="pre">zarr</span></code> consolidating metadata.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">LTS</span> <span class="o">=</span> <span class="n">xr</span><span class="o">.</span><span class="n">open_dataset</span><span class="p">(</span>
+    <span class="s2">&quot;reference://&quot;</span><span class="p">,</span> 
+    <span class="n">engine</span><span class="o">=</span><span class="s2">&quot;zarr&quot;</span><span class="p">,</span>
+    <span class="n">backend_kwargs</span><span class="o">=</span><span class="p">{</span>
+        <span class="s2">&quot;storage_options&quot;</span><span class="p">:</span> <span class="p">{</span>
+            <span class="s2">&quot;fo&quot;</span><span class="p">:</span> <span class="n">chunk_info</span><span class="p">,</span>
+        <span class="p">},</span>
+        <span class="s2">&quot;consolidated&quot;</span><span class="p">:</span> <span class="kc">False</span>
+    <span class="p">}</span>
+<span class="p">)</span>
+<span class="n">LTS</span>
+</pre></div>
+</div>
+</div>
 </div>
 <p>As you can notice above, all the Data Variables are already chunked according to the native file chunks of the NetCDF file.</p>
 </section>
@@ -7001,47 +1106,6 @@ <h3>Combine all LTS files into one kerchunked single ensemble dataset<a class="h
 </pre></div>
 </div>
 </div>
-<div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&#39;foss4g-data/CGLS_LTS_1999_2019/&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-0101_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-0111_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-0121_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-0201_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-0211_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-0221_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-0301_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-0311_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-0321_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-0401_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-0411_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-0421_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-0501_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-0511_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
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- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-0801_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-0811_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
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- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-0921_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1001_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1011_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1021_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1101_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1111_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1121_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1201_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1211_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;,
- &#39;foss4g-data/CGLS_LTS_1999_2019/c_gls_NDVI-LTS_1999-2019-1221_GLOBE_VGT-PROBAV_V3.0.1.nc&#39;]
-</pre></div>
-</div>
-</div>
 </div>
 <p>We have 36 files to process, but for this chunking_introduction example, we’ll just use 6 file so that it take less time.</p>
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-</pre></div>
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 <p>This time we use <code class="docutils literal notranslate"><span class="pre">MultiZarrToZarr</span></code> to combine multiple kerchunked datasets into a single logical aggregated dataset. Like when opening multiple files with Xarray <code class="docutils literal notranslate"><span class="pre">open_mfdataset</span></code>, we need to tell <code class="docutils literal notranslate"><span class="pre">MultiZarrToZarr</span></code> how to concatenate all the files. There is no time dimension in the original dataset, but one file corresponds to one date (average over the period 1999-2019 for a given 10-day period e.g. January 01, January 11, January 21, etc.).</p>
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-  * lat      (lat) float64 80.0 79.99 79.98 79.97 ... -59.97 -59.98 -59.99
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-Attributes: (12/19)
-    Conventions:          CF-1.6
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-    copyright:            Copernicus Service information 2021
-    history:              2021-03-01 - Processing line NDVI LTS
-    identifier:           urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-0...
-    institution:          VITO NV
-    ...                   ...
-    references:           https://land.copernicus.eu/global/products/ndvi
-    sensor:               VEGETATION-1, VEGETATION-2, VEGETATION
-    source:               Derived from EO satellite imagery
-    time_coverage_end:    2019-12-31T23:59:59Z
-    time_coverage_start:  1999-01-01T00:00:00Z
-    title:                Normalized Difference Vegetation Index: Long Term S...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f3967043-6119-4216-a87c-81b2c04c45f4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f3967043-6119-4216-a87c-81b2c04c45f4' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>INDEX</span>: 6</li><li><span class='xr-has-index'>lat</span>: 15680</li><li><span class='xr-has-index'>lon</span>: 40320</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-59f870bc-cb38-43b9-ad03-50b8b5c011c6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-59f870bc-cb38-43b9-ad03-50b8b5c011c6' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>INDEX</span></div><div class='xr-var-dims'>(INDEX)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5</div><input id='attrs-7d8c9063-c5e2-458a-bbbd-74faa539c3ad' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7d8c9063-c5e2-458a-bbbd-74faa539c3ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac11a6fc-4a92-4c33-9d18-732f53d2f1e6' class='xr-var-data-in' type='checkbox'><label for='data-ac11a6fc-4a92-4c33-9d18-732f53d2f1e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4, 5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.99 79.98 ... -59.98 -59.99</div><input id='attrs-521c0d9b-2865-4d68-9dd6-5462413a059d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-521c0d9b-2865-4d68-9dd6-5462413a059d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6688f1ee-cce0-428a-adce-cd26f49feff1' class='xr-var-data-in' type='checkbox'><label for='data-6688f1ee-cce0-428a-adce-cd26f49feff1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lat</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 80.      ,  79.991071,  79.982143, ..., -59.973214, -59.982143,
-       -59.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-7ad1ed78-4a5c-446d-a45c-16cc3aac653b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ad1ed78-4a5c-446d-a45c-16cc3aac653b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4bc9b01-83bc-49a3-ad7b-8ab7f21c4b07' class='xr-var-data-in' type='checkbox'><label for='data-d4bc9b01-83bc-49a3-ad7b-8ab7f21c4b07' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lon</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-180.      , -179.991071, -179.982143, ...,  179.973214,  179.982143,
-        179.991071])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-13d506f7-b93d-4b5c-b2d9-0b36bb1ccf45' class='xr-section-summary-in' type='checkbox'  checked><label for='section-13d506f7-b93d-4b5c-b2d9-0b36bb1ccf45' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b83b430a-ad86-458f-9eae-8dd4bfe10f62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b83b430a-ad86-458f-9eae-8dd4bfe10f62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c990760-2cc8-4306-9192-8b7ece7b389c' class='xr-var-data-in' type='checkbox'><label for='data-8c990760-2cc8-4306-9192-8b7ece7b389c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GeoTransform :</span></dt><dd>-180.0000000000 0.0089285714 0.0 80.0000000000 0.0 -0.0089285714</dd><dt><span>_CoordinateAxisTypes :</span></dt><dd>GeoX GeoY</dd><dt><span>_CoordinateTransformType :</span></dt><dd>Projection</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>long_name :</span></dt><dd>coordinate reference system</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9108&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=object]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max</span></div><div class='xr-var-dims'>(INDEX, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-10ee5638-89eb-4185-aea6-d12d18b80f82' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-10ee5638-89eb-4185-aea6-d12d18b80f82' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c406c81b-a382-4589-a45f-3fb5009cc3c6' class='xr-var-data-in' type='checkbox'><label for='data-c406c81b-a382-4589-a45f-3fb5009cc3c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: maximum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Maximum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[3793305600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean</span></div><div class='xr-var-dims'>(INDEX, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-24970ffe-9e82-41b6-b33a-190d5550f927' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24970ffe-9e82-41b6-b33a-190d5550f927' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-feab78f0-2360-495a-9ff0-91ac465f3d79' class='xr-var-data-in' type='checkbox'><label for='data-feab78f0-2360-495a-9ff0-91ac465f3d79' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: mean</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Mean Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[3793305600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>median</span></div><div class='xr-var-dims'>(INDEX, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-df1cda8f-0342-4226-901b-a1f3ee187ccf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-df1cda8f-0342-4226-901b-a1f3ee187ccf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-443cfc8e-0c2f-4d96-91b5-8f2ecac3b278' class='xr-var-data-in' type='checkbox'><label for='data-443cfc8e-0c2f-4d96-91b5-8f2ecac3b278' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: median</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Median Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[3793305600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min</span></div><div class='xr-var-dims'>(INDEX, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9bc614d9-5535-4ec2-9bbd-36904ecb881c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9bc614d9-5535-4ec2-9bbd-36904ecb881c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32de3ad8-271a-46fa-881f-6c436215cfd0' class='xr-var-data-in' type='checkbox'><label for='data-32de3ad8-271a-46fa-881f-6c436215cfd0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: minimum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Minimum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[3793305600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nobs</span></div><div class='xr-var-dims'>(INDEX, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b402836b-7732-494c-9b66-0b89ed97ea64' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b402836b-7732-494c-9b66-0b89ed97ea64' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0ae9be0-af13-44e4-81dc-1009eb6ff7a0' class='xr-var-data-in' type='checkbox'><label for='data-d0ae9be0-af13-44e4-81dc-1009eb6ff7a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index number_of_observations</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[1, 250]</dd></dl></div><div class='xr-var-data'><pre>[3793305600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stdev</span></div><div class='xr-var-dims'>(INDEX, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e2425357-458d-45af-8966-3b34641ffdfe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2425357-458d-45af-8966-3b34641ffdfe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-472c38d5-a74c-451a-87e8-f564b4e462f7' class='xr-var-data-in' type='checkbox'><label for='data-472c38d5-a74c-451a-87e8-f564b4e462f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: standard_deviation</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Standard deviation Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[3793305600 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f918e818-6822-4ebf-857f-1888e4a9d450' class='xr-section-summary-in' type='checkbox'  ><label for='section-f918e818-6822-4ebf-857f-1888e4a9d450' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>INDEX</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e3f27f08-6351-4bc8-99ed-ea59a2f8b57a' class='xr-index-data-in' type='checkbox'/><label for='index-e3f27f08-6351-4bc8-99ed-ea59a2f8b57a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3, 4, 5], dtype=&#x27;int64&#x27;, name=&#x27;INDEX&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3b8bc148-ebf5-49b0-ab44-67a24ef59504' class='xr-index-data-in' type='checkbox'/><label for='index-3b8bc148-ebf5-49b0-ab44-67a24ef59504' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               80.0,   79.99107142857143,   79.98214285714286,
-         79.97321428571429,   79.96428571428572,   79.95535714285715,
-         79.94642857142858,   79.93750000000001,   79.92857142857144,
-         79.91964285714288,
-       ...
-       -59.910714285682474,  -59.91964285711106,  -59.92857142853961,
-        -59.93749999996817,  -59.94642857139675, -59.955357142825335,
-        -59.96428571425389, -59.973214285682445,  -59.98214285711103,
-        -59.99107142853961],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=15680))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d6500764-400b-48da-954b-8c1ebf4481df' class='xr-index-data-in' type='checkbox'/><label for='index-d6500764-400b-48da-954b-8c1ebf4481df' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -180.0, -179.99107142857142, -179.98214285714283,
-       -179.97321428571425, -179.96428571428567, -179.95535714285708,
-        -179.9464285714285, -179.93749999999991, -179.92857142857133,
-       -179.91964285714275,
-       ...
-         179.9107142862053,   179.9196428576339,  179.92857142906246,
-          179.937500000491,  179.94642857191963,  179.95535714334824,
-         179.9642857147768,  179.97321428620535,  179.98214285763396,
-        179.99107142906257],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=40320))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f5b4b22b-3fe1-4e20-a5ec-574e00da3c73' class='xr-section-summary-in' type='checkbox'  ><label for='section-f5b4b22b-3fe1-4e20-a5ec-574e00da3c73' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>archive_facility :</span></dt><dd>VITO</dd><dt><span>copyright :</span></dt><dd>Copernicus Service information 2021</dd><dt><span>history :</span></dt><dd>2021-03-01 - Processing line NDVI LTS</dd><dt><span>identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-0701_GLOBE_V3.0.1</dd><dt><span>institution :</span></dt><dd>VITO NV</dd><dt><span>long_name :</span></dt><dd>Normalized Difference Vegetation Index</dd><dt><span>orbit_type :</span></dt><dd>LEO</dd><dt><span>parent_identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all</dd><dt><span>platform :</span></dt><dd>SPOT-4, SPOT-5, Proba-V</dd><dt><span>processing_level :</span></dt><dd>L4</dd><dt><span>processing_mode :</span></dt><dd>Offline</dd><dt><span>product_version :</span></dt><dd>V3.0.1</dd><dt><span>references :</span></dt><dd>https://land.copernicus.eu/global/products/ndvi</dd><dt><span>sensor :</span></dt><dd>VEGETATION-1, VEGETATION-2, VEGETATION</dd><dt><span>source :</span></dt><dd>Derived from EO satellite imagery</dd><dt><span>time_coverage_end :</span></dt><dd>2019-12-31T23:59:59Z</dd><dt><span>time_coverage_start :</span></dt><dd>1999-01-01T00:00:00Z</dd><dt><span>title :</span></dt><dd>Normalized Difference Vegetation Index: Long Term Statistics 1KM: GLOBE 1999-2019 0701</dd></dl></div></li></ul></div></div></div></div>
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-Dimensions:  (INDEX: 6, lat: 15680, lon: 40320)
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-  * INDEX    (INDEX) int64 0 1 2 3 4 5
-  * lat      (lat) float64 80.0 79.99 79.98 79.97 ... -59.97 -59.98 -59.99
-  * lon      (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0
-Data variables:
-    crs      object ...
-    max      (INDEX, lat, lon) float32 ...
-    mean     (INDEX, lat, lon) float32 ...
-    median   (INDEX, lat, lon) float32 ...
-    min      (INDEX, lat, lon) float32 ...
-    nobs     (INDEX, lat, lon) float32 ...
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-Attributes: (12/19)
-    Conventions:          CF-1.6
-    archive_facility:     VITO
-    copyright:            Copernicus Service information 2021
-    history:              2021-03-01 - Processing line NDVI LTS
-    identifier:           urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-0...
-    institution:          VITO NV
-    ...                   ...
-    references:           https://land.copernicus.eu/global/products/ndvi
-    sensor:               VEGETATION-1, VEGETATION-2, VEGETATION
-    source:               Derived from EO satellite imagery
-    time_coverage_end:    2019-12-31T23:59:59Z
-    time_coverage_start:  1999-01-01T00:00:00Z
-    title:                Normalized Difference Vegetation Index: Long Term S...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-a54b116a-10b8-429c-ac20-19fb585c6c6c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a54b116a-10b8-429c-ac20-19fb585c6c6c' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>INDEX</span>: 6</li><li><span class='xr-has-index'>lat</span>: 15680</li><li><span class='xr-has-index'>lon</span>: 40320</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9672efb7-82b7-445a-8168-05b50e03bc03' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9672efb7-82b7-445a-8168-05b50e03bc03' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>INDEX</span></div><div class='xr-var-dims'>(INDEX)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5</div><input id='attrs-388c7d2e-531a-4ddb-a599-c5c0303cae52' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-388c7d2e-531a-4ddb-a599-c5c0303cae52' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-463b604d-7792-407a-bb7b-f263d3afc9af' class='xr-var-data-in' type='checkbox'><label for='data-463b604d-7792-407a-bb7b-f263d3afc9af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4, 5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.99 79.98 ... -59.98 -59.99</div><input id='attrs-222c1b96-9bab-49f0-bb75-24f15cca7102' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-222c1b96-9bab-49f0-bb75-24f15cca7102' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aafe6ee8-cf4a-42cd-9397-87399a690319' class='xr-var-data-in' type='checkbox'><label for='data-aafe6ee8-cf4a-42cd-9397-87399a690319' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lat</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 80.      ,  79.991071,  79.982143, ..., -59.973214, -59.982143,
-       -59.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-d04f27f2-a32d-450f-b760-d30d4bab9e1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d04f27f2-a32d-450f-b760-d30d4bab9e1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8fef0bf1-89a2-4d84-9601-f89899a4b713' class='xr-var-data-in' type='checkbox'><label for='data-8fef0bf1-89a2-4d84-9601-f89899a4b713' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lon</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-180.      , -179.991071, -179.982143, ...,  179.973214,  179.982143,
-        179.991071])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5bc2ac80-65d7-442f-9755-8719176794c1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5bc2ac80-65d7-442f-9755-8719176794c1' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-156f2a2e-848b-40a9-adb0-68e0cbfc8c50' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-156f2a2e-848b-40a9-adb0-68e0cbfc8c50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8f9a0cc-1ed4-47de-a40d-9033d2df073f' class='xr-var-data-in' type='checkbox'><label for='data-f8f9a0cc-1ed4-47de-a40d-9033d2df073f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GeoTransform :</span></dt><dd>-180.0000000000 0.0089285714 0.0 80.0000000000 0.0 -0.0089285714</dd><dt><span>_CoordinateAxisTypes :</span></dt><dd>GeoX GeoY</dd><dt><span>_CoordinateTransformType :</span></dt><dd>Projection</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>long_name :</span></dt><dd>coordinate reference system</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9108&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=object]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max</span></div><div class='xr-var-dims'>(INDEX, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-faae6703-a37e-4ed0-acdd-fe3375129a4b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-faae6703-a37e-4ed0-acdd-fe3375129a4b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ae161c6-d5b2-44ec-83ca-070101c2af09' class='xr-var-data-in' type='checkbox'><label for='data-5ae161c6-d5b2-44ec-83ca-070101c2af09' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: maximum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Maximum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[3793305600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean</span></div><div class='xr-var-dims'>(INDEX, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d567c0d3-4364-43a1-a078-edd7cf6b1032' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d567c0d3-4364-43a1-a078-edd7cf6b1032' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41fde5a0-2a4e-4eca-9618-80593ee7c7e8' class='xr-var-data-in' type='checkbox'><label for='data-41fde5a0-2a4e-4eca-9618-80593ee7c7e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: mean</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Mean Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[3793305600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>median</span></div><div class='xr-var-dims'>(INDEX, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-23a392cc-3e96-4e76-8dca-18abb9e837ca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-23a392cc-3e96-4e76-8dca-18abb9e837ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6436c05-c133-4f60-83bb-050f026e5846' class='xr-var-data-in' type='checkbox'><label for='data-c6436c05-c133-4f60-83bb-050f026e5846' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: median</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Median Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[3793305600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min</span></div><div class='xr-var-dims'>(INDEX, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-72287eef-9651-47eb-a5d5-2f4808fd2088' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-72287eef-9651-47eb-a5d5-2f4808fd2088' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10c3a1df-2bd0-4338-a4fa-ebbeb1f79700' class='xr-var-data-in' type='checkbox'><label for='data-10c3a1df-2bd0-4338-a4fa-ebbeb1f79700' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: minimum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Minimum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[3793305600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nobs</span></div><div class='xr-var-dims'>(INDEX, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cf35d9ad-08f3-4b4a-b14d-336c703c0dee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cf35d9ad-08f3-4b4a-b14d-336c703c0dee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8fe98ce-8662-4c76-a539-c567b410dcdd' class='xr-var-data-in' type='checkbox'><label for='data-b8fe98ce-8662-4c76-a539-c567b410dcdd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index number_of_observations</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[1, 250]</dd></dl></div><div class='xr-var-data'><pre>[3793305600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stdev</span></div><div class='xr-var-dims'>(INDEX, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0174bd55-111f-4a98-9f9e-a06579cfb872' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0174bd55-111f-4a98-9f9e-a06579cfb872' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc75e237-b5c9-426e-8eb0-b3f09715c7b3' class='xr-var-data-in' type='checkbox'><label for='data-fc75e237-b5c9-426e-8eb0-b3f09715c7b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: standard_deviation</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Standard deviation Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[3793305600 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8dadb9e1-51f2-47df-a005-6c7e982fd66b' class='xr-section-summary-in' type='checkbox'  ><label for='section-8dadb9e1-51f2-47df-a005-6c7e982fd66b' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>INDEX</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9d37f643-c1f4-49f5-95e5-89a528d6f57c' class='xr-index-data-in' type='checkbox'/><label for='index-9d37f643-c1f4-49f5-95e5-89a528d6f57c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3, 4, 5], dtype=&#x27;int64&#x27;, name=&#x27;INDEX&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6a85f894-5a9a-416c-9854-ca4c48ea1e50' class='xr-index-data-in' type='checkbox'/><label for='index-6a85f894-5a9a-416c-9854-ca4c48ea1e50' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               80.0,   79.99107142857143,   79.98214285714286,
-         79.97321428571429,   79.96428571428572,   79.95535714285715,
-         79.94642857142858,   79.93750000000001,   79.92857142857144,
-         79.91964285714288,
-       ...
-       -59.910714285682474,  -59.91964285711106,  -59.92857142853961,
-        -59.93749999996817,  -59.94642857139675, -59.955357142825335,
-        -59.96428571425389, -59.973214285682445,  -59.98214285711103,
-        -59.99107142853961],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=15680))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1911c77d-0bc7-490b-b8a3-d359e098efd7' class='xr-index-data-in' type='checkbox'/><label for='index-1911c77d-0bc7-490b-b8a3-d359e098efd7' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -180.0, -179.99107142857142, -179.98214285714283,
-       -179.97321428571425, -179.96428571428567, -179.95535714285708,
-        -179.9464285714285, -179.93749999999991, -179.92857142857133,
-       -179.91964285714275,
-       ...
-         179.9107142862053,   179.9196428576339,  179.92857142906246,
-          179.937500000491,  179.94642857191963,  179.95535714334824,
-         179.9642857147768,  179.97321428620535,  179.98214285763396,
-        179.99107142906257],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=40320))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-59f47819-9f15-404b-ba49-b83f683b7839' class='xr-section-summary-in' type='checkbox'  ><label for='section-59f47819-9f15-404b-ba49-b83f683b7839' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>archive_facility :</span></dt><dd>VITO</dd><dt><span>copyright :</span></dt><dd>Copernicus Service information 2021</dd><dt><span>history :</span></dt><dd>2021-03-01 - Processing line NDVI LTS</dd><dt><span>identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-0701_GLOBE_V3.0.1</dd><dt><span>institution :</span></dt><dd>VITO NV</dd><dt><span>long_name :</span></dt><dd>Normalized Difference Vegetation Index</dd><dt><span>orbit_type :</span></dt><dd>LEO</dd><dt><span>parent_identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all</dd><dt><span>platform :</span></dt><dd>SPOT-4, SPOT-5, Proba-V</dd><dt><span>processing_level :</span></dt><dd>L4</dd><dt><span>processing_mode :</span></dt><dd>Offline</dd><dt><span>product_version :</span></dt><dd>V3.0.1</dd><dt><span>references :</span></dt><dd>https://land.copernicus.eu/global/products/ndvi</dd><dt><span>sensor :</span></dt><dd>VEGETATION-1, VEGETATION-2, VEGETATION</dd><dt><span>source :</span></dt><dd>Derived from EO satellite imagery</dd><dt><span>time_coverage_end :</span></dt><dd>2019-12-31T23:59:59Z</dd><dt><span>time_coverage_start :</span></dt><dd>1999-01-01T00:00:00Z</dd><dt><span>title :</span></dt><dd>Normalized Difference Vegetation Index: Long Term Statistics 1KM: GLOBE 1999-2019 0701</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <p>The catalog (json file we created) can be shared on the cloud (or GitHub, etc.) and anyone can load it from there too.
 This approach allows anyone to easily access LTS data and select the Area of Interest for their own study.</p>
@@ -8019,427 +1225,20 @@ <h3>Combine all LTS files into one kerchunked single ensemble dataset<a class="h
 </pre></div>
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-</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;
-Dimensions:  (lat: 15680, lon: 40320, time: 36)
-Coordinates:
-  * lat      (lat) float64 80.0 79.99 79.98 79.97 ... -59.97 -59.98 -59.99
-  * lon      (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0
-  * time     (time) float64 nan 1.0 2.0 3.0 4.0 5.0 ... 31.0 32.0 33.0 34.0 35.0
-Data variables:
-    crs      object ...
-    max      (time, lat, lon) float32 ...
-    mean     (time, lat, lon) float32 ...
-    median   (time, lat, lon) float32 ...
-    min      (time, lat, lon) float32 ...
-    nobs     (time, lat, lon) float32 ...
-    stdev    (time, lat, lon) float32 ...
-Attributes: (12/19)
-    Conventions:          CF-1.6
-    archive_facility:     VITO
-    copyright:            Copernicus Service information 2021
-    history:              2021-03-01 - Processing line NDVI LTS
-    identifier:           urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-0...
-    institution:          VITO NV
-    ...                   ...
-    references:           https://land.copernicus.eu/global/products/ndvi
-    sensor:               VEGETATION-1, VEGETATION-2, VEGETATION
-    source:               Derived from EO satellite imagery
-    time_coverage_end:    2019-12-31T23:59:59Z
-    time_coverage_start:  1999-01-01T00:00:00Z
-    title:                Normalized Difference Vegetation Index: Long Term S...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6b6bf06b-3738-4c0b-b93f-c3701932b503' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6b6bf06b-3738-4c0b-b93f-c3701932b503' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 15680</li><li><span class='xr-has-index'>lon</span>: 40320</li><li><span class='xr-has-index'>time</span>: 36</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-0ff78400-0509-457e-80e2-dac8d77d707d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0ff78400-0509-457e-80e2-dac8d77d707d' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.99 79.98 ... -59.98 -59.99</div><input id='attrs-eeb9c4dc-5a32-45bd-826c-3b8ddec9e867' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eeb9c4dc-5a32-45bd-826c-3b8ddec9e867' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a7a8949-0b02-4e31-a9d3-9ae54d103803' class='xr-var-data-in' type='checkbox'><label for='data-1a7a8949-0b02-4e31-a9d3-9ae54d103803' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lat</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 80.      ,  79.991071,  79.982143, ..., -59.973214, -59.982143,
-       -59.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-d41f697d-31ec-4fad-828f-3559bc9982bf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d41f697d-31ec-4fad-828f-3559bc9982bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab496623-9396-4897-b308-15c66fafcbab' class='xr-var-data-in' type='checkbox'><label for='data-ab496623-9396-4897-b308-15c66fafcbab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lon</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-180.      , -179.991071, -179.982143, ...,  179.973214,  179.982143,
-        179.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan 1.0 2.0 3.0 ... 33.0 34.0 35.0</div><input id='attrs-b6838d4e-e517-4871-8423-0cd2f6bbfb88' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b6838d4e-e517-4871-8423-0cd2f6bbfb88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be1d1770-c836-40a0-ab7a-0e77f84fa93e' class='xr-var-data-in' type='checkbox'><label for='data-be1d1770-c836-40a0-ab7a-0e77f84fa93e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan,  1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 13.,
-       14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27.,
-       28., 29., 30., 31., 32., 33., 34., 35.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1bec2bdf-8eed-42e7-a3b3-b1604e11b23a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1bec2bdf-8eed-42e7-a3b3-b1604e11b23a' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-de1ca6e3-6c7e-41f2-9987-a96ae0101a50' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-de1ca6e3-6c7e-41f2-9987-a96ae0101a50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d3126cf-d7bc-4d16-8805-79948d7ab360' class='xr-var-data-in' type='checkbox'><label for='data-7d3126cf-d7bc-4d16-8805-79948d7ab360' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GeoTransform :</span></dt><dd>-180.0000000000 0.0089285714 0.0 80.0000000000 0.0 -0.0089285714</dd><dt><span>_CoordinateAxisTypes :</span></dt><dd>GeoX GeoY</dd><dt><span>_CoordinateTransformType :</span></dt><dd>Projection</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>long_name :</span></dt><dd>coordinate reference system</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9108&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=object]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6a1da1e5-be8d-4708-820a-bced9da8e982' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a1da1e5-be8d-4708-820a-bced9da8e982' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46aa6635-2706-409c-bcc6-721a7b001d09' class='xr-var-data-in' type='checkbox'><label for='data-46aa6635-2706-409c-bcc6-721a7b001d09' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: maximum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Maximum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[22759833600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9a0ba404-832a-4e65-b917-5ecc8d95a165' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a0ba404-832a-4e65-b917-5ecc8d95a165' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa71c1ce-9e27-46b9-960d-fb46fdb11d3d' class='xr-var-data-in' type='checkbox'><label for='data-fa71c1ce-9e27-46b9-960d-fb46fdb11d3d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: mean</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Mean Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[22759833600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>median</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3a4186a3-e694-4940-8641-3044c8644689' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a4186a3-e694-4940-8641-3044c8644689' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9b9980a-3948-4728-8244-69f6de3b2cdc' class='xr-var-data-in' type='checkbox'><label for='data-c9b9980a-3948-4728-8244-69f6de3b2cdc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: median</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Median Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[22759833600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9c6f743d-a7fe-4a4b-8ba1-818befc4a3a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c6f743d-a7fe-4a4b-8ba1-818befc4a3a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-544c6a7c-4c77-4803-9298-cc68797e1e60' class='xr-var-data-in' type='checkbox'><label for='data-544c6a7c-4c77-4803-9298-cc68797e1e60' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: minimum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Minimum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[22759833600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nobs</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-35579718-36ad-40a6-a88a-2932f6d727a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-35579718-36ad-40a6-a88a-2932f6d727a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d90d117-48f3-4e1e-9298-7ce494850607' class='xr-var-data-in' type='checkbox'><label for='data-0d90d117-48f3-4e1e-9298-7ce494850607' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index number_of_observations</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[1, 250]</dd></dl></div><div class='xr-var-data'><pre>[22759833600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stdev</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f29b826c-d761-49a9-944d-da71e8a0bc48' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f29b826c-d761-49a9-944d-da71e8a0bc48' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-917ec893-9a00-40a7-8363-438497ee1687' class='xr-var-data-in' type='checkbox'><label for='data-917ec893-9a00-40a7-8363-438497ee1687' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: standard_deviation</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Standard deviation Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><pre>[22759833600 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7b645f8c-63db-4037-964a-3dd4b0a13c28' class='xr-section-summary-in' type='checkbox'  ><label for='section-7b645f8c-63db-4037-964a-3dd4b0a13c28' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ac72d52f-6dbc-435b-8091-42acc0041b23' class='xr-index-data-in' type='checkbox'/><label for='index-ac72d52f-6dbc-435b-8091-42acc0041b23' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               80.0,   79.99107142857143,   79.98214285714286,
-         79.97321428571429,   79.96428571428572,   79.95535714285715,
-         79.94642857142858,   79.93750000000001,   79.92857142857144,
-         79.91964285714288,
-       ...
-       -59.910714285682474,  -59.91964285711106,  -59.92857142853961,
-        -59.93749999996817,  -59.94642857139675, -59.955357142825335,
-        -59.96428571425389, -59.973214285682445,  -59.98214285711103,
-        -59.99107142853961],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=15680))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6be88692-d7d3-463a-ad5e-b4f8dc7f1c24' class='xr-index-data-in' type='checkbox'/><label for='index-6be88692-d7d3-463a-ad5e-b4f8dc7f1c24' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -180.0, -179.99107142857142, -179.98214285714283,
-       -179.97321428571425, -179.96428571428567, -179.95535714285708,
-        -179.9464285714285, -179.93749999999991, -179.92857142857133,
-       -179.91964285714275,
-       ...
-         179.9107142862053,   179.9196428576339,  179.92857142906246,
-          179.937500000491,  179.94642857191963,  179.95535714334824,
-         179.9642857147768,  179.97321428620535,  179.98214285763396,
-        179.99107142906257],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=40320))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-17237445-40e6-4d5c-a277-6a1400ff899e' class='xr-index-data-in' type='checkbox'/><label for='index-17237445-40e6-4d5c-a277-6a1400ff899e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ nan,  1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,  9.0, 10.0, 11.0,
-       12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0,
-       24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0, 32.0, 33.0, 34.0, 35.0],
-      dtype=&#x27;float64&#x27;, name=&#x27;time&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d17af476-9b22-493a-91d2-1ed5c1b3c795' class='xr-section-summary-in' type='checkbox'  ><label for='section-d17af476-9b22-493a-91d2-1ed5c1b3c795' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>archive_facility :</span></dt><dd>VITO</dd><dt><span>copyright :</span></dt><dd>Copernicus Service information 2021</dd><dt><span>history :</span></dt><dd>2021-03-01 - Processing line NDVI LTS</dd><dt><span>identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-0101_GLOBE_V3.0.1</dd><dt><span>institution :</span></dt><dd>VITO NV</dd><dt><span>long_name :</span></dt><dd>Normalized Difference Vegetation Index</dd><dt><span>orbit_type :</span></dt><dd>LEO</dd><dt><span>parent_identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all</dd><dt><span>platform :</span></dt><dd>SPOT-4, SPOT-5, Proba-V</dd><dt><span>processing_level :</span></dt><dd>L4</dd><dt><span>processing_mode :</span></dt><dd>Offline</dd><dt><span>product_version :</span></dt><dd>V3.0.1</dd><dt><span>references :</span></dt><dd>https://land.copernicus.eu/global/products/ndvi</dd><dt><span>sensor :</span></dt><dd>VEGETATION-1, VEGETATION-2, VEGETATION</dd><dt><span>source :</span></dt><dd>Derived from EO satellite imagery</dd><dt><span>time_coverage_end :</span></dt><dd>2019-12-31T23:59:59Z</dd><dt><span>time_coverage_start :</span></dt><dd>1999-01-01T00:00:00Z</dd><dt><span>title :</span></dt><dd>Normalized Difference Vegetation Index: Long Term Statistics 1KM: GLOBE 1999-2019 0101</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <p>We will use this catalogue in <span class="xref myst">dask_introduction</span> chapter.</p>
 </section>
 </section>
+<section id="operations-on-a-chunked-dataset">
+<h2>Operations on a chunked dataset<a class="headerlink" href="#operations-on-a-chunked-dataset" title="Permalink to this heading">#</a></h2>
+<p>Let’s have a look of our chunked test dataset backend representation.</p>
+<p><code class="docutils literal notranslate"> <span class="pre">test.data</span></code> is the backend array Python representation of Xarray’s Data Array, <a class="reference external" href="https://docs.dask.org/en/stable/array.html"><strong>Dask Array</strong></a> when using chunking, Numpy by default.</p>
+<p>We will introduce Dask arrays and Dask graphs visualization in the next section <span class="xref myst">dask_introduction</span>.</p>
+<p>Anyway, when applying <code class="docutils literal notranslate"><span class="pre">chunk</span></code> function you may have the impression that the chunks sizes just changes and everything will be fine.</p>
+<p>However, as you can see in the graph visualization above, Xarray will actually have to fetch at least one entire initial chunk that was defined when opening the Dataset at first before rechunking at a smaller size or even selecting one value. This is true when applying any funtions on any values: Xarray will work by loading entire chunks.</p>
+<p>You can imagine that it will not be very optimal if you load one file as an entire chunk, or if your initial chunks are too big (your Python Jupyter kernel may crash!), especially with large numbers of files and large files. Choosing an appropriate chunk size is really important and depends on your analysis.</p>
+<p>You can find a really nice article by Dask team on how to chose the right chunk size <a class="reference external" href="https://blog.dask.org/2021/11/02/choosing-dask-chunk-sizes">here</a>.</p>
+</section>
 <section id="conclusion">
 <h2>Conclusion<a class="headerlink" href="#conclusion" title="Permalink to this heading">#</a></h2>
 <p>Understanding chunking is key to optimize your data analysis when dealing with big datasets. In this episode we learned how to optimize the data access time and memory resources by exploiting native file chunks from netCDF4 data files and instructing Xarray to access data per chunk. However, computations on big datasets can be very slow on a single computer, and to optimize its time we may need to parallelize your computations. This is what you will learn in the next episode with Dask.</p>
@@ -8558,21 +1357,29 @@ <h2>Packages citation<a class="headerlink" href="#packages-citation" title="Perm
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#packages">Packages</a></li>
 </ul>
 </li>
-<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#global-lts">Global LTS</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#title-here">title here</a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#what-is-a-chunk">What is a <strong>chunk</strong></a></li>
-<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#using-chunks-within-a-single-file">Using chunks within a single file</a></li>
-<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#operations-on-a-chunked-dataset">Operations on a chunked dataset</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#modifying-chunks">Modifying chunks</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#defining-the-chunk-at-the-creatioin-of-xarray">Defining the chunk at the creatioin of Xarray</a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#so-why-chunks">So, why chunks?</a><ul class="nav section-nav flex-column">
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#chunks-and-files">Chunks and files</a></li>
 </ul>
 </li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#zarr-storage-format">Zarr storage format</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#load-data-using-stackstac-with-specific-chunk">Load data using stackstac (with specific chunk)</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#coomputing-snow-index">Coomputing Snow index</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#clip-the-data">Clip the data</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#lets-save-the-intermediate-result-of-a-few-days-in-a-zarr-format">Lets save the intermediate result of a few days in a zarr format</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#before-saving-we-clean-the-chunk-size-clean-attribute-and-save-the-data-in-xarray-dataset-format">Before saving, we clean the chunk size, clean attribute and save the data in Xarray DataSet format</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#load-the-temporaly-data-saved-as-zarr-back-to-xarray">Load the temporaly data saved as zarr back to Xarray</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#group-by-to-a-day-and-plot-the-results">Group by to a day, and plot the results</a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#opening-multiple-netcdf-files-and-kerchunk">Opening multiple NetCDF files and Kerchunk</a><ul class="nav section-nav flex-column">
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#exploiting-native-file-chunks-for-reading-datasets">Exploiting native file chunks for reading datasets</a></li>
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#extract-chunk-information">Extract chunk information</a></li>
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#combine-all-lts-files-into-one-kerchunked-single-ensemble-dataset">Combine all LTS files into one kerchunked single ensemble dataset</a></li>
 </ul>
 </li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#operations-on-a-chunked-dataset">Operations on a chunked dataset</a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#conclusion">Conclusion</a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#packages-citation">Packages citation</a></li>
 </ul>
diff --git a/part3/data_exploitability_pangeo.html b/part3/data_exploitability_pangeo.html
index 2da5b98..cc29c6a 100644
--- a/part3/data_exploitability_pangeo.html
+++ b/part3/data_exploitability_pangeo.html
@@ -1100,7 +1100,7 @@ <h3>Import libraries<a class="headerlink" href="#import-libraries" title="Permal
     <div style="width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;"> </div>
     <div style="margin-left: 48px;">
         <h3 style="margin-bottom: 0px;">Client</h3>
-        <p style="color: #9D9D9D; margin-bottom: 0px;">Client-13a5a6af-7802-11ee-8e86-000d3ae50e51</p>
+        <p style="color: #9D9D9D; margin-bottom: 0px;">Client-edaff6c9-7807-11ee-8ef1-002248352ce8</p>
         <table style="width: 100%; text-align: left;">
 
         <tr>
@@ -1135,7 +1135,7 @@ <h3 style="margin-bottom: 0px;">Client</h3>
     </div>
     <div style="margin-left: 48px;">
         <h3 style="margin-bottom: 0px; margin-top: 0px;">LocalCluster</h3>
-        <p style="color: #9D9D9D; margin-bottom: 0px;">34936e63</p>
+        <p style="color: #9D9D9D; margin-bottom: 0px;">b7c274aa</p>
         <table style="width: 100%; text-align: left;">
             <tr>
                 <td style="text-align: left;">
@@ -1172,11 +1172,11 @@ <h3 style="display: inline;">Scheduler Info</h3>
         <div style="width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;"> </div>
         <div style="margin-left: 48px;">
             <h3 style="margin-bottom: 0px;">Scheduler</h3>
-            <p style="color: #9D9D9D; margin-bottom: 0px;">Scheduler-68489d21-2ff0-432e-af6d-08835991d0a1</p>
+            <p style="color: #9D9D9D; margin-bottom: 0px;">Scheduler-96c2e906-39d5-4c32-b5f3-bbe085230c15</p>
             <table style="width: 100%; text-align: left;">
                 <tr>
                     <td style="text-align: left;">
-                        <strong>Comm:</strong> tcp://127.0.0.1:37291
+                        <strong>Comm:</strong> tcp://127.0.0.1:34541
                     </td>
                     <td style="text-align: left;">
                         <strong>Workers:</strong> 2
@@ -1218,7 +1218,7 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 0</h4>
                 <table style="width: 100%; text-align: left;">
                     <tr>
                         <td style="text-align: left;">
-                            <strong>Comm: </strong> tcp://127.0.0.1:43833
+                            <strong>Comm: </strong> tcp://127.0.0.1:37157
                         </td>
                         <td style="text-align: left;">
                             <strong>Total threads: </strong> 1
@@ -1226,7 +1226,7 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 0</h4>
                     </tr>
                     <tr>
                         <td style="text-align: left;">
-                            <strong>Dashboard: </strong> <a href="http://127.0.0.1:35453/status" target="_blank">http://127.0.0.1:35453/status</a>
+                            <strong>Dashboard: </strong> <a href="http://127.0.0.1:36441/status" target="_blank">http://127.0.0.1:36441/status</a>
                         </td>
                         <td style="text-align: left;">
                             <strong>Memory: </strong> 3.38 GiB
@@ -1234,13 +1234,13 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 0</h4>
                     </tr>
                     <tr>
                         <td style="text-align: left;">
-                            <strong>Nanny: </strong> tcp://127.0.0.1:32889
+                            <strong>Nanny: </strong> tcp://127.0.0.1:45265
                         </td>
                         <td style="text-align: left;"></td>
                     </tr>
                     <tr>
                         <td colspan="2" style="text-align: left;">
-                            <strong>Local directory: </strong> /tmp/dask-scratch-space/worker-pef2v7g6
+                            <strong>Local directory: </strong> /tmp/dask-scratch-space/worker-4rq4mjpx
                         </td>
                     </tr>
 
@@ -1263,7 +1263,7 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 1</h4>
                 <table style="width: 100%; text-align: left;">
                     <tr>
                         <td style="text-align: left;">
-                            <strong>Comm: </strong> tcp://127.0.0.1:46063
+                            <strong>Comm: </strong> tcp://127.0.0.1:38709
                         </td>
                         <td style="text-align: left;">
                             <strong>Total threads: </strong> 1
@@ -1271,7 +1271,7 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 1</h4>
                     </tr>
                     <tr>
                         <td style="text-align: left;">
-                            <strong>Dashboard: </strong> <a href="http://127.0.0.1:40309/status" target="_blank">http://127.0.0.1:40309/status</a>
+                            <strong>Dashboard: </strong> <a href="http://127.0.0.1:40257/status" target="_blank">http://127.0.0.1:40257/status</a>
                         </td>
                         <td style="text-align: left;">
                             <strong>Memory: </strong> 3.38 GiB
@@ -1279,13 +1279,13 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 1</h4>
                     </tr>
                     <tr>
                         <td style="text-align: left;">
-                            <strong>Nanny: </strong> tcp://127.0.0.1:32869
+                            <strong>Nanny: </strong> tcp://127.0.0.1:41953
                         </td>
                         <td style="text-align: left;"></td>
                     </tr>
                     <tr>
                         <td colspan="2" style="text-align: left;">
-                            <strong>Local directory: </strong> /tmp/dask-scratch-space/worker-omfk_kjm
+                            <strong>Local directory: </strong> /tmp/dask-scratch-space/worker-th2368qu
                         </td>
                     </tr>
 
diff --git a/part3/scaling_dask.html b/part3/scaling_dask.html
index db58033..3fbdd79 100644
--- a/part3/scaling_dask.html
+++ b/part3/scaling_dask.html
@@ -556,10 +556,10 @@ <h3>Contributors<a class="headerlink" href="#contributors" title="Permalink to t
 </section>
 <section id="context">
 <h2>Context<a class="headerlink" href="#context" title="Permalink to this heading">#</a></h2>
-<p>We will be using <a class="reference external" href="https://docs.dask.org/">Dask</a> with <a class="reference external" href="https://docs.xarray.dev/en/stable/">Xarray</a> to parallelize our data analysis. The analysis is very similar to what we have done in previous episodes but this time we will use data on a global coverage that we read from a shared catalog (stored online in the Pangeo EOSC Openstack Object Storage).</p>
+<p>We will be using <a class="reference external" href="https://docs.dask.org/">Dask</a> with <a class="reference external" href="https://docs.xarray.dev/en/stable/">Xarray</a> to parallelize our data analysis.  We continue to use the snow index example.</p>
 <section id="data">
 <h3>Data<a class="headerlink" href="#data" title="Permalink to this heading">#</a></h3>
-<p>In this episode, we will be using Global Long Term Statistics (1999-2019) product provided by the <a class="reference external" href="https://land.copernicus.eu/global/index.html">Copernicus Global Land Service over Lombardia</a> and access them through <a class="reference external" href="https://en.wikipedia.org/wiki/Amazon_S3">S3-comptabile storage</a> (<a class="reference external" href="https://wiki.openstack.org/wiki/Swift">OpenStack Object Storage “Swift”</a>) with a data catalog we have created and made publicly available.</p>
+<p>In this episode, we will be using xxx</p>
 </section>
 </section>
 <section id="setup">
@@ -652,7 +652,7 @@ <h3>Dask distributed Client<a class="headerlink" href="#dask-distributed-client"
     <div style="width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;"> </div>
     <div style="margin-left: 48px;">
         <h3 style="margin-bottom: 0px;">Client</h3>
-        <p style="color: #9D9D9D; margin-bottom: 0px;">Client-167fc368-7802-11ee-8ebb-000d3ae50e51</p>
+        <p style="color: #9D9D9D; margin-bottom: 0px;">Client-f067bffd-7807-11ee-8f27-002248352ce8</p>
         <table style="width: 100%; text-align: left;">
 
         <tr>
@@ -687,7 +687,7 @@ <h3 style="margin-bottom: 0px;">Client</h3>
     </div>
     <div style="margin-left: 48px;">
         <h3 style="margin-bottom: 0px; margin-top: 0px;">LocalCluster</h3>
-        <p style="color: #9D9D9D; margin-bottom: 0px;">7b7ee630</p>
+        <p style="color: #9D9D9D; margin-bottom: 0px;">f6ec83ae</p>
         <table style="width: 100%; text-align: left;">
             <tr>
                 <td style="text-align: left;">
@@ -724,11 +724,11 @@ <h3 style="display: inline;">Scheduler Info</h3>
         <div style="width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;"> </div>
         <div style="margin-left: 48px;">
             <h3 style="margin-bottom: 0px;">Scheduler</h3>
-            <p style="color: #9D9D9D; margin-bottom: 0px;">Scheduler-22629aad-d055-4d0e-90bf-2ff24f230f09</p>
+            <p style="color: #9D9D9D; margin-bottom: 0px;">Scheduler-2c0285da-fe0c-45db-9fff-65741d02495c</p>
             <table style="width: 100%; text-align: left;">
                 <tr>
                     <td style="text-align: left;">
-                        <strong>Comm:</strong> tcp://127.0.0.1:35241
+                        <strong>Comm:</strong> tcp://127.0.0.1:38551
                     </td>
                     <td style="text-align: left;">
                         <strong>Workers:</strong> 2
@@ -770,7 +770,7 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 0</h4>
                 <table style="width: 100%; text-align: left;">
                     <tr>
                         <td style="text-align: left;">
-                            <strong>Comm: </strong> tcp://127.0.0.1:43425
+                            <strong>Comm: </strong> tcp://127.0.0.1:43451
                         </td>
                         <td style="text-align: left;">
                             <strong>Total threads: </strong> 1
@@ -778,7 +778,7 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 0</h4>
                     </tr>
                     <tr>
                         <td style="text-align: left;">
-                            <strong>Dashboard: </strong> <a href="http://127.0.0.1:42109/status" target="_blank">http://127.0.0.1:42109/status</a>
+                            <strong>Dashboard: </strong> <a href="http://127.0.0.1:43647/status" target="_blank">http://127.0.0.1:43647/status</a>
                         </td>
                         <td style="text-align: left;">
                             <strong>Memory: </strong> 3.38 GiB
@@ -786,13 +786,13 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 0</h4>
                     </tr>
                     <tr>
                         <td style="text-align: left;">
-                            <strong>Nanny: </strong> tcp://127.0.0.1:33769
+                            <strong>Nanny: </strong> tcp://127.0.0.1:32953
                         </td>
                         <td style="text-align: left;"></td>
                     </tr>
                     <tr>
                         <td colspan="2" style="text-align: left;">
-                            <strong>Local directory: </strong> /tmp/dask-scratch-space/worker-pic4d6yl
+                            <strong>Local directory: </strong> /tmp/dask-scratch-space/worker-n_y_bw4o
                         </td>
                     </tr>
 
@@ -815,7 +815,7 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 1</h4>
                 <table style="width: 100%; text-align: left;">
                     <tr>
                         <td style="text-align: left;">
-                            <strong>Comm: </strong> tcp://127.0.0.1:38947
+                            <strong>Comm: </strong> tcp://127.0.0.1:32881
                         </td>
                         <td style="text-align: left;">
                             <strong>Total threads: </strong> 1
@@ -823,7 +823,7 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 1</h4>
                     </tr>
                     <tr>
                         <td style="text-align: left;">
-                            <strong>Dashboard: </strong> <a href="http://127.0.0.1:40579/status" target="_blank">http://127.0.0.1:40579/status</a>
+                            <strong>Dashboard: </strong> <a href="http://127.0.0.1:34921/status" target="_blank">http://127.0.0.1:34921/status</a>
                         </td>
                         <td style="text-align: left;">
                             <strong>Memory: </strong> 3.38 GiB
@@ -831,13 +831,13 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 1</h4>
                     </tr>
                     <tr>
                         <td style="text-align: left;">
-                            <strong>Nanny: </strong> tcp://127.0.0.1:40875
+                            <strong>Nanny: </strong> tcp://127.0.0.1:45839
                         </td>
                         <td style="text-align: left;"></td>
                     </tr>
                     <tr>
                         <td colspan="2" style="text-align: left;">
-                            <strong>Local directory: </strong> /tmp/dask-scratch-space/worker-44b_mftm
+                            <strong>Local directory: </strong> /tmp/dask-scratch-space/worker-bsn8wvdp
                         </td>
                     </tr>
 
@@ -877,13 +877,14 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 1</h4>
 </div></section>
 <section id="dask-dashboard">
 <h3>Dask Dashboard<a class="headerlink" href="#dask-dashboard" title="Permalink to this heading">#</a></h3>
-<p>Dask comes with a really handy interface: the Dask Dashboard. It is a web interface that you can open in a separated tab of your browser (but not with he link above, you’ve got to use Jupyterlabs proxy: <a class="reference external" href="https://pangeo-foss4g.vm.fedcloud.eu/jupyterhub/user/">https://pangeo-foss4g.vm.fedcloud.eu/jupyterhub/user/</a><em>yourusername</em>/proxy/8787/status).</p>
+<p>Dask comes with a really handy interface: the Dask Dashboard. It is a web interface that you can open in a separated tab of your browser (but not with he link above, you’ve got to use Jupyterlabs proxy: /user/todaka/proxy/8787/status).</p>
 <p>We will learn here how to use it through <a class="reference external" href="https://github.com/dask/dask-labextension">dask jupyterlab extension</a>.</p>
-<p>To use Dask Dashboard through jupyterlab extension on Pangeo EOSC FOSS4G infrastructure,
+<p>To use Dask Dashboard through jupyterlab extension on Pangeo EOSC infrastructure,
 you will just need too look at the html link you have for your jupyterlab, and Dask dashboard port number, as highlighted in the figure below.</p>
 <img src="../figures/dashboardlink.png" width="50%">
-<img src="../figures/dasklab.png" width="30%">
-<p>Then click the orange icon indicated in the above figure, and type ‘your’ dashboard link (normally, you just need to replace ‘todaka’ to ‘your username’).</p>
+<img src="../figures/dasklab.png" width="80%">
+<p>Then click the orange icon indicated in the above figure, and type ‘your’ dashboard link (normally, you just need to replace ‘todaka’ to ‘your username’).<br />
+<img src="../figures/daskclick.png" width="30%"></p>
 <p>You can click several buttons indicated with blue arrows in above figures, then drag and drop to place them as your convenience.</p>
 <img src="../figures/exampledasklab.png" width="50%">
 <p>It’s really helpfull to understand your computation and how it is distributed.</p>
@@ -1306,11 +1307,11 @@ <h3>Read from online kerchunked consolidated dataset<a class="headerlink" href="
     source:               Derived from EO satellite imagery
     time_coverage_end:    2019-12-31T23:59:59Z
     time_coverage_start:  1999-01-01T00:00:00Z
-    title:                Normalized Difference Vegetation Index: Long Term S...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-56a7f866-818c-4fc9-9185-169cbb55d6aa' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-56a7f866-818c-4fc9-9185-169cbb55d6aa' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 15680</li><li><span class='xr-has-index'>lon</span>: 40320</li><li><span class='xr-has-index'>time</span>: 36</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-241f32d0-f514-4455-a03b-fdbce41d5987' class='xr-section-summary-in' type='checkbox'  checked><label for='section-241f32d0-f514-4455-a03b-fdbce41d5987' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.99 79.98 ... -59.98 -59.99</div><input id='attrs-9dea4619-eda1-4d42-9432-7acbc7416ab1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9dea4619-eda1-4d42-9432-7acbc7416ab1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd840949-30cf-4130-8b05-edcd8f3c37e3' class='xr-var-data-in' type='checkbox'><label for='data-bd840949-30cf-4130-8b05-edcd8f3c37e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lat</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 80.      ,  79.991071,  79.982143, ..., -59.973214, -59.982143,
-       -59.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-a3d95add-39cd-4981-a610-6af3a13c61bf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3d95add-39cd-4981-a610-6af3a13c61bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19745962-4f4d-41f1-8bf1-74979852b6e9' class='xr-var-data-in' type='checkbox'><label for='data-19745962-4f4d-41f1-8bf1-74979852b6e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lon</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-180.      , -179.991071, -179.982143, ...,  179.973214,  179.982143,
-        179.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan 1.0 2.0 3.0 ... 33.0 34.0 35.0</div><input id='attrs-eb084142-2d88-41fa-8744-c2cf35b37ecf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-eb084142-2d88-41fa-8744-c2cf35b37ecf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e6b4cbf-4b24-4591-a438-d4c46fcaf99f' class='xr-var-data-in' type='checkbox'><label for='data-5e6b4cbf-4b24-4591-a438-d4c46fcaf99f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan,  1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 13.,
+    title:                Normalized Difference Vegetation Index: Long Term S...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d25ced06-1dc6-497d-a17c-7109d13e49ac' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d25ced06-1dc6-497d-a17c-7109d13e49ac' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 15680</li><li><span class='xr-has-index'>lon</span>: 40320</li><li><span class='xr-has-index'>time</span>: 36</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-4b8bde58-4ba7-4ca3-84ed-a31ad8d42672' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4b8bde58-4ba7-4ca3-84ed-a31ad8d42672' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.99 79.98 ... -59.98 -59.99</div><input id='attrs-9c356f0e-f7d6-4d9b-899e-84786e2fe4eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c356f0e-f7d6-4d9b-899e-84786e2fe4eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3d605af-1cd0-494e-a803-6621564988e9' class='xr-var-data-in' type='checkbox'><label for='data-b3d605af-1cd0-494e-a803-6621564988e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lat</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 80.      ,  79.991071,  79.982143, ..., -59.973214, -59.982143,
+       -59.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-a42ccfb4-2cec-4a35-8e9a-05f10ef22d20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a42ccfb4-2cec-4a35-8e9a-05f10ef22d20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24197c0d-1b53-4546-a5a6-5df78c5738be' class='xr-var-data-in' type='checkbox'><label for='data-24197c0d-1b53-4546-a5a6-5df78c5738be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lon</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-180.      , -179.991071, -179.982143, ...,  179.973214,  179.982143,
+        179.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan 1.0 2.0 3.0 ... 33.0 34.0 35.0</div><input id='attrs-5f28d7d6-88f4-4510-9439-9dc3076c5af4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5f28d7d6-88f4-4510-9439-9dc3076c5af4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03587a76-82a2-4a8e-ad40-bd81ceba96ab' class='xr-var-data-in' type='checkbox'><label for='data-03587a76-82a2-4a8e-ad40-bd81ceba96ab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan,  1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 13.,
        14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27.,
-       28., 29., 30., 31., 32., 33., 34., 35.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6de76cc2-e482-444e-a026-1a00a845d996' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6de76cc2-e482-444e-a026-1a00a845d996' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1cffe4e7-4f2d-4c68-973d-23149b988a9a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1cffe4e7-4f2d-4c68-973d-23149b988a9a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5882bb47-1eba-4844-ae04-7041b8d05f3c' class='xr-var-data-in' type='checkbox'><label for='data-5882bb47-1eba-4844-ae04-7041b8d05f3c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GeoTransform :</span></dt><dd>-180.0000000000 0.0089285714 0.0 80.0000000000 0.0 -0.0089285714</dd><dt><span>_CoordinateAxisTypes :</span></dt><dd>GeoX GeoY</dd><dt><span>_CoordinateTransformType :</span></dt><dd>Projection</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>long_name :</span></dt><dd>coordinate reference system</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9108&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=object]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-f9e96506-471d-4719-bac3-46961812445f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f9e96506-471d-4719-bac3-46961812445f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e049df37-2546-4201-8bdd-bba4be9aa5a5' class='xr-var-data-in' type='checkbox'><label for='data-e049df37-2546-4201-8bdd-bba4be9aa5a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: maximum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Maximum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
+       28., 29., 30., 31., 32., 33., 34., 35.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8c5d8a1f-7850-4ffc-ad65-873ba139bc06' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8c5d8a1f-7850-4ffc-ad65-873ba139bc06' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5a725d08-ac90-4619-ad9a-5ea1543d98a2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a725d08-ac90-4619-ad9a-5ea1543d98a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c410a086-080d-4fb5-8b11-037ee66000fd' class='xr-var-data-in' type='checkbox'><label for='data-c410a086-080d-4fb5-8b11-037ee66000fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GeoTransform :</span></dt><dd>-180.0000000000 0.0089285714 0.0 80.0000000000 0.0 -0.0089285714</dd><dt><span>_CoordinateAxisTypes :</span></dt><dd>GeoX GeoY</dd><dt><span>_CoordinateTransformType :</span></dt><dd>Projection</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>long_name :</span></dt><dd>coordinate reference system</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9108&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=object]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-e19f7478-850d-4d6d-87ec-9daf06e051b7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e19f7478-850d-4d6d-87ec-9daf06e051b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58bef11a-89eb-44b5-93ea-42e201970c5d' class='xr-var-data-in' type='checkbox'><label for='data-58bef11a-89eb-44b5-93ea-42e201970c5d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: maximum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Maximum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -1472,7 +1473,7 @@ <h3>Read from online kerchunked consolidated dataset<a class="headerlink" href="
 </svg>
         </td>
     </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-acf0a60f-5e3d-4430-a5ff-e7845fc85e71' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-acf0a60f-5e3d-4430-a5ff-e7845fc85e71' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6fd17b5a-991c-4499-a2e6-8714ef219412' class='xr-var-data-in' type='checkbox'><label for='data-6fd17b5a-991c-4499-a2e6-8714ef219412' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: mean</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Mean Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-adf8593e-d9ab-4d0d-b1ee-ed1e4e2e1171' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-adf8593e-d9ab-4d0d-b1ee-ed1e4e2e1171' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b175ffae-444b-4468-a5e3-ab99fae24b34' class='xr-var-data-in' type='checkbox'><label for='data-b175ffae-444b-4468-a5e3-ab99fae24b34' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: mean</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Mean Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -1634,7 +1635,7 @@ <h3>Read from online kerchunked consolidated dataset<a class="headerlink" href="
 </svg>
         </td>
     </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>median</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-14f40490-29fe-4210-b927-644014bfda5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14f40490-29fe-4210-b927-644014bfda5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9af97801-4e95-4e87-b6f2-b293852378af' class='xr-var-data-in' type='checkbox'><label for='data-9af97801-4e95-4e87-b6f2-b293852378af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: median</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Median Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>median</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-b7921f3b-ea81-4dfa-98b3-ac35c0335ae2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b7921f3b-ea81-4dfa-98b3-ac35c0335ae2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d7c5f3d-a8cf-491e-80a1-b13217f412f6' class='xr-var-data-in' type='checkbox'><label for='data-4d7c5f3d-a8cf-491e-80a1-b13217f412f6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: median</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Median Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -1796,7 +1797,7 @@ <h3>Read from online kerchunked consolidated dataset<a class="headerlink" href="
 </svg>
         </td>
     </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-a18b276c-527f-4197-aac2-9242f67ec646' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a18b276c-527f-4197-aac2-9242f67ec646' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0ed9b08-c241-4508-aab8-c61280a7aeb3' class='xr-var-data-in' type='checkbox'><label for='data-f0ed9b08-c241-4508-aab8-c61280a7aeb3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: minimum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Minimum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-a890de13-f14f-4cac-8cb7-ab0b2355669b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a890de13-f14f-4cac-8cb7-ab0b2355669b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c73e7ec4-8c81-43ea-bfbd-cfb9a4cc1ff4' class='xr-var-data-in' type='checkbox'><label for='data-c73e7ec4-8c81-43ea-bfbd-cfb9a4cc1ff4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: minimum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Minimum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -1958,7 +1959,7 @@ <h3>Read from online kerchunked consolidated dataset<a class="headerlink" href="
 </svg>
         </td>
     </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nobs</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-11652819-2ea7-4371-8e4f-480006cda44f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11652819-2ea7-4371-8e4f-480006cda44f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1de33b3f-4ede-4b2e-bdf0-fe2e16081afd' class='xr-var-data-in' type='checkbox'><label for='data-1de33b3f-4ede-4b2e-bdf0-fe2e16081afd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index number_of_observations</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[1, 250]</dd></dl></div><div class='xr-var-data'><table>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nobs</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-825e588b-7497-4535-a32e-260ed2c4939c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-825e588b-7497-4535-a32e-260ed2c4939c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-feca7af2-56be-4a9b-b83d-2ab86d5429ab' class='xr-var-data-in' type='checkbox'><label for='data-feca7af2-56be-4a9b-b83d-2ab86d5429ab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index number_of_observations</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[1, 250]</dd></dl></div><div class='xr-var-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -2120,7 +2121,7 @@ <h3>Read from online kerchunked consolidated dataset<a class="headerlink" href="
 </svg>
         </td>
     </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stdev</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-fcd3537c-35d6-42c4-a3dc-59242d196fdf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fcd3537c-35d6-42c4-a3dc-59242d196fdf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c26e0df3-a50c-492b-874f-c9c666206ed5' class='xr-var-data-in' type='checkbox'><label for='data-c26e0df3-a50c-492b-874f-c9c666206ed5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: standard_deviation</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Standard deviation Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stdev</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-cbf75f43-c110-4dbb-8496-7c932f3b0a0a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cbf75f43-c110-4dbb-8496-7c932f3b0a0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee54e948-540c-4421-8219-730bbf54ced9' class='xr-var-data-in' type='checkbox'><label for='data-ee54e948-540c-4421-8219-730bbf54ced9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: standard_deviation</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Standard deviation Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -2282,7 +2283,7 @@ <h3>Read from online kerchunked consolidated dataset<a class="headerlink" href="
 </svg>
         </td>
     </tr>
-</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-4b425b7b-03ac-49ca-a288-07f977f6b34b' class='xr-section-summary-in' type='checkbox'  ><label for='section-4b425b7b-03ac-49ca-a288-07f977f6b34b' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-86a3cb72-bb57-48a3-b4cf-e63c2cc00637' class='xr-index-data-in' type='checkbox'/><label for='index-86a3cb72-bb57-48a3-b4cf-e63c2cc00637' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               80.0,   79.99107142857143,   79.98214285714286,
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-834d4a40-8e80-445d-be84-7239ec5b2c37' class='xr-section-summary-in' type='checkbox'  ><label for='section-834d4a40-8e80-445d-be84-7239ec5b2c37' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-db421833-4e43-464f-a41e-77caccb97239' class='xr-index-data-in' type='checkbox'/><label for='index-db421833-4e43-464f-a41e-77caccb97239' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               80.0,   79.99107142857143,   79.98214285714286,
          79.97321428571429,   79.96428571428572,   79.95535714285715,
          79.94642857142858,   79.93750000000001,   79.92857142857144,
          79.91964285714288,
@@ -2291,7 +2292,7 @@ <h3>Read from online kerchunked consolidated dataset<a class="headerlink" href="
         -59.93749999996817,  -59.94642857139675, -59.955357142825335,
         -59.96428571425389, -59.973214285682445,  -59.98214285711103,
         -59.99107142853961],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=15680))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-10b7b148-e77f-4756-99c7-392d62c98dcb' class='xr-index-data-in' type='checkbox'/><label for='index-10b7b148-e77f-4756-99c7-392d62c98dcb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -180.0, -179.99107142857142, -179.98214285714283,
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=15680))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-19120e47-43c2-46cc-85bf-1ed72743d0f2' class='xr-index-data-in' type='checkbox'/><label for='index-19120e47-43c2-46cc-85bf-1ed72743d0f2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -180.0, -179.99107142857142, -179.98214285714283,
        -179.97321428571425, -179.96428571428567, -179.95535714285708,
         -179.9464285714285, -179.93749999999991, -179.92857142857133,
        -179.91964285714275,
@@ -2300,10 +2301,10 @@ <h3>Read from online kerchunked consolidated dataset<a class="headerlink" href="
           179.937500000491,  179.94642857191963,  179.95535714334824,
          179.9642857147768,  179.97321428620535,  179.98214285763396,
         179.99107142906257],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=40320))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-28d140c6-4a04-40c4-8e1f-120353cda245' class='xr-index-data-in' type='checkbox'/><label for='index-28d140c6-4a04-40c4-8e1f-120353cda245' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ nan,  1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,  9.0, 10.0, 11.0,
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=40320))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c8f0ae1a-b6b2-4e03-9937-7886bff11f16' class='xr-index-data-in' type='checkbox'/><label for='index-c8f0ae1a-b6b2-4e03-9937-7886bff11f16' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ nan,  1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,  9.0, 10.0, 11.0,
        12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0,
        24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0, 32.0, 33.0, 34.0, 35.0],
-      dtype=&#x27;float64&#x27;, name=&#x27;time&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-395591e4-45c0-4022-9aa5-1c81df912860' class='xr-section-summary-in' type='checkbox'  ><label for='section-395591e4-45c0-4022-9aa5-1c81df912860' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>archive_facility :</span></dt><dd>VITO</dd><dt><span>copyright :</span></dt><dd>Copernicus Service information 2021</dd><dt><span>history :</span></dt><dd>2021-03-01 - Processing line NDVI LTS</dd><dt><span>identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-0101_GLOBE_V3.0.1</dd><dt><span>institution :</span></dt><dd>VITO NV</dd><dt><span>long_name :</span></dt><dd>Normalized Difference Vegetation Index</dd><dt><span>orbit_type :</span></dt><dd>LEO</dd><dt><span>parent_identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all</dd><dt><span>platform :</span></dt><dd>SPOT-4, SPOT-5, Proba-V</dd><dt><span>processing_level :</span></dt><dd>L4</dd><dt><span>processing_mode :</span></dt><dd>Offline</dd><dt><span>product_version :</span></dt><dd>V3.0.1</dd><dt><span>references :</span></dt><dd>https://land.copernicus.eu/global/products/ndvi</dd><dt><span>sensor :</span></dt><dd>VEGETATION-1, VEGETATION-2, VEGETATION</dd><dt><span>source :</span></dt><dd>Derived from EO satellite imagery</dd><dt><span>time_coverage_end :</span></dt><dd>2019-12-31T23:59:59Z</dd><dt><span>time_coverage_start :</span></dt><dd>1999-01-01T00:00:00Z</dd><dt><span>title :</span></dt><dd>Normalized Difference Vegetation Index: Long Term Statistics 1KM: GLOBE 1999-2019 0101</dd></dl></div></li></ul></div></div></div></div>
+      dtype=&#x27;float64&#x27;, name=&#x27;time&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1e37547e-d6ba-41f3-957e-f29d3bae3cc9' class='xr-section-summary-in' type='checkbox'  ><label for='section-1e37547e-d6ba-41f3-957e-f29d3bae3cc9' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>archive_facility :</span></dt><dd>VITO</dd><dt><span>copyright :</span></dt><dd>Copernicus Service information 2021</dd><dt><span>history :</span></dt><dd>2021-03-01 - Processing line NDVI LTS</dd><dt><span>identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-0101_GLOBE_V3.0.1</dd><dt><span>institution :</span></dt><dd>VITO NV</dd><dt><span>long_name :</span></dt><dd>Normalized Difference Vegetation Index</dd><dt><span>orbit_type :</span></dt><dd>LEO</dd><dt><span>parent_identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all</dd><dt><span>platform :</span></dt><dd>SPOT-4, SPOT-5, Proba-V</dd><dt><span>processing_level :</span></dt><dd>L4</dd><dt><span>processing_mode :</span></dt><dd>Offline</dd><dt><span>product_version :</span></dt><dd>V3.0.1</dd><dt><span>references :</span></dt><dd>https://land.copernicus.eu/global/products/ndvi</dd><dt><span>sensor :</span></dt><dd>VEGETATION-1, VEGETATION-2, VEGETATION</dd><dt><span>source :</span></dt><dd>Derived from EO satellite imagery</dd><dt><span>time_coverage_end :</span></dt><dd>2019-12-31T23:59:59Z</dd><dt><span>time_coverage_start :</span></dt><dd>1999-01-01T00:00:00Z</dd><dt><span>title :</span></dt><dd>Normalized Difference Vegetation Index: Long Term Statistics 1KM: GLOBE 1999-2019 0101</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <p>By inspecting any of the variables on the representation above, you’ll see that each data array represents <strong>about 85GiB of data</strong>, so much more than the availabe memory on this notebook server, and even on the Dask Cluster we created above. But thanks to chunking, we can still analyze it!</p>
 <div class="cell docutils container">
@@ -2681,7 +2682,7 @@ <h3>Read from online kerchunked consolidated dataset<a class="headerlink" href="
 dask.array&lt;mean_agg-aggregate, shape=(), dtype=float32, chunksize=(), chunktype=numpy.ndarray&gt;
 Coordinates:
     lat      float64 45.5
-    lon      float64 9.357</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'min'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-4f4f3c30-6d59-43eb-9e71-318886fb01f2' class='xr-array-in' type='checkbox' checked><label for='section-4f4f3c30-6d59-43eb-9e71-318886fb01f2' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>
+    lon      float64 9.357</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'min'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-cd3bdffa-575a-4570-b320-3f091c488286' class='xr-array-in' type='checkbox' checked><label for='section-cd3bdffa-575a-4570-b320-3f091c488286' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -2720,7 +2721,7 @@ <h3>Read from online kerchunked consolidated dataset<a class="headerlink" href="
         
         </td>
     </tr>
-</table></div></div></li><li class='xr-section-item'><input id='section-c96076a6-f3c0-4f00-9bd7-0ea0c9eccaf2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c96076a6-f3c0-4f00-9bd7-0ea0c9eccaf2' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>45.5</div><input id='attrs-73610771-4e3c-4e66-8e8e-3cb2f41aa874' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73610771-4e3c-4e66-8e8e-3cb2f41aa874' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2ff1386-0338-48f6-93f6-a3c1e8cccf08' class='xr-var-data-in' type='checkbox'><label for='data-b2ff1386-0338-48f6-93f6-a3c1e8cccf08' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lat</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array(45.5)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.357</div><input id='attrs-29ba0003-9bc7-46c6-a8d4-05669d699419' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29ba0003-9bc7-46c6-a8d4-05669d699419' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b4b48c8-40fa-4bd8-b932-93f5dcd570a5' class='xr-var-data-in' type='checkbox'><label for='data-9b4b48c8-40fa-4bd8-b932-93f5dcd570a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lon</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array(9.35714286)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0ded2d21-80de-4973-932d-cf0abd9b8215' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0ded2d21-80de-4973-932d-cf0abd9b8215' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-eb20fc4e-8055-4d93-8030-10366051af18' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-eb20fc4e-8055-4d93-8030-10366051af18' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
+</table></div></div></li><li class='xr-section-item'><input id='section-b852a4f9-6524-444a-8851-b3edfd278b41' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b852a4f9-6524-444a-8851-b3edfd278b41' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>45.5</div><input id='attrs-88557d91-83b9-4b87-8eae-1910295e5bdb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88557d91-83b9-4b87-8eae-1910295e5bdb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64b9407e-abe0-415a-9ba7-76cc8544c983' class='xr-var-data-in' type='checkbox'><label for='data-64b9407e-abe0-415a-9ba7-76cc8544c983' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lat</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array(45.5)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.357</div><input id='attrs-4010e765-e623-4959-8a08-a77779166372' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4010e765-e623-4959-8a08-a77779166372' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b66114f1-d61c-4567-a4e7-73a5914cdea0' class='xr-var-data-in' type='checkbox'><label for='data-b66114f1-d61c-4567-a4e7-73a5914cdea0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lon</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array(9.35714286)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3181dbd8-c23f-4b1c-a66e-8103d3d2ec77' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3181dbd8-c23f-4b1c-a66e-8103d3d2ec77' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-d556d22d-35a4-4ff8-a319-18841061f9d9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d556d22d-35a4-4ff8-a319-18841061f9d9' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
 </div>
 <p>Did you notice something on the Dask Dashboard when running the two previous cells?</p>
 <p>We didn’t ‘compute’ anything. We just built a Dask task graph with it’s size indicated as count above, but did not ask Dask to return a result.</p>
@@ -2788,7 +2789,7 @@ <h3>Optimize the task graph<a class="headerlink" href="#optimize-the-task-graph"
 </div>
 </div>
 <div class="cell_output docutils container">
-<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "48ffe034627342d9a4ddacb6f04298da"}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "b333c366c5064b55be8bac5d5d16c08b"}</script></div>
 </div>
 </section>
 <section id="compute-on-the-dask-workers">
@@ -3167,7 +3168,7 @@ <h3>Compute on the dask workers<a class="headerlink" href="#compute-on-the-dask-
 array(0.31844446, dtype=float32)
 Coordinates:
     lat      float64 45.5
-    lon      float64 9.357</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'min'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e2b9ee44-1013-4a68-8448-c316732aae13' class='xr-array-in' type='checkbox' checked><label for='section-e2b9ee44-1013-4a68-8448-c316732aae13' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.3184</span></div><div class='xr-array-data'><pre>array(0.31844446, dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-06dbf375-fd92-4343-899e-50492b366f4b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-06dbf375-fd92-4343-899e-50492b366f4b' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>45.5</div><input id='attrs-89bd4423-9b8b-4b25-9135-fc2f08b35d1e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89bd4423-9b8b-4b25-9135-fc2f08b35d1e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66c26a89-12f9-4820-909e-1e77458d80b9' class='xr-var-data-in' type='checkbox'><label for='data-66c26a89-12f9-4820-909e-1e77458d80b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lat</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array(45.5)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.357</div><input id='attrs-a77bdfbc-c49b-4df0-83f0-2e58abff382b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a77bdfbc-c49b-4df0-83f0-2e58abff382b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b17a4251-cb9b-4d0f-abfa-43aca0bbfda7' class='xr-var-data-in' type='checkbox'><label for='data-b17a4251-cb9b-4d0f-abfa-43aca0bbfda7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lon</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array(9.35714286)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-81fdeccf-0b90-4861-9967-eeb6a359fdf9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-81fdeccf-0b90-4861-9967-eeb6a359fdf9' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-0191de56-4264-498c-a51a-f42c7a1b63f7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0191de56-4264-498c-a51a-f42c7a1b63f7' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
+    lon      float64 9.357</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'min'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-6870a4da-cf08-462e-adf2-4cef365dbdc3' class='xr-array-in' type='checkbox' checked><label for='section-6870a4da-cf08-462e-adf2-4cef365dbdc3' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.3184</span></div><div class='xr-array-data'><pre>array(0.31844446, dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-8d9e9c02-38a6-4c3b-9c74-1f3239fb91a2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8d9e9c02-38a6-4c3b-9c74-1f3239fb91a2' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>45.5</div><input id='attrs-74ff0c92-3171-474e-9e1b-6975a405dae3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74ff0c92-3171-474e-9e1b-6975a405dae3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43918c57-9838-4259-b3f2-8005f7b4fd55' class='xr-var-data-in' type='checkbox'><label for='data-43918c57-9838-4259-b3f2-8005f7b4fd55' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lat</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array(45.5)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.357</div><input id='attrs-63319a63-bdac-4fa6-849b-d4e480c6dc2e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63319a63-bdac-4fa6-849b-d4e480c6dc2e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0c9b099-69fc-41da-8b05-0a07c3e52fbc' class='xr-var-data-in' type='checkbox'><label for='data-e0c9b099-69fc-41da-8b05-0a07c3e52fbc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lon</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array(9.35714286)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-075fde6a-3fc7-4699-af75-67f77d872beb' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-075fde6a-3fc7-4699-af75-67f77d872beb' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-942d8019-a22f-4c23-bb5d-ef5debdb40e4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-942d8019-a22f-4c23-bb5d-ef5debdb40e4' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
 </div>
 <p>Calling compute on our Xarray object triggered the execution on Dask Cluster side.</p>
 <p>You should be able to see how Dask is working on Dask Dashboard.</p>
@@ -3260,7 +3261,7 @@ <h3>Get a client from the Dask Gateway Cluster<a class="headerlink" href="#get-a
     <div style="width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;"> </div>
     <div style="margin-left: 48px;">
         <h3 style="margin-bottom: 0px;">Client</h3>
-        <p style="color: #9D9D9D; margin-bottom: 0px;">Client-1ff9e743-7802-11ee-8ebb-000d3ae50e51</p>
+        <p style="color: #9D9D9D; margin-bottom: 0px;">Client-f8f23665-7807-11ee-8f27-002248352ce8</p>
         <table style="width: 100%; text-align: left;">
 
         <tr>
@@ -3295,7 +3296,7 @@ <h3 style="margin-bottom: 0px;">Client</h3>
     </div>
     <div style="margin-left: 48px;">
         <h3 style="margin-bottom: 0px; margin-top: 0px;">LocalCluster</h3>
-        <p style="color: #9D9D9D; margin-bottom: 0px;">6e1bf9fb</p>
+        <p style="color: #9D9D9D; margin-bottom: 0px;">2dd009f6</p>
         <table style="width: 100%; text-align: left;">
             <tr>
                 <td style="text-align: left;">
@@ -3332,11 +3333,11 @@ <h3 style="display: inline;">Scheduler Info</h3>
         <div style="width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;"> </div>
         <div style="margin-left: 48px;">
             <h3 style="margin-bottom: 0px;">Scheduler</h3>
-            <p style="color: #9D9D9D; margin-bottom: 0px;">Scheduler-45497f53-a093-43e3-9779-a25bfddebb25</p>
+            <p style="color: #9D9D9D; margin-bottom: 0px;">Scheduler-953bc830-1f06-4704-8abe-e7bdaff76253</p>
             <table style="width: 100%; text-align: left;">
                 <tr>
                     <td style="text-align: left;">
-                        <strong>Comm:</strong> tcp://127.0.0.1:36863
+                        <strong>Comm:</strong> tcp://127.0.0.1:37459
                     </td>
                     <td style="text-align: left;">
                         <strong>Workers:</strong> 2
@@ -3378,7 +3379,7 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 0</h4>
                 <table style="width: 100%; text-align: left;">
                     <tr>
                         <td style="text-align: left;">
-                            <strong>Comm: </strong> tcp://127.0.0.1:46093
+                            <strong>Comm: </strong> tcp://127.0.0.1:46281
                         </td>
                         <td style="text-align: left;">
                             <strong>Total threads: </strong> 1
@@ -3386,7 +3387,7 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 0</h4>
                     </tr>
                     <tr>
                         <td style="text-align: left;">
-                            <strong>Dashboard: </strong> <a href="http://127.0.0.1:33329/status" target="_blank">http://127.0.0.1:33329/status</a>
+                            <strong>Dashboard: </strong> <a href="http://127.0.0.1:46877/status" target="_blank">http://127.0.0.1:46877/status</a>
                         </td>
                         <td style="text-align: left;">
                             <strong>Memory: </strong> 3.38 GiB
@@ -3394,13 +3395,13 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 0</h4>
                     </tr>
                     <tr>
                         <td style="text-align: left;">
-                            <strong>Nanny: </strong> tcp://127.0.0.1:43249
+                            <strong>Nanny: </strong> tcp://127.0.0.1:35783
                         </td>
                         <td style="text-align: left;"></td>
                     </tr>
                     <tr>
                         <td colspan="2" style="text-align: left;">
-                            <strong>Local directory: </strong> /tmp/dask-scratch-space/worker-e7mrhyvm
+                            <strong>Local directory: </strong> /tmp/dask-scratch-space/worker-4pfh6xjh
                         </td>
                     </tr>
 
@@ -3423,7 +3424,7 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 1</h4>
                 <table style="width: 100%; text-align: left;">
                     <tr>
                         <td style="text-align: left;">
-                            <strong>Comm: </strong> tcp://127.0.0.1:38413
+                            <strong>Comm: </strong> tcp://127.0.0.1:43977
                         </td>
                         <td style="text-align: left;">
                             <strong>Total threads: </strong> 1
@@ -3431,7 +3432,7 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 1</h4>
                     </tr>
                     <tr>
                         <td style="text-align: left;">
-                            <strong>Dashboard: </strong> <a href="http://127.0.0.1:38237/status" target="_blank">http://127.0.0.1:38237/status</a>
+                            <strong>Dashboard: </strong> <a href="http://127.0.0.1:46497/status" target="_blank">http://127.0.0.1:46497/status</a>
                         </td>
                         <td style="text-align: left;">
                             <strong>Memory: </strong> 3.38 GiB
@@ -3439,13 +3440,13 @@ <h4 style="margin-bottom: 0px; display: inline;">Worker: 1</h4>
                     </tr>
                     <tr>
                         <td style="text-align: left;">
-                            <strong>Nanny: </strong> tcp://127.0.0.1:40079
+                            <strong>Nanny: </strong> tcp://127.0.0.1:44771
                         </td>
                         <td style="text-align: left;"></td>
                     </tr>
                     <tr>
                         <td colspan="2" style="text-align: left;">
-                            <strong>Local directory: </strong> /tmp/dask-scratch-space/worker-nem0ni8e
+                            <strong>Local directory: </strong> /tmp/dask-scratch-space/worker-p_h9_jjy
                         </td>
                     </tr>
 
@@ -3874,11 +3875,11 @@ <h2>Global LTS computation<a class="headerlink" href="#global-lts-computation" t
     source:               Derived from EO satellite imagery
     time_coverage_end:    2019-12-31T23:59:59Z
     time_coverage_start:  1999-01-01T00:00:00Z
-    title:                Normalized Difference Vegetation Index: Long Term S...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-51968c6f-3132-40f4-b6d5-e7928160a760' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-51968c6f-3132-40f4-b6d5-e7928160a760' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 15680</li><li><span class='xr-has-index'>lon</span>: 40320</li><li><span class='xr-has-index'>time</span>: 36</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-da9532fc-572f-485d-859f-3502461eeb47' class='xr-section-summary-in' type='checkbox'  checked><label for='section-da9532fc-572f-485d-859f-3502461eeb47' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.99 79.98 ... -59.98 -59.99</div><input id='attrs-3f41c81f-a213-4203-8a97-cc3925dba3df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f41c81f-a213-4203-8a97-cc3925dba3df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b2c179b-0a8d-4a2d-b6bd-cd2d42c74b8e' class='xr-var-data-in' type='checkbox'><label for='data-6b2c179b-0a8d-4a2d-b6bd-cd2d42c74b8e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lat</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 80.      ,  79.991071,  79.982143, ..., -59.973214, -59.982143,
-       -59.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-0f3518a9-6614-4557-b535-f3701c061afa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f3518a9-6614-4557-b535-f3701c061afa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6058951d-142b-445d-b5e8-c7eb5aa71f49' class='xr-var-data-in' type='checkbox'><label for='data-6058951d-142b-445d-b5e8-c7eb5aa71f49' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lon</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-180.      , -179.991071, -179.982143, ...,  179.973214,  179.982143,
-        179.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan 1.0 2.0 3.0 ... 33.0 34.0 35.0</div><input id='attrs-d6a00031-701a-4c2f-803b-a8aee7766eb4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d6a00031-701a-4c2f-803b-a8aee7766eb4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9e0a75d-38ce-4dcc-8e10-a7deaac201d4' class='xr-var-data-in' type='checkbox'><label for='data-d9e0a75d-38ce-4dcc-8e10-a7deaac201d4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan,  1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 13.,
+    title:                Normalized Difference Vegetation Index: Long Term S...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6363618f-1db2-4ab3-8fab-00c2f05bf698' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6363618f-1db2-4ab3-8fab-00c2f05bf698' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 15680</li><li><span class='xr-has-index'>lon</span>: 40320</li><li><span class='xr-has-index'>time</span>: 36</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ecc0d717-52d0-489b-8836-c106724e75a4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ecc0d717-52d0-489b-8836-c106724e75a4' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.99 79.98 ... -59.98 -59.99</div><input id='attrs-124e486f-6906-4515-9488-761897e6ff96' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-124e486f-6906-4515-9488-761897e6ff96' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e13ac5b-6ba8-4520-891f-dc7c31f2a1d3' class='xr-var-data-in' type='checkbox'><label for='data-6e13ac5b-6ba8-4520-891f-dc7c31f2a1d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lat</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 80.      ,  79.991071,  79.982143, ..., -59.973214, -59.982143,
+       -59.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-0ffdc7eb-bf2e-4358-836e-e3b56ddd3f10' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ffdc7eb-bf2e-4358-836e-e3b56ddd3f10' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-801a3f3c-6d36-4535-aae6-11e2ffeb18e1' class='xr-var-data-in' type='checkbox'><label for='data-801a3f3c-6d36-4535-aae6-11e2ffeb18e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lon</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-180.      , -179.991071, -179.982143, ...,  179.973214,  179.982143,
+        179.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan 1.0 2.0 3.0 ... 33.0 34.0 35.0</div><input id='attrs-1c85881a-9bd8-4c83-8830-ef702ba26885' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1c85881a-9bd8-4c83-8830-ef702ba26885' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b1a1c50-2fb8-4710-ae20-c3b2ae706cec' class='xr-var-data-in' type='checkbox'><label for='data-4b1a1c50-2fb8-4710-ae20-c3b2ae706cec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan,  1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 13.,
        14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27.,
-       28., 29., 30., 31., 32., 33., 34., 35.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e807fb75-c2dc-4ac7-95b4-776de1b4072e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e807fb75-c2dc-4ac7-95b4-776de1b4072e' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-18b8f58f-4544-4f68-abef-c90e9e7ef8ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18b8f58f-4544-4f68-abef-c90e9e7ef8ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f01c247-903e-41c6-b7b9-c24a959376bf' class='xr-var-data-in' type='checkbox'><label for='data-1f01c247-903e-41c6-b7b9-c24a959376bf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GeoTransform :</span></dt><dd>-180.0000000000 0.0089285714 0.0 80.0000000000 0.0 -0.0089285714</dd><dt><span>_CoordinateAxisTypes :</span></dt><dd>GeoX GeoY</dd><dt><span>_CoordinateTransformType :</span></dt><dd>Projection</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>long_name :</span></dt><dd>coordinate reference system</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9108&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=object]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-0cc3cd74-da06-46b9-8c35-7ef1c5e7601d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0cc3cd74-da06-46b9-8c35-7ef1c5e7601d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dee544e1-f6d4-4ad0-a872-f387a552ecc6' class='xr-var-data-in' type='checkbox'><label for='data-dee544e1-f6d4-4ad0-a872-f387a552ecc6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: maximum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Maximum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
+       28., 29., 30., 31., 32., 33., 34., 35.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1676d4a1-360d-4701-8171-668c4820ff83' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1676d4a1-360d-4701-8171-668c4820ff83' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cbf04ab8-3e11-45d4-8075-b14c73a67cf2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cbf04ab8-3e11-45d4-8075-b14c73a67cf2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4853d80-f17c-4081-bf34-3c98ef5930cb' class='xr-var-data-in' type='checkbox'><label for='data-a4853d80-f17c-4081-bf34-3c98ef5930cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GeoTransform :</span></dt><dd>-180.0000000000 0.0089285714 0.0 80.0000000000 0.0 -0.0089285714</dd><dt><span>_CoordinateAxisTypes :</span></dt><dd>GeoX GeoY</dd><dt><span>_CoordinateTransformType :</span></dt><dd>Projection</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>long_name :</span></dt><dd>coordinate reference system</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9108&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=object]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-154f02ed-eae9-43f6-8300-ec01dbb5eca3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-154f02ed-eae9-43f6-8300-ec01dbb5eca3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24de6efb-99e1-4c6e-abb0-563679ee3e82' class='xr-var-data-in' type='checkbox'><label for='data-24de6efb-99e1-4c6e-abb0-563679ee3e82' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: maximum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Maximum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -4040,7 +4041,7 @@ <h2>Global LTS computation<a class="headerlink" href="#global-lts-computation" t
 </svg>
         </td>
     </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-0287cf14-5aaa-4f85-9253-02688b58315a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0287cf14-5aaa-4f85-9253-02688b58315a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a068a7f-8f86-4a11-8b9e-74d549e6c3cb' class='xr-var-data-in' type='checkbox'><label for='data-0a068a7f-8f86-4a11-8b9e-74d549e6c3cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: mean</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Mean Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-173af904-8e70-460b-bb4b-d122acb7fc84' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-173af904-8e70-460b-bb4b-d122acb7fc84' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ba91f33-ffe4-46b7-8cb9-770a7a2253a1' class='xr-var-data-in' type='checkbox'><label for='data-6ba91f33-ffe4-46b7-8cb9-770a7a2253a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: mean</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Mean Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -4202,7 +4203,7 @@ <h2>Global LTS computation<a class="headerlink" href="#global-lts-computation" t
 </svg>
         </td>
     </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>median</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-0dc793eb-a6c9-489c-b400-78ceb65687f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0dc793eb-a6c9-489c-b400-78ceb65687f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78e67eda-c083-42ff-b5fe-5de90e3b4f76' class='xr-var-data-in' type='checkbox'><label for='data-78e67eda-c083-42ff-b5fe-5de90e3b4f76' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: median</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Median Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>median</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-e198ec6d-40c9-4cd7-900f-1869969524c3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e198ec6d-40c9-4cd7-900f-1869969524c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85417b24-962a-4913-801f-75142b2700a0' class='xr-var-data-in' type='checkbox'><label for='data-85417b24-962a-4913-801f-75142b2700a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: median</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Median Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -4364,7 +4365,7 @@ <h2>Global LTS computation<a class="headerlink" href="#global-lts-computation" t
 </svg>
         </td>
     </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-f1eef72a-5d91-43a7-8ea9-3874eb0eaff3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1eef72a-5d91-43a7-8ea9-3874eb0eaff3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe440044-2a80-43a8-92a0-ee1e895caeb6' class='xr-var-data-in' type='checkbox'><label for='data-fe440044-2a80-43a8-92a0-ee1e895caeb6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: minimum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Minimum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-309d1776-7e83-4677-b9e5-18b92caaec5a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-309d1776-7e83-4677-b9e5-18b92caaec5a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13f49a7a-40c4-4a24-bd9f-9d7125242dc6' class='xr-var-data-in' type='checkbox'><label for='data-13f49a7a-40c4-4a24-bd9f-9d7125242dc6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: minimum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Minimum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -4526,7 +4527,7 @@ <h2>Global LTS computation<a class="headerlink" href="#global-lts-computation" t
 </svg>
         </td>
     </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nobs</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-c53d2d39-6f8d-4700-b04e-a3de86ec5f9a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c53d2d39-6f8d-4700-b04e-a3de86ec5f9a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a52f7d32-102b-4e53-a576-7305c6f076fb' class='xr-var-data-in' type='checkbox'><label for='data-a52f7d32-102b-4e53-a576-7305c6f076fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index number_of_observations</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[1, 250]</dd></dl></div><div class='xr-var-data'><table>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nobs</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-d83da818-fc2a-4fa6-b59b-3778cec5c8fb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d83da818-fc2a-4fa6-b59b-3778cec5c8fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-005261f9-484f-4d7a-a20e-e55c196483cd' class='xr-var-data-in' type='checkbox'><label for='data-005261f9-484f-4d7a-a20e-e55c196483cd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index number_of_observations</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[1, 250]</dd></dl></div><div class='xr-var-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -4688,7 +4689,7 @@ <h2>Global LTS computation<a class="headerlink" href="#global-lts-computation" t
 </svg>
         </td>
     </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stdev</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-ee292655-e4c9-431c-ba6f-d94b9e122cfb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee292655-e4c9-431c-ba6f-d94b9e122cfb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37c2f4ee-ce83-438d-bfb5-8e6bfc853ac3' class='xr-var-data-in' type='checkbox'><label for='data-37c2f4ee-ce83-438d-bfb5-8e6bfc853ac3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: standard_deviation</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Standard deviation Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stdev</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-19be9748-a935-44b1-bc52-464eeef28391' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-19be9748-a935-44b1-bc52-464eeef28391' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41fbad0e-3a66-43d8-8e6a-b93b6327a349' class='xr-var-data-in' type='checkbox'><label for='data-41fbad0e-3a66-43d8-8e6a-b93b6327a349' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: standard_deviation</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Standard deviation Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -4850,7 +4851,7 @@ <h2>Global LTS computation<a class="headerlink" href="#global-lts-computation" t
 </svg>
         </td>
     </tr>
-</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-5b09cb93-c751-44ba-91cc-fc484fdd2108' class='xr-section-summary-in' type='checkbox'  ><label for='section-5b09cb93-c751-44ba-91cc-fc484fdd2108' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bc225034-58cf-4229-978d-53f6ccee8d4f' class='xr-index-data-in' type='checkbox'/><label for='index-bc225034-58cf-4229-978d-53f6ccee8d4f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               80.0,   79.99107142857143,   79.98214285714286,
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-9c3b6b5b-df84-480b-b694-094271cebe0a' class='xr-section-summary-in' type='checkbox'  ><label for='section-9c3b6b5b-df84-480b-b694-094271cebe0a' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f0828b8e-d3c3-4dfa-9c1a-1c59be21d9fd' class='xr-index-data-in' type='checkbox'/><label for='index-f0828b8e-d3c3-4dfa-9c1a-1c59be21d9fd' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               80.0,   79.99107142857143,   79.98214285714286,
          79.97321428571429,   79.96428571428572,   79.95535714285715,
          79.94642857142858,   79.93750000000001,   79.92857142857144,
          79.91964285714288,
@@ -4859,7 +4860,7 @@ <h2>Global LTS computation<a class="headerlink" href="#global-lts-computation" t
         -59.93749999996817,  -59.94642857139675, -59.955357142825335,
         -59.96428571425389, -59.973214285682445,  -59.98214285711103,
         -59.99107142853961],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=15680))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-84342e4e-5f5f-4382-a84a-0a5925abfd3e' class='xr-index-data-in' type='checkbox'/><label for='index-84342e4e-5f5f-4382-a84a-0a5925abfd3e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -180.0, -179.99107142857142, -179.98214285714283,
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=15680))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1b69bb15-1bc4-47bf-b158-bfa1d5277bf3' class='xr-index-data-in' type='checkbox'/><label for='index-1b69bb15-1bc4-47bf-b158-bfa1d5277bf3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -180.0, -179.99107142857142, -179.98214285714283,
        -179.97321428571425, -179.96428571428567, -179.95535714285708,
         -179.9464285714285, -179.93749999999991, -179.92857142857133,
        -179.91964285714275,
@@ -4868,10 +4869,10 @@ <h2>Global LTS computation<a class="headerlink" href="#global-lts-computation" t
           179.937500000491,  179.94642857191963,  179.95535714334824,
          179.9642857147768,  179.97321428620535,  179.98214285763396,
         179.99107142906257],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=40320))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-af18b4e4-c442-49b9-9348-93b54f3706de' class='xr-index-data-in' type='checkbox'/><label for='index-af18b4e4-c442-49b9-9348-93b54f3706de' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ nan,  1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,  9.0, 10.0, 11.0,
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=40320))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d20bc775-36b3-4cc9-8883-a542e5ff36e1' class='xr-index-data-in' type='checkbox'/><label for='index-d20bc775-36b3-4cc9-8883-a542e5ff36e1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ nan,  1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,  9.0, 10.0, 11.0,
        12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0,
        24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0, 32.0, 33.0, 34.0, 35.0],
-      dtype=&#x27;float64&#x27;, name=&#x27;time&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-93ace062-f990-434a-9fc3-00ee39c28e70' class='xr-section-summary-in' type='checkbox'  ><label for='section-93ace062-f990-434a-9fc3-00ee39c28e70' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>archive_facility :</span></dt><dd>VITO</dd><dt><span>copyright :</span></dt><dd>Copernicus Service information 2021</dd><dt><span>history :</span></dt><dd>2021-03-01 - Processing line NDVI LTS</dd><dt><span>identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-0101_GLOBE_V3.0.1</dd><dt><span>institution :</span></dt><dd>VITO NV</dd><dt><span>long_name :</span></dt><dd>Normalized Difference Vegetation Index</dd><dt><span>orbit_type :</span></dt><dd>LEO</dd><dt><span>parent_identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all</dd><dt><span>platform :</span></dt><dd>SPOT-4, SPOT-5, Proba-V</dd><dt><span>processing_level :</span></dt><dd>L4</dd><dt><span>processing_mode :</span></dt><dd>Offline</dd><dt><span>product_version :</span></dt><dd>V3.0.1</dd><dt><span>references :</span></dt><dd>https://land.copernicus.eu/global/products/ndvi</dd><dt><span>sensor :</span></dt><dd>VEGETATION-1, VEGETATION-2, VEGETATION</dd><dt><span>source :</span></dt><dd>Derived from EO satellite imagery</dd><dt><span>time_coverage_end :</span></dt><dd>2019-12-31T23:59:59Z</dd><dt><span>time_coverage_start :</span></dt><dd>1999-01-01T00:00:00Z</dd><dt><span>title :</span></dt><dd>Normalized Difference Vegetation Index: Long Term Statistics 1KM: GLOBE 1999-2019 0101</dd></dl></div></li></ul></div></div></div></div>
+      dtype=&#x27;float64&#x27;, name=&#x27;time&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ed94b72e-4599-44a1-be5a-e4c6270cba38' class='xr-section-summary-in' type='checkbox'  ><label for='section-ed94b72e-4599-44a1-be5a-e4c6270cba38' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>archive_facility :</span></dt><dd>VITO</dd><dt><span>copyright :</span></dt><dd>Copernicus Service information 2021</dd><dt><span>history :</span></dt><dd>2021-03-01 - Processing line NDVI LTS</dd><dt><span>identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-0101_GLOBE_V3.0.1</dd><dt><span>institution :</span></dt><dd>VITO NV</dd><dt><span>long_name :</span></dt><dd>Normalized Difference Vegetation Index</dd><dt><span>orbit_type :</span></dt><dd>LEO</dd><dt><span>parent_identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all</dd><dt><span>platform :</span></dt><dd>SPOT-4, SPOT-5, Proba-V</dd><dt><span>processing_level :</span></dt><dd>L4</dd><dt><span>processing_mode :</span></dt><dd>Offline</dd><dt><span>product_version :</span></dt><dd>V3.0.1</dd><dt><span>references :</span></dt><dd>https://land.copernicus.eu/global/products/ndvi</dd><dt><span>sensor :</span></dt><dd>VEGETATION-1, VEGETATION-2, VEGETATION</dd><dt><span>source :</span></dt><dd>Derived from EO satellite imagery</dd><dt><span>time_coverage_end :</span></dt><dd>2019-12-31T23:59:59Z</dd><dt><span>time_coverage_start :</span></dt><dd>1999-01-01T00:00:00Z</dd><dt><span>title :</span></dt><dd>Normalized Difference Vegetation Index: Long Term Statistics 1KM: GLOBE 1999-2019 0101</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <section id="fix-time-coordinate">
 <h3>Fix time coordinate<a class="headerlink" href="#fix-time-coordinate" title="Permalink to this heading">#</a></h3>
@@ -5279,9 +5280,9 @@ <h3>Fix time coordinate<a class="headerlink" href="#fix-time-coordinate" title="
     source:               Derived from EO satellite imagery
     time_coverage_end:    2019-12-31T23:59:59Z
     time_coverage_start:  1999-01-01T00:00:00Z
-    title:                Normalized Difference Vegetation Index: Long Term S...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-20837ce6-eb58-46fb-b7d2-d16df7a40a96' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-20837ce6-eb58-46fb-b7d2-d16df7a40a96' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 15680</li><li><span class='xr-has-index'>lon</span>: 40320</li><li><span class='xr-has-index'>time</span>: 36</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c43a2f77-4c18-4b3e-8f84-29d913b4857f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c43a2f77-4c18-4b3e-8f84-29d913b4857f' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.99 79.98 ... -59.98 -59.99</div><input id='attrs-fba56ea4-d2ee-4ab3-aeb4-b764237b9f9e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fba56ea4-d2ee-4ab3-aeb4-b764237b9f9e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9191a11-47bf-41a0-b45d-df85b72d30e8' class='xr-var-data-in' type='checkbox'><label for='data-b9191a11-47bf-41a0-b45d-df85b72d30e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lat</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 80.      ,  79.991071,  79.982143, ..., -59.973214, -59.982143,
-       -59.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-3d19503c-8fa5-4f19-bed0-f3d6d75404f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d19503c-8fa5-4f19-bed0-f3d6d75404f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ee06af8-fe16-4aa0-b478-ee2731553838' class='xr-var-data-in' type='checkbox'><label for='data-8ee06af8-fe16-4aa0-b478-ee2731553838' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lon</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-180.      , -179.991071, -179.982143, ...,  179.973214,  179.982143,
-        179.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-12-21</div><input id='attrs-5f09fc51-da76-4adb-bfa7-3a225aac486d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5f09fc51-da76-4adb-bfa7-3a225aac486d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77000138-a6a4-4795-84e1-3a5c9fa1c7ec' class='xr-var-data-in' type='checkbox'><label for='data-77000138-a6a4-4795-84e1-3a5c9fa1c7ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
+    title:                Normalized Difference Vegetation Index: Long Term S...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-534f52a9-c823-4959-bae0-c013bcfba7ba' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-534f52a9-c823-4959-bae0-c013bcfba7ba' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 15680</li><li><span class='xr-has-index'>lon</span>: 40320</li><li><span class='xr-has-index'>time</span>: 36</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e9d1fb92-26f5-4ad4-8fe2-48549a6dd118' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e9d1fb92-26f5-4ad4-8fe2-48549a6dd118' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.99 79.98 ... -59.98 -59.99</div><input id='attrs-7d497d79-0b21-4e52-a92b-f8641e63d631' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d497d79-0b21-4e52-a92b-f8641e63d631' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b9d7db0-b9ce-48e6-b760-312076ccf46b' class='xr-var-data-in' type='checkbox'><label for='data-6b9d7db0-b9ce-48e6-b760-312076ccf46b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lat</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 80.      ,  79.991071,  79.982143, ..., -59.973214, -59.982143,
+       -59.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-5ba8f8b0-8536-4e5c-b5d4-9c09b65bdd62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ba8f8b0-8536-4e5c-b5d4-9c09b65bdd62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8608f3d2-0fd9-45a9-b9c3-299f0ae0fb4e' class='xr-var-data-in' type='checkbox'><label for='data-8608f3d2-0fd9-45a9-b9c3-299f0ae0fb4e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>DIMENSION_LABELS :</span></dt><dd>lon</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-180.      , -179.991071, -179.982143, ...,  179.973214,  179.982143,
+        179.991071])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-12-21</div><input id='attrs-d835f6c4-9e88-4263-8a3e-966e60aab5a9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d835f6c4-9e88-4263-8a3e-966e60aab5a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bedc6f66-c7b5-4173-b87e-7af41093d953' class='xr-var-data-in' type='checkbox'><label for='data-bedc6f66-c7b5-4173-b87e-7af41093d953' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-11T00:00:00.000000000&#x27;,
        &#x27;2022-01-21T00:00:00.000000000&#x27;, &#x27;2022-02-01T00:00:00.000000000&#x27;,
        &#x27;2022-02-11T00:00:00.000000000&#x27;, &#x27;2022-02-21T00:00:00.000000000&#x27;,
        &#x27;2022-03-01T00:00:00.000000000&#x27;, &#x27;2022-03-11T00:00:00.000000000&#x27;,
@@ -5299,7 +5300,7 @@ <h3>Fix time coordinate<a class="headerlink" href="#fix-time-coordinate" title="
        &#x27;2022-11-01T00:00:00.000000000&#x27;, &#x27;2022-11-11T00:00:00.000000000&#x27;,
        &#x27;2022-11-21T00:00:00.000000000&#x27;, &#x27;2022-12-01T00:00:00.000000000&#x27;,
        &#x27;2022-12-11T00:00:00.000000000&#x27;, &#x27;2022-12-21T00:00:00.000000000&#x27;],
-      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8dcdae97-1419-46ae-9844-c272a0641de9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8dcdae97-1419-46ae-9844-c272a0641de9' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b3f38659-1381-4e06-ac09-9219291c83ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3f38659-1381-4e06-ac09-9219291c83ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-072e6d44-9c67-41bb-822a-53f96a99c0c4' class='xr-var-data-in' type='checkbox'><label for='data-072e6d44-9c67-41bb-822a-53f96a99c0c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GeoTransform :</span></dt><dd>-180.0000000000 0.0089285714 0.0 80.0000000000 0.0 -0.0089285714</dd><dt><span>_CoordinateAxisTypes :</span></dt><dd>GeoX GeoY</dd><dt><span>_CoordinateTransformType :</span></dt><dd>Projection</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>long_name :</span></dt><dd>coordinate reference system</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9108&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=object]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-56dee26a-92cb-44c7-a738-9b024cb4b325' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-56dee26a-92cb-44c7-a738-9b024cb4b325' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2acf025a-f17b-4caf-b8dc-5b395d2acc1d' class='xr-var-data-in' type='checkbox'><label for='data-2acf025a-f17b-4caf-b8dc-5b395d2acc1d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: maximum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Maximum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-198f0e22-db5b-4974-aef2-8377de334504' class='xr-section-summary-in' type='checkbox'  checked><label for='section-198f0e22-db5b-4974-aef2-8377de334504' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-68075a5d-6343-4042-b51b-54bf00e9af81' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68075a5d-6343-4042-b51b-54bf00e9af81' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec93780e-af1e-48ca-9eab-ae78e89076c7' class='xr-var-data-in' type='checkbox'><label for='data-ec93780e-af1e-48ca-9eab-ae78e89076c7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GeoTransform :</span></dt><dd>-180.0000000000 0.0089285714 0.0 80.0000000000 0.0 -0.0089285714</dd><dt><span>_CoordinateAxisTypes :</span></dt><dd>GeoX GeoY</dd><dt><span>_CoordinateTransformType :</span></dt><dd>Projection</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>long_name :</span></dt><dd>coordinate reference system</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9108&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=object]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-e8131be7-f508-4d14-9190-a45b4f790432' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e8131be7-f508-4d14-9190-a45b4f790432' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0db8562-acac-489d-9b55-6fa7a2910591' class='xr-var-data-in' type='checkbox'><label for='data-a0db8562-acac-489d-9b55-6fa7a2910591' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: maximum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Maximum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -5461,7 +5462,7 @@ <h3>Fix time coordinate<a class="headerlink" href="#fix-time-coordinate" title="
 </svg>
         </td>
     </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-296c12f3-cfbc-4401-b8ef-9994a11e93be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-296c12f3-cfbc-4401-b8ef-9994a11e93be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3db5ad1f-196b-46cd-8858-c6cc95757af5' class='xr-var-data-in' type='checkbox'><label for='data-3db5ad1f-196b-46cd-8858-c6cc95757af5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: mean</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Mean Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-9deb8fb5-a529-458c-8d53-4815e3dfb855' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9deb8fb5-a529-458c-8d53-4815e3dfb855' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-beb7f85a-d8c5-4248-894c-f608177279ac' class='xr-var-data-in' type='checkbox'><label for='data-beb7f85a-d8c5-4248-894c-f608177279ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: mean</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Mean Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -5623,7 +5624,7 @@ <h3>Fix time coordinate<a class="headerlink" href="#fix-time-coordinate" title="
 </svg>
         </td>
     </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>median</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-24264cc4-1086-400f-bcb9-ddcb1c0bb27e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24264cc4-1086-400f-bcb9-ddcb1c0bb27e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42803699-233c-4fb1-b7e4-0f437f9418b3' class='xr-var-data-in' type='checkbox'><label for='data-42803699-233c-4fb1-b7e4-0f437f9418b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: median</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Median Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>median</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-ce9587c4-5751-48d3-8537-df53fa52517a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce9587c4-5751-48d3-8537-df53fa52517a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fcc6134c-7e40-4520-a9c7-c5a8a16a61ad' class='xr-var-data-in' type='checkbox'><label for='data-fcc6134c-7e40-4520-a9c7-c5a8a16a61ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: median</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Median Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -5785,7 +5786,7 @@ <h3>Fix time coordinate<a class="headerlink" href="#fix-time-coordinate" title="
 </svg>
         </td>
     </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-d363e8bb-e4ee-429b-9325-e1ba4d4f8b0d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d363e8bb-e4ee-429b-9325-e1ba4d4f8b0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d55e417-7aff-49d6-901b-09cb0aeae88a' class='xr-var-data-in' type='checkbox'><label for='data-1d55e417-7aff-49d6-901b-09cb0aeae88a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: minimum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Minimum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-9f80464b-bc9e-4141-a736-a35fe46ac694' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f80464b-bc9e-4141-a736-a35fe46ac694' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84a3ec80-8d77-48eb-920f-a0210c50fb86' class='xr-var-data-in' type='checkbox'><label for='data-84a3ec80-8d77-48eb-920f-a0210c50fb86' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: minimum</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Minimum Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -5947,7 +5948,7 @@ <h3>Fix time coordinate<a class="headerlink" href="#fix-time-coordinate" title="
 </svg>
         </td>
     </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nobs</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-35f06633-c2c4-4f8c-9481-52ac829edf63' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-35f06633-c2c4-4f8c-9481-52ac829edf63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-170718d7-1831-4e63-a44d-f09ba1b2fcab' class='xr-var-data-in' type='checkbox'><label for='data-170718d7-1831-4e63-a44d-f09ba1b2fcab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index number_of_observations</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[1, 250]</dd></dl></div><div class='xr-var-data'><table>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nobs</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-e191dddb-a190-459c-9e0d-f57c3ee58b85' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e191dddb-a190-459c-9e0d-f57c3ee58b85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b74f217-8008-4f73-840d-1c7908574d57' class='xr-var-data-in' type='checkbox'><label for='data-1b74f217-8008-4f73-840d-1c7908574d57' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index number_of_observations</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[1, 250]</dd></dl></div><div class='xr-var-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -6109,7 +6110,7 @@ <h3>Fix time coordinate<a class="headerlink" href="#fix-time-coordinate" title="
 </svg>
         </td>
     </tr>
-</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stdev</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-f5257b4b-5464-4103-939d-6bac9d5187be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f5257b4b-5464-4103-939d-6bac9d5187be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-954114f1-e9b0-4d8c-8481-d50d3c3c91ff' class='xr-var-data-in' type='checkbox'><label for='data-954114f1-e9b0-4d8c-8481-d50d3c3c91ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: standard_deviation</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Standard deviation Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stdev</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1207, 3102), meta=np.ndarray&gt;</div><input id='attrs-bfa6cbd1-ef3a-4e0f-8424-8aee3d8ff81b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfa6cbd1-ef3a-4e0f-8424-8aee3d8ff81b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f63ea175-ba30-4f74-84b4-179135a37f1c' class='xr-var-data-in' type='checkbox'><label for='data-f63ea175-ba30-4f74-84b4-179135a37f1c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: standard_deviation</dd><dt><span>flag_meanings :</span></dt><dd>sea no_data</dd><dt><span>flag_values :</span></dt><dd>[254, 255]</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Standard deviation Normalized Difference Vegetation Index over time period</dd><dt><span>standard_name :</span></dt><dd>normalized_difference_vegetation_index</dd><dt><span>units :</span></dt><dd> </dd><dt><span>valid_range :</span></dt><dd>[0, 250]</dd></dl></div><div class='xr-var-data'><table>
     <tr>
         <td>
             <table style="border-collapse: collapse;">
@@ -6271,7 +6272,7 @@ <h3>Fix time coordinate<a class="headerlink" href="#fix-time-coordinate" title="
 </svg>
         </td>
     </tr>
-</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-0cb54c3c-dc40-4bb3-b56f-188520fd91d9' class='xr-section-summary-in' type='checkbox'  ><label for='section-0cb54c3c-dc40-4bb3-b56f-188520fd91d9' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4dd6980e-c16d-4876-8897-10326e3e8c4d' class='xr-index-data-in' type='checkbox'/><label for='index-4dd6980e-c16d-4876-8897-10326e3e8c4d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               80.0,   79.99107142857143,   79.98214285714286,
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-7850e243-bb6b-480f-8f8e-43550c1b6921' class='xr-section-summary-in' type='checkbox'  ><label for='section-7850e243-bb6b-480f-8f8e-43550c1b6921' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-02d02cae-f1f6-4075-b7f2-eea4149ae61c' class='xr-index-data-in' type='checkbox'/><label for='index-02d02cae-f1f6-4075-b7f2-eea4149ae61c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               80.0,   79.99107142857143,   79.98214285714286,
          79.97321428571429,   79.96428571428572,   79.95535714285715,
          79.94642857142858,   79.93750000000001,   79.92857142857144,
          79.91964285714288,
@@ -6280,7 +6281,7 @@ <h3>Fix time coordinate<a class="headerlink" href="#fix-time-coordinate" title="
         -59.93749999996817,  -59.94642857139675, -59.955357142825335,
         -59.96428571425389, -59.973214285682445,  -59.98214285711103,
         -59.99107142853961],
-      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=15680))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-af9e7f7d-1f15-48c7-9ffd-64a845c060b1' class='xr-index-data-in' type='checkbox'/><label for='index-af9e7f7d-1f15-48c7-9ffd-64a845c060b1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -180.0, -179.99107142857142, -179.98214285714283,
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=15680))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-51be4865-89ec-4376-a276-6974d63caaa5' class='xr-index-data-in' type='checkbox'/><label for='index-51be4865-89ec-4376-a276-6974d63caaa5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -180.0, -179.99107142857142, -179.98214285714283,
        -179.97321428571425, -179.96428571428567, -179.95535714285708,
         -179.9464285714285, -179.93749999999991, -179.92857142857133,
        -179.91964285714275,
@@ -6289,7 +6290,7 @@ <h3>Fix time coordinate<a class="headerlink" href="#fix-time-coordinate" title="
           179.937500000491,  179.94642857191963,  179.95535714334824,
          179.9642857147768,  179.97321428620535,  179.98214285763396,
         179.99107142906257],
-      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=40320))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-41d38bfc-933b-493b-b79d-a25561d4af31' class='xr-index-data-in' type='checkbox'/><label for='index-41d38bfc-933b-493b-b79d-a25561d4af31' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=40320))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-06f05afa-7597-4fbc-942f-8a74f0a1be03' class='xr-index-data-in' type='checkbox'/><label for='index-06f05afa-7597-4fbc-942f-8a74f0a1be03' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-01-01&#x27;, &#x27;2022-01-11&#x27;, &#x27;2022-01-21&#x27;, &#x27;2022-02-01&#x27;,
                &#x27;2022-02-11&#x27;, &#x27;2022-02-21&#x27;, &#x27;2022-03-01&#x27;, &#x27;2022-03-11&#x27;,
                &#x27;2022-03-21&#x27;, &#x27;2022-04-01&#x27;, &#x27;2022-04-11&#x27;, &#x27;2022-04-21&#x27;,
                &#x27;2022-05-01&#x27;, &#x27;2022-05-11&#x27;, &#x27;2022-05-21&#x27;, &#x27;2022-06-01&#x27;,
@@ -6298,7 +6299,7 @@ <h3>Fix time coordinate<a class="headerlink" href="#fix-time-coordinate" title="
                &#x27;2022-09-01&#x27;, &#x27;2022-09-11&#x27;, &#x27;2022-09-21&#x27;, &#x27;2022-10-01&#x27;,
                &#x27;2022-10-11&#x27;, &#x27;2022-10-21&#x27;, &#x27;2022-11-01&#x27;, &#x27;2022-11-11&#x27;,
                &#x27;2022-11-21&#x27;, &#x27;2022-12-01&#x27;, &#x27;2022-12-11&#x27;, &#x27;2022-12-21&#x27;],
-              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cc35d9da-75e2-49d1-ae80-5d0b0b7d4fc0' class='xr-section-summary-in' type='checkbox'  ><label for='section-cc35d9da-75e2-49d1-ae80-5d0b0b7d4fc0' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>archive_facility :</span></dt><dd>VITO</dd><dt><span>copyright :</span></dt><dd>Copernicus Service information 2021</dd><dt><span>history :</span></dt><dd>2021-03-01 - Processing line NDVI LTS</dd><dt><span>identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-0101_GLOBE_V3.0.1</dd><dt><span>institution :</span></dt><dd>VITO NV</dd><dt><span>long_name :</span></dt><dd>Normalized Difference Vegetation Index</dd><dt><span>orbit_type :</span></dt><dd>LEO</dd><dt><span>parent_identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all</dd><dt><span>platform :</span></dt><dd>SPOT-4, SPOT-5, Proba-V</dd><dt><span>processing_level :</span></dt><dd>L4</dd><dt><span>processing_mode :</span></dt><dd>Offline</dd><dt><span>product_version :</span></dt><dd>V3.0.1</dd><dt><span>references :</span></dt><dd>https://land.copernicus.eu/global/products/ndvi</dd><dt><span>sensor :</span></dt><dd>VEGETATION-1, VEGETATION-2, VEGETATION</dd><dt><span>source :</span></dt><dd>Derived from EO satellite imagery</dd><dt><span>time_coverage_end :</span></dt><dd>2019-12-31T23:59:59Z</dd><dt><span>time_coverage_start :</span></dt><dd>1999-01-01T00:00:00Z</dd><dt><span>title :</span></dt><dd>Normalized Difference Vegetation Index: Long Term Statistics 1KM: GLOBE 1999-2019 0101</dd></dl></div></li></ul></div></div></div></div>
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8fc83787-b3f1-408c-850f-020305599c0c' class='xr-section-summary-in' type='checkbox'  ><label for='section-8fc83787-b3f1-408c-850f-020305599c0c' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>archive_facility :</span></dt><dd>VITO</dd><dt><span>copyright :</span></dt><dd>Copernicus Service information 2021</dd><dt><span>history :</span></dt><dd>2021-03-01 - Processing line NDVI LTS</dd><dt><span>identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-0101_GLOBE_V3.0.1</dd><dt><span>institution :</span></dt><dd>VITO NV</dd><dt><span>long_name :</span></dt><dd>Normalized Difference Vegetation Index</dd><dt><span>orbit_type :</span></dt><dd>LEO</dd><dt><span>parent_identifier :</span></dt><dd>urn:cgls:global:ndvi_stats_all</dd><dt><span>platform :</span></dt><dd>SPOT-4, SPOT-5, Proba-V</dd><dt><span>processing_level :</span></dt><dd>L4</dd><dt><span>processing_mode :</span></dt><dd>Offline</dd><dt><span>product_version :</span></dt><dd>V3.0.1</dd><dt><span>references :</span></dt><dd>https://land.copernicus.eu/global/products/ndvi</dd><dt><span>sensor :</span></dt><dd>VEGETATION-1, VEGETATION-2, VEGETATION</dd><dt><span>source :</span></dt><dd>Derived from EO satellite imagery</dd><dt><span>time_coverage_end :</span></dt><dd>2019-12-31T23:59:59Z</dd><dt><span>time_coverage_start :</span></dt><dd>1999-01-01T00:00:00Z</dd><dt><span>title :</span></dt><dd>Normalized Difference Vegetation Index: Long Term Statistics 1KM: GLOBE 1999-2019 0101</dd></dl></div></li></ul></div></div></div></div>
 </div>
 </section>
 <section id="clip-lts-over-lombardia">
diff --git a/reports/part3/chunking_introduction.err.log b/reports/part3/chunking_introduction.err.log
new file mode 100644
index 0000000..aefd015
--- /dev/null
+++ b/reports/part3/chunking_introduction.err.log
@@ -0,0 +1,31 @@
+Traceback (most recent call last):
+  File "/home/runner/micromamba/envs/bids23/lib/python3.11/site-packages/jupyter_cache/executors/utils.py", line 58, in single_nb_execution
+    executenb(
+  File "/home/runner/micromamba/envs/bids23/lib/python3.11/site-packages/nbclient/client.py", line 1305, in execute
+    return NotebookClient(nb=nb, resources=resources, km=km, **kwargs).execute()
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/runner/micromamba/envs/bids23/lib/python3.11/site-packages/jupyter_core/utils/__init__.py", line 173, in wrapped
+    return loop.run_until_complete(inner)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/runner/micromamba/envs/bids23/lib/python3.11/asyncio/base_events.py", line 653, in run_until_complete
+    return future.result()
+           ^^^^^^^^^^^^^^^
+  File "/home/runner/micromamba/envs/bids23/lib/python3.11/site-packages/nbclient/client.py", line 705, in async_execute
+    await self.async_execute_cell(
+  File "/home/runner/micromamba/envs/bids23/lib/python3.11/site-packages/nbclient/client.py", line 1058, in async_execute_cell
+    await self._check_raise_for_error(cell, cell_index, exec_reply)
+  File "/home/runner/micromamba/envs/bids23/lib/python3.11/site-packages/nbclient/client.py", line 914, in _check_raise_for_error
+    raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)
+nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:
+------------------
+sentinel2_l2a
+------------------
+
+
+---------------------------------------------------------------------------
+NameError                                 Traceback (most recent call last)
+Cell In[3], line 1
+----> 1 sentinel2_l2a
+
+NameError: name 'sentinel2_l2a' is not defined
+
diff --git a/searchindex.js b/searchindex.js
index 31ff635..d7c765f 100644
--- a/searchindex.js
+++ b/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"docnames": ["about/timeline", "afterword/envds-book", "afterword/pythia", "afterword/resources", "before/EOSC", "before/copernicus", "before/openeo", "before/setup", "intro", "part1/motivation", "part1/overview", "part1/visualization", "part1/xarray_pitfalls", "part2/advanced_workflows", "part2/agenda_and_links", "part3/advanced_udf", "part3/advanced_ufunc", "part3/advanced_workflow", "part3/chunking_introduction", "part3/data_discovery", "part3/data_exploitability_openEO", "part3/data_exploitability_pangeo", "part3/scaling_dask"], "filenames": ["about/timeline.md", "afterword/envds-book.md", "afterword/pythia.md", "afterword/resources.md", "before/EOSC.md", "before/copernicus.md", "before/openeo.md", "before/setup.md", "intro.md", "part1/motivation.md", "part1/overview.md", "part1/visualization.ipynb", "part1/xarray_pitfalls.ipynb", "part2/advanced_workflows.md", "part2/agenda_and_links.md", "part3/advanced_udf.ipynb", "part3/advanced_ufunc.ipynb", "part3/advanced_workflow.ipynb", "part3/chunking_introduction.ipynb", "part3/data_discovery.md", "part3/data_exploitability_openEO.ipynb", "part3/data_exploitability_pangeo.ipynb", "part3/scaling_dask.ipynb"], "titles": ["Timeline of the workshops", "Environmental Data Science Book", "Project Pythia", "Join the community!", "Pangeo&#64;EOSC", "Copernicus Data Space Ecosystem", "OpenEO", "Setup", "Welcome \ud83d\udc4b", "Introduction and Motivation", "Overview of the Pangeo ecosystem", "Interactive plotting with HoloViews", "Handling multi-dimensional arrays with xarray", "Case 1 Rank composites", "Part-2: OpenEO (Comment: Intro Session)", "OpenEO - User Defined Functions", "OpenEO - User Functions", "OpenEO - Advanced Workflows", "Data chunking with zarr and kerchunk.", "Data discoverability and searchability", "Hands-on \u201cThe Easy-peasy life with OpenEO\u201d", "How to exploit data on Pangeo", "Parallel computing with Dask"], "terms": {"The": [0, 1, 2, 3, 5, 6, 7, 8, 11, 12, 17, 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