python/RankComposites/rank_composites.ipynb

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    "# Rank composites\n",
    "\n",
    "Optical satellite imagery contains gaps due to clouds, and the observation scenario. Many methods rely on having gap-free data available at regular time intervals. The most common technique to achieve this is to combine pixels from different observations, which is also referred to as compositing.\n",
    "\n",
    "Various compositing approaches exist, in this notebook, we demonstrate ‘rank composites’ or more specifically the ‘max NDVI’ composite. A rank composite uses a single ‘rank band’ to decide if pixels of other bands are included in the composite. The advantage of rank composites over compositing per band is that the spectral signal represented by the different bands has been observed in reality in a single observation, and is not a combination of spectral values that occurred at different points in time.\n",
    "\n",
    "This method is used in various peer reviewed publications, and some of its properties have been validated based on specific sensors: https://www.tandfonline.com/doi/abs/10.1080/01431168608948945\n",
    "\n",
    "In this case the 'rank band' is a simple NDVI, which we 'score' based on the maximum value. The rank band can also be a combination of values leading to a more complex score, such as distance to cloud and observation angles. This variant is called a 'best available pixel' composite. (https://doi.org/10.1080/07038992.2014.945827)\n",
    "\n",
    "## openEO implementation\n",
    "\n",
    "The steps to implement this method in openEO are relatively simple, but may be different from the steps in a 'traditional' programming language:\n",
    "\n",
    "1. We load and compute the rank band separately\n",
    "2. The rank band is converted into a mask, retaining only pixels that we want to select\n",
    "3. A datacube with raw bands is loaded, and the rank band mask is applied to it\n",
    "4. aggregate_temporal(_period) is used to create a composite at regular intervals if needed\n",
    "\n",
    "Most methods require composites for multiple time periods as input. For instance, one composite per month, or every 10 days. We can compute these in one process graph, using apply_neighborhood, so that the result is also an immediate input for further processing.\n"
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    "spatial_extent = {'west': 4.45, 'east': 4.50, 'south': 51.16, 'north': 51.17, 'crs': 'epsg:4326'}"
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    "import openeo\n",
    "import xarray\n",
    "import numpy as np\n",
    "import io\n",
    "import requests\n",
    "\n",
    "import panel as pn\n",
    "\n",
    "import pyproj\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "\n",
    "%matplotlib inline"
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    "We first create a binary cloud mask, as we don't want to consider clouded pixels. This is also a good way to avoid loading too much data, which is costly."
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      "/home/driesj/python/openeo-python-client/openeo/rest/connection.py:1133: UserWarning: SENTINEL2_L2A property filtering with properties that are undefined in the collection metadata (summaries): eo:cloud_cover.\n",
      "  return DataCube.load_collection(\n"
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    "scl = c.load_collection(\n",
    "    \"SENTINEL2_L2A\",\n",
    "    temporal_extent = [\"2022-06-04\", \"2022-08-01\"],\n",
    "    bands = [\"SCL\"],\n",
    "    max_cloud_cover=95\n",
    ")\n",
    "\n",
    "cloud_mask = scl.process(\n",
    "    \"to_scl_dilation_mask\",\n",
    "    data=scl,\n",
    "    kernel1_size=17, kernel2_size=77,\n",
    "    mask1_values=[2, 4, 5, 6, 7],\n",
    "    mask2_values=[3, 8, 9, 10, 11],\n",
    "    erosion_kernel_size=3)\n",
    "\n"
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    "Now we load the bands required to compute NDVI, apply the cloud mask, and compute NDVI. \n",
    "The NDVI will be our 'rank band' in this example."
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    "ndvi_bands = c.load_collection(\n",
    "    \"SENTINEL2_L2A\",\n",
    "    temporal_extent = [\"2022-06-04\", \"2022-08-01\"],\n",
    "    bands = [\"B04\", \"B08\", \"SCL\"],\n",
    "    max_cloud_cover=95\n",
    ")\n",
    "\n",
    "ndvi_bands = ndvi_bands.mask(cloud_mask)\n",
    "\n",
    "ndvi = ndvi_bands.ndvi(nir=\"B08\",red=\"B04\")"
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    "The next step is the most difficult one, and constructs the final mask that will be used to load the full datacube, but with only the observations where the NDVI is equal to the maximum.\n",
    "\n",
    "We first create a function that computes the maximum NDVI from a series of values, and then loops again over those values to set values to 1 if they are equal to the maximum, and zero otherwise.\n",
    "\n",
    "The apply_neighborhood process is used here to define the groups of NDVI values on which we want to run this function. We want to create multiple monthly max-NDVI composites, so we specify that the size of groups along the time dimension should correspond to 1 month. \n",
    "Apply_neighborhood is one of the more complex processes, but once you understand it, you'll notice it's quite versatile and useful."
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    "def max_ndvi_selection(ndvi):\n",
    "    max_ndvi = ndvi.max()\n",
    "    return ndvi.array_apply(lambda x:x!=max_ndvi)\n",
    "\n",
    "rank_mask = ndvi.apply_neighborhood(\n",
    "        max_ndvi_selection,\n",
    "        size=[{'dimension': 'x', 'unit': 'px', 'value': 1}, {'dimension': 'y', 'unit': 'px', 'value': 1},\n",
    "              {'dimension': 't', 'value': \"month\"}],\n",
    "        overlap=[]\n",
    "    )"
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    "At this point, we download our mask for inspection. This is just an intermediate result, and is not needed in a real use case."
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       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (t: 12, x: 352, y: 119)\n",
       "Coordinates:\n",
       "  * t        (t) datetime64[ns] 2022-06-04 2022-06-11 ... 2022-07-24 2022-07-29\n",
       "  * x        (x) float64 6.014e+05 6.014e+05 6.014e+05 ... 6.049e+05 6.049e+05\n",
       "  * y        (y) float64 5.67e+06 5.67e+06 5.67e+06 ... 5.669e+06 5.669e+06\n",
       "Data variables:\n",
       "    crs      |S1 ...\n",
       "    var      (t, y, x) uint8 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.9\n",
       "    institution:  openEO platform - Geotrellis backend: 0.16.2a1\n",
       "    description:  \n",
       "    title:        </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-2beb1746-78dd-475b-8d29-ff95fad9246b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2beb1746-78dd-475b-8d29-ff95fad9246b' 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>: 12</li><li><span class='xr-has-index'>x</span>: 352</li><li><span class='xr-has-index'>y</span>: 119</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f4c336e1-9a71-4671-9d2d-60e57342d0f8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f4c336e1-9a71-4671-9d2d-60e57342d0f8' 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'>2022-06-04 ... 2022-07-29</div><input id='attrs-8e67c8a5-ff22-4b02-b997-ee8bc2524245' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e67c8a5-ff22-4b02-b997-ee8bc2524245' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c51cc291-c0af-4443-a9a0-f353671b969e' class='xr-var-data-in' type='checkbox'><label for='data-c51cc291-c0af-4443-a9a0-f353671b969e' 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;2022-06-04T00:00:00.000000000&#x27;, &#x27;2022-06-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-06-14T00:00:00.000000000&#x27;, &#x27;2022-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-06-29T00:00:00.000000000&#x27;, &#x27;2022-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-07-04T00:00:00.000000000&#x27;, &#x27;2022-07-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-07-16T00:00:00.000000000&#x27;, &#x27;2022-07-19T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-07-24T00:00:00.000000000&#x27;, &#x27;2022-07-29T00:00:00.000000000&#x27;],\n",
       "      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'>6.014e+05 6.014e+05 ... 6.049e+05</div><input id='attrs-0821d1e9-bc95-4a71-a7cd-38bb0068c1f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0821d1e9-bc95-4a71-a7cd-38bb0068c1f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a42aac3-4849-4ee3-81e6-6a3e0106cfa0' class='xr-var-data-in' type='checkbox'><label for='data-5a42aac3-4849-4ee3-81e6-6a3e0106cfa0' 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 of projection</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([601375., 601385., 601395., ..., 604865., 604875., 604885.])</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'>5.67e+06 5.67e+06 ... 5.669e+06</div><input id='attrs-9968f15d-30e7-46a4-af7e-f5992fb3b9d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9968f15d-30e7-46a4-af7e-f5992fb3b9d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f609bb33-3890-47c0-8acb-a177ca3fb9a9' class='xr-var-data-in' type='checkbox'><label for='data-f609bb33-3890-47c0-8acb-a177ca3fb9a9' 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 of projection</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([5669795., 5669785., 5669775., 5669765., 5669755., 5669745., 5669735.,\n",
       "       5669725., 5669715., 5669705., 5669695., 5669685., 5669675., 5669665.,\n",
       "       5669655., 5669645., 5669635., 5669625., 5669615., 5669605., 5669595.,\n",
       "       5669585., 5669575., 5669565., 5669555., 5669545., 5669535., 5669525.,\n",
       "       5669515., 5669505., 5669495., 5669485., 5669475., 5669465., 5669455.,\n",
       "       5669445., 5669435., 5669425., 5669415., 5669405., 5669395., 5669385.,\n",
       "       5669375., 5669365., 5669355., 5669345., 5669335., 5669325., 5669315.,\n",
       "       5669305., 5669295., 5669285., 5669275., 5669265., 5669255., 5669245.,\n",
       "       5669235., 5669225., 5669215., 5669205., 5669195., 5669185., 5669175.,\n",
       "       5669165., 5669155., 5669145., 5669135., 5669125., 5669115., 5669105.,\n",
       "       5669095., 5669085., 5669075., 5669065., 5669055., 5669045., 5669035.,\n",
       "       5669025., 5669015., 5669005., 5668995., 5668985., 5668975., 5668965.,\n",
       "       5668955., 5668945., 5668935., 5668925., 5668915., 5668905., 5668895.,\n",
       "       5668885., 5668875., 5668865., 5668855., 5668845., 5668835., 5668825.,\n",
       "       5668815., 5668805., 5668795., 5668785., 5668775., 5668765., 5668755.,\n",
       "       5668745., 5668735., 5668725., 5668715., 5668705., 5668695., 5668685.,\n",
       "       5668675., 5668665., 5668655., 5668645., 5668635., 5668625., 5668615.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6ec4a221-0379-4629-b44d-bdea77a26653' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6ec4a221-0379-4629-b44d-bdea77a26653' 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-c19dda86-ec4e-4732-9ef9-b605c0b8db43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c19dda86-ec4e-4732-9ef9-b605c0b8db43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-682a9fd8-d327-470f-841b-527260539abc' class='xr-var-data-in' type='checkbox'><label for='data-682a9fd8-d327-470f-841b-527260539abc' 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>PROJCS[&quot;WGS 84 / UTM zone 31N&quot;, 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;]], PROJECTION[&quot;Transverse_Mercator&quot;, AUTHORITY[&quot;EPSG&quot;,&quot;9807&quot;]], PARAMETER[&quot;central_meridian&quot;, 3.0], PARAMETER[&quot;latitude_of_origin&quot;, 0.0], PARAMETER[&quot;scale_factor&quot;, 0.9996], PARAMETER[&quot;false_easting&quot;, 500000.0], PARAMETER[&quot;false_northing&quot;, 0.0], UNIT[&quot;m&quot;, 1.0], AXIS[&quot;Easting&quot;, EAST], AXIS[&quot;Northing&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;32631&quot;]]</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 31N&quot;, 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;]], PROJECTION[&quot;Transverse_Mercator&quot;, AUTHORITY[&quot;EPSG&quot;,&quot;9807&quot;]], PARAMETER[&quot;central_meridian&quot;, 3.0], PARAMETER[&quot;latitude_of_origin&quot;, 0.0], PARAMETER[&quot;scale_factor&quot;, 0.9996], PARAMETER[&quot;false_easting&quot;, 500000.0], PARAMETER[&quot;false_northing&quot;, 0.0], UNIT[&quot;m&quot;, 1.0], AXIS[&quot;Easting&quot;, EAST], AXIS[&quot;Northing&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;32631&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>var</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-f32777e7-60ae-4129-be08-af4bf7c45acb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f32777e7-60ae-4129-be08-af4bf7c45acb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1af2387c-d56b-4978-adf5-47b16dd5d2a5' class='xr-var-data-in' type='checkbox'><label for='data-1af2387c-d56b-4978-adf5-47b16dd5d2a5' 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>var</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>[502656 values with dtype=uint8]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5b129007-5337-4916-a1dc-9a142c87b9e8' class='xr-section-summary-in' type='checkbox'  ><label for='section-5b129007-5337-4916-a1dc-9a142c87b9e8' 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-40b2061d-1613-4cbc-a3d8-183135ca0d67' class='xr-index-data-in' type='checkbox'/><label for='index-40b2061d-1613-4cbc-a3d8-183135ca0d67' 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;2022-06-04&#x27;, &#x27;2022-06-11&#x27;, &#x27;2022-06-14&#x27;, &#x27;2022-06-16&#x27;,\n",
       "               &#x27;2022-06-29&#x27;, &#x27;2022-07-01&#x27;, &#x27;2022-07-04&#x27;, &#x27;2022-07-11&#x27;,\n",
       "               &#x27;2022-07-16&#x27;, &#x27;2022-07-19&#x27;, &#x27;2022-07-24&#x27;, &#x27;2022-07-29&#x27;],\n",
       "              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-18537029-2180-4f18-b65f-e4e2dee34f6f' class='xr-index-data-in' type='checkbox'/><label for='index-18537029-2180-4f18-b65f-e4e2dee34f6f' 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(Float64Index([601375.0, 601385.0, 601395.0, 601405.0, 601415.0, 601425.0,\n",
       "              601435.0, 601445.0, 601455.0, 601465.0,\n",
       "              ...\n",
       "              604795.0, 604805.0, 604815.0, 604825.0, 604835.0, 604845.0,\n",
       "              604855.0, 604865.0, 604875.0, 604885.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=352))</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-133ef4d2-2fd6-486e-b5b0-96eb18fae075' class='xr-index-data-in' type='checkbox'/><label for='index-133ef4d2-2fd6-486e-b5b0-96eb18fae075' 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(Float64Index([5669795.0, 5669785.0, 5669775.0, 5669765.0, 5669755.0, 5669745.0,\n",
       "              5669735.0, 5669725.0, 5669715.0, 5669705.0,\n",
       "              ...\n",
       "              5668705.0, 5668695.0, 5668685.0, 5668675.0, 5668665.0, 5668655.0,\n",
       "              5668645.0, 5668635.0, 5668625.0, 5668615.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=119))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0e1d6380-5622-4965-8705-7510c1824d52' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0e1d6380-5622-4965-8705-7510c1824d52' class='xr-section-summary' >Attributes: <span>(4)</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-1.9</dd><dt><span>institution :</span></dt><dd>openEO platform - Geotrellis backend: 0.16.2a1</dd><dt><span>description :</span></dt><dd></dd><dt><span>title :</span></dt><dd></dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (t: 12, x: 352, y: 119)\n",
       "Coordinates:\n",
       "  * t        (t) datetime64[ns] 2022-06-04 2022-06-11 ... 2022-07-24 2022-07-29\n",
       "  * x        (x) float64 6.014e+05 6.014e+05 6.014e+05 ... 6.049e+05 6.049e+05\n",
       "  * y        (y) float64 5.67e+06 5.67e+06 5.67e+06 ... 5.669e+06 5.669e+06\n",
       "Data variables:\n",
       "    crs      |S1 ...\n",
       "    var      (t, y, x) uint8 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.9\n",
       "    institution:  openEO platform - Geotrellis backend: 0.16.2a1\n",
       "    description:  \n",
       "    title:        "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask_ds = xarray.open_dataset('the_mask.nc')\n",
    "mask_ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We inspect the mask by filtering out nodata and plotting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<xarray.plot.facetgrid.FacetGrid at 0x7f72f4674ed0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1300x900 with 13 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mask_ds['var'] = mask_ds['var'].where(mask_ds['var']!=129)\n",
    "mask_ds['var'].plot(vmin=0,vmax=1,col=\"t\",col_wrap=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating and downloading your composite\n",
    "\n",
    "Now it's time to create and load the actual composite, which is very simply once a compositing mask has been created.\n",
    "It's very important in this step to use the exact same 'load_collection' paratemers as were used to create the mask(s), to have a correct output.\n",
    "Note that we still use aggregate_temporal_period, which has 2 effects:\n",
    "- after masking, observations will still have their original dates, this process will generate equitemporal intervals.\n",
    "- In the case where multiple observations have the same NDVI value, the first observation will be retained."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rgb_bands = c.load_collection(\n",
    "    \"SENTINEL2_L2A\",\n",
    "    temporal_extent = [\"2022-06-04\", \"2022-08-01\"],\n",
    "    bands = [\"B02\", \"B03\",\"B04\"],\n",
    "    max_cloud_cover=95\n",
    ")\n",
    "\n",
    "composite = rgb_bands.mask(rank_mask).aggregate_temporal_period(\"month\",\"first\")\n",
    "\n",
    "composite.filter_bbox(spatial_extent).execute_batch(\"composite.nc\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
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       "\n",
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       "\n",
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       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
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       "\n",
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       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
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       "\n",
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       "  padding-bottom: 6px;\n",
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       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
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       "\n",
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       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
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       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
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       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
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       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
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       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
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       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
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       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
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       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (t: 2, x: 352, y: 119)\n",
       "Coordinates:\n",
       "  * t        (t) datetime64[ns] 2022-06-01 2022-07-01\n",
       "  * x        (x) float64 6.014e+05 6.014e+05 6.014e+05 ... 6.049e+05 6.049e+05\n",
       "  * y        (y) float64 5.67e+06 5.67e+06 5.67e+06 ... 5.669e+06 5.669e+06\n",
       "Data variables:\n",
       "    crs      |S1 ...\n",
       "    B02      (t, y, x) float32 ...\n",
       "    B03      (t, y, x) float32 ...\n",
       "    B04      (t, y, x) float32 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.9\n",
       "    institution:  openEO platform - Geotrellis backend: 0.16.2a1\n",
       "    description:  \n",
       "    title:        </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-c83b7e72-dc12-4cb9-aa88-b28e41f8a489' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c83b7e72-dc12-4cb9-aa88-b28e41f8a489' 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>: 2</li><li><span class='xr-has-index'>x</span>: 352</li><li><span class='xr-has-index'>y</span>: 119</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-bc53149f-46d6-4f4b-be6f-36d826b2310e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bc53149f-46d6-4f4b-be6f-36d826b2310e' 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'>2022-06-01 2022-07-01</div><input id='attrs-74dd56ae-15c3-46d6-b700-8ac8dd7c9e2a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74dd56ae-15c3-46d6-b700-8ac8dd7c9e2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b8f8e05-9544-4e67-8dbe-475b0300ce1f' class='xr-var-data-in' type='checkbox'><label for='data-0b8f8e05-9544-4e67-8dbe-475b0300ce1f' 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;2022-06-01T00:00:00.000000000&#x27;, &#x27;2022-07-01T00:00:00.000000000&#x27;],\n",
       "      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'>6.014e+05 6.014e+05 ... 6.049e+05</div><input id='attrs-a2e98fd3-7679-4158-995f-784a805e4355' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2e98fd3-7679-4158-995f-784a805e4355' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8c0faf7-8aed-4eb4-bc42-45cc72ee2b3c' class='xr-var-data-in' type='checkbox'><label for='data-d8c0faf7-8aed-4eb4-bc42-45cc72ee2b3c' 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 of projection</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([601375., 601385., 601395., ..., 604865., 604875., 604885.])</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'>5.67e+06 5.67e+06 ... 5.669e+06</div><input id='attrs-5d3b210a-e98d-472f-8098-aadb589b51ec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d3b210a-e98d-472f-8098-aadb589b51ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3d6155d-f03b-4452-ba2f-c5cf418c2921' class='xr-var-data-in' type='checkbox'><label for='data-e3d6155d-f03b-4452-ba2f-c5cf418c2921' 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 of projection</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([5669795., 5669785., 5669775., 5669765., 5669755., 5669745., 5669735.,\n",
       "       5669725., 5669715., 5669705., 5669695., 5669685., 5669675., 5669665.,\n",
       "       5669655., 5669645., 5669635., 5669625., 5669615., 5669605., 5669595.,\n",
       "       5669585., 5669575., 5669565., 5669555., 5669545., 5669535., 5669525.,\n",
       "       5669515., 5669505., 5669495., 5669485., 5669475., 5669465., 5669455.,\n",
       "       5669445., 5669435., 5669425., 5669415., 5669405., 5669395., 5669385.,\n",
       "       5669375., 5669365., 5669355., 5669345., 5669335., 5669325., 5669315.,\n",
       "       5669305., 5669295., 5669285., 5669275., 5669265., 5669255., 5669245.,\n",
       "       5669235., 5669225., 5669215., 5669205., 5669195., 5669185., 5669175.,\n",
       "       5669165., 5669155., 5669145., 5669135., 5669125., 5669115., 5669105.,\n",
       "       5669095., 5669085., 5669075., 5669065., 5669055., 5669045., 5669035.,\n",
       "       5669025., 5669015., 5669005., 5668995., 5668985., 5668975., 5668965.,\n",
       "       5668955., 5668945., 5668935., 5668925., 5668915., 5668905., 5668895.,\n",
       "       5668885., 5668875., 5668865., 5668855., 5668845., 5668835., 5668825.,\n",
       "       5668815., 5668805., 5668795., 5668785., 5668775., 5668765., 5668755.,\n",
       "       5668745., 5668735., 5668725., 5668715., 5668705., 5668695., 5668685.,\n",
       "       5668675., 5668665., 5668655., 5668645., 5668635., 5668625., 5668615.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-47dc5ff9-fc0b-4885-a210-664bf3c7b12e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-47dc5ff9-fc0b-4885-a210-664bf3c7b12e' class='xr-section-summary' >Data variables: <span>(4)</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-e34a532d-bb95-4d89-9247-9929bdbd92d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e34a532d-bb95-4d89-9247-9929bdbd92d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15c9d732-8cd6-4973-8a54-833b92d4bb06' class='xr-var-data-in' type='checkbox'><label for='data-15c9d732-8cd6-4973-8a54-833b92d4bb06' 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>PROJCS[&quot;WGS 84 / UTM zone 31N&quot;, 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;]], PROJECTION[&quot;Transverse_Mercator&quot;, AUTHORITY[&quot;EPSG&quot;,&quot;9807&quot;]], PARAMETER[&quot;central_meridian&quot;, 3.0], PARAMETER[&quot;latitude_of_origin&quot;, 0.0], PARAMETER[&quot;scale_factor&quot;, 0.9996], PARAMETER[&quot;false_easting&quot;, 500000.0], PARAMETER[&quot;false_northing&quot;, 0.0], UNIT[&quot;m&quot;, 1.0], AXIS[&quot;Easting&quot;, EAST], AXIS[&quot;Northing&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;32631&quot;]]</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 31N&quot;, 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;]], PROJECTION[&quot;Transverse_Mercator&quot;, AUTHORITY[&quot;EPSG&quot;,&quot;9807&quot;]], PARAMETER[&quot;central_meridian&quot;, 3.0], PARAMETER[&quot;latitude_of_origin&quot;, 0.0], PARAMETER[&quot;scale_factor&quot;, 0.9996], PARAMETER[&quot;false_easting&quot;, 500000.0], PARAMETER[&quot;false_northing&quot;, 0.0], UNIT[&quot;m&quot;, 1.0], AXIS[&quot;Easting&quot;, EAST], AXIS[&quot;Northing&quot;, NORTH], AUTHORITY[&quot;EPSG&quot;,&quot;32631&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>B02</span></div><div class='xr-var-dims'>(t, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6276a395-cb62-4f41-acb6-ac948ead45e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6276a395-cb62-4f41-acb6-ac948ead45e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18a446c9-7169-48b7-b51d-06ac9dc59958' class='xr-var-data-in' type='checkbox'><label for='data-18a446c9-7169-48b7-b51d-06ac9dc59958' 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>B02</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>[83776 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B03</span></div><div class='xr-var-dims'>(t, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a2f1be52-f87e-4d42-a669-5594f42c517b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2f1be52-f87e-4d42-a669-5594f42c517b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53007668-6e27-4776-82e7-f725af750d99' class='xr-var-data-in' type='checkbox'><label for='data-53007668-6e27-4776-82e7-f725af750d99' 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>B03</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>[83776 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B04</span></div><div class='xr-var-dims'>(t, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c02c49c4-a0ce-4858-865a-5c1635edab62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c02c49c4-a0ce-4858-865a-5c1635edab62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c272eebe-f90a-4e66-b878-4f9e9036d474' class='xr-var-data-in' type='checkbox'><label for='data-c272eebe-f90a-4e66-b878-4f9e9036d474' 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>B04</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>[83776 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9079d195-ac35-495d-9536-db8180e48f10' class='xr-section-summary-in' type='checkbox'  ><label for='section-9079d195-ac35-495d-9536-db8180e48f10' 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-13873bf6-29f8-434c-9c50-2af1fb55591e' class='xr-index-data-in' type='checkbox'/><label for='index-13873bf6-29f8-434c-9c50-2af1fb55591e' 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;2022-06-01&#x27;, &#x27;2022-07-01&#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-51f6ed19-97ff-40e2-b4d9-73a216b7982e' class='xr-index-data-in' type='checkbox'/><label for='index-51f6ed19-97ff-40e2-b4d9-73a216b7982e' 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(Float64Index([601375.0, 601385.0, 601395.0, 601405.0, 601415.0, 601425.0,\n",
       "              601435.0, 601445.0, 601455.0, 601465.0,\n",
       "              ...\n",
       "              604795.0, 604805.0, 604815.0, 604825.0, 604835.0, 604845.0,\n",
       "              604855.0, 604865.0, 604875.0, 604885.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=352))</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-65698978-0fb8-494d-888e-ffcc57a0220f' class='xr-index-data-in' type='checkbox'/><label for='index-65698978-0fb8-494d-888e-ffcc57a0220f' 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(Float64Index([5669795.0, 5669785.0, 5669775.0, 5669765.0, 5669755.0, 5669745.0,\n",
       "              5669735.0, 5669725.0, 5669715.0, 5669705.0,\n",
       "              ...\n",
       "              5668705.0, 5668695.0, 5668685.0, 5668675.0, 5668665.0, 5668655.0,\n",
       "              5668645.0, 5668635.0, 5668625.0, 5668615.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=119))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-441df3e5-f883-455f-a5fa-455d7f73a150' class='xr-section-summary-in' type='checkbox'  checked><label for='section-441df3e5-f883-455f-a5fa-455d7f73a150' class='xr-section-summary' >Attributes: <span>(4)</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-1.9</dd><dt><span>institution :</span></dt><dd>openEO platform - Geotrellis backend: 0.16.2a1</dd><dt><span>description :</span></dt><dd></dd><dt><span>title :</span></dt><dd></dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (t: 2, x: 352, y: 119)\n",
       "Coordinates:\n",
       "  * t        (t) datetime64[ns] 2022-06-01 2022-07-01\n",
       "  * x        (x) float64 6.014e+05 6.014e+05 6.014e+05 ... 6.049e+05 6.049e+05\n",
       "  * y        (y) float64 5.67e+06 5.67e+06 5.67e+06 ... 5.669e+06 5.669e+06\n",
       "Data variables:\n",
       "    crs      |S1 ...\n",
       "    B02      (t, y, x) float32 ...\n",
       "    B03      (t, y, x) float32 ...\n",
       "    B04      (t, y, x) float32 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.9\n",
       "    institution:  openEO platform - Geotrellis backend: 0.16.2a1\n",
       "    description:  \n",
       "    title:        "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "composite = xarray.open_dataset('composite.nc')\n",
    "composite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
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       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (bands: 3, t: 2, y: 119, x: 352)&gt;\n",
       "array([[[[0.1007, 0.1026, 0.0713, ..., 0.0566, 0.0427, 0.0598],\n",
       "         [0.0868, 0.101 , 0.0811, ..., 0.083 , 0.0714, 0.104 ],\n",
       "         [0.087 , 0.0872, 0.0858, ..., 0.13  , 0.097 , 0.1382],\n",
       "         ...,\n",
       "         [0.0996, 0.096 , 0.0677, ..., 0.0165, 0.0178, 0.0228],\n",
       "         [0.0599, 0.059 , 0.0776, ..., 0.015 , 0.0168, 0.023 ],\n",
       "         [0.0532, 0.0518, 0.0499, ..., 0.0145, 0.0156, 0.0192]],\n",
       "\n",
       "        [[   nan,    nan, 0.0833, ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [0.1098,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         ...,\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan]]],\n",
       "\n",
       "\n",
       "       [[[0.0966, 0.0972, 0.0716, ..., 0.0665, 0.0536, 0.0714],\n",
       "         [0.0845, 0.0871, 0.0762, ..., 0.0773, 0.072 , 0.1106],\n",
       "         [0.083 , 0.083 , 0.0882, ..., 0.1206, 0.1004, 0.1616],\n",
       "...\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan]]],\n",
       "\n",
       "\n",
       "       [[[0.0732, 0.0776, 0.0601, ..., 0.0479, 0.0394, 0.0458],\n",
       "         [0.0676, 0.078 , 0.0606, ..., 0.0708, 0.0594, 0.0787],\n",
       "         [0.0746, 0.0784, 0.0802, ..., 0.1036, 0.0727, 0.145 ],\n",
       "         ...,\n",
       "         [0.0742, 0.0708, 0.0469, ..., 0.0196, 0.018 , 0.0236],\n",
       "         [0.0438, 0.0426, 0.0546, ..., 0.0188, 0.0182, 0.0208],\n",
       "         [0.0429, 0.0431, 0.0418, ..., 0.0179, 0.0188, 0.0206]],\n",
       "\n",
       "        [[   nan,    nan, 0.093 , ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [0.1146,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         ...,\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan]]]],\n",
       "      dtype=float32)\n",
       "Coordinates:\n",
       "  * t        (t) datetime64[ns] 2022-06-01 2022-07-01\n",
       "  * x        (x) float64 6.014e+05 6.014e+05 6.014e+05 ... 6.049e+05 6.049e+05\n",
       "  * y        (y) float64 5.67e+06 5.67e+06 5.67e+06 ... 5.669e+06 5.669e+06\n",
       "  * bands    (bands) object &#x27;B04&#x27; &#x27;B03&#x27; &#x27;B02&#x27;</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'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>bands</span>: 3</li><li><span class='xr-has-index'>t</span>: 2</li><li><span class='xr-has-index'>y</span>: 119</li><li><span class='xr-has-index'>x</span>: 352</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-0f1248fc-91cf-484b-b87e-26a4f762c541' class='xr-array-in' type='checkbox' checked><label for='section-0f1248fc-91cf-484b-b87e-26a4f762c541' 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>0.1007 0.1026 0.0713 0.0976 0.1158 0.0876 ... nan nan nan nan nan nan</span></div><div class='xr-array-data'><pre>array([[[[0.1007, 0.1026, 0.0713, ..., 0.0566, 0.0427, 0.0598],\n",
       "         [0.0868, 0.101 , 0.0811, ..., 0.083 , 0.0714, 0.104 ],\n",
       "         [0.087 , 0.0872, 0.0858, ..., 0.13  , 0.097 , 0.1382],\n",
       "         ...,\n",
       "         [0.0996, 0.096 , 0.0677, ..., 0.0165, 0.0178, 0.0228],\n",
       "         [0.0599, 0.059 , 0.0776, ..., 0.015 , 0.0168, 0.023 ],\n",
       "         [0.0532, 0.0518, 0.0499, ..., 0.0145, 0.0156, 0.0192]],\n",
       "\n",
       "        [[   nan,    nan, 0.0833, ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [0.1098,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         ...,\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan]]],\n",
       "\n",
       "\n",
       "       [[[0.0966, 0.0972, 0.0716, ..., 0.0665, 0.0536, 0.0714],\n",
       "         [0.0845, 0.0871, 0.0762, ..., 0.0773, 0.072 , 0.1106],\n",
       "         [0.083 , 0.083 , 0.0882, ..., 0.1206, 0.1004, 0.1616],\n",
       "...\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan]]],\n",
       "\n",
       "\n",
       "       [[[0.0732, 0.0776, 0.0601, ..., 0.0479, 0.0394, 0.0458],\n",
       "         [0.0676, 0.078 , 0.0606, ..., 0.0708, 0.0594, 0.0787],\n",
       "         [0.0746, 0.0784, 0.0802, ..., 0.1036, 0.0727, 0.145 ],\n",
       "         ...,\n",
       "         [0.0742, 0.0708, 0.0469, ..., 0.0196, 0.018 , 0.0236],\n",
       "         [0.0438, 0.0426, 0.0546, ..., 0.0188, 0.0182, 0.0208],\n",
       "         [0.0429, 0.0431, 0.0418, ..., 0.0179, 0.0188, 0.0206]],\n",
       "\n",
       "        [[   nan,    nan, 0.093 , ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [0.1146,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         ...,\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan]]]],\n",
       "      dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-c51993a3-e021-4b02-a575-26ea8d00e160' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c51993a3-e021-4b02-a575-26ea8d00e160' class='xr-section-summary' >Coordinates: <span>(4)</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'>2022-06-01 2022-07-01</div><input id='attrs-6f39d35b-ba25-4c4f-a25a-7b19549e1bd3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f39d35b-ba25-4c4f-a25a-7b19549e1bd3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0812352-4d10-40d7-97ac-c7c01f0838f6' class='xr-var-data-in' type='checkbox'><label for='data-e0812352-4d10-40d7-97ac-c7c01f0838f6' 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;2022-06-01T00:00:00.000000000&#x27;, &#x27;2022-07-01T00:00:00.000000000&#x27;],\n",
       "      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'>6.014e+05 6.014e+05 ... 6.049e+05</div><input id='attrs-88da6366-90c8-4dcd-8d73-327ad2f4c16a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88da6366-90c8-4dcd-8d73-327ad2f4c16a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37a3b242-65e4-482e-ade5-a4488c96362b' class='xr-var-data-in' type='checkbox'><label for='data-37a3b242-65e4-482e-ade5-a4488c96362b' 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 of projection</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([601375., 601385., 601395., ..., 604865., 604875., 604885.])</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'>5.67e+06 5.67e+06 ... 5.669e+06</div><input id='attrs-809a08e2-9f3a-462c-a2cb-f0e3f409cfe4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-809a08e2-9f3a-462c-a2cb-f0e3f409cfe4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a30586cc-2920-4fe2-abf9-92f5ab3c2102' class='xr-var-data-in' type='checkbox'><label for='data-a30586cc-2920-4fe2-abf9-92f5ab3c2102' 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 of projection</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([5669795., 5669785., 5669775., 5669765., 5669755., 5669745., 5669735.,\n",
       "       5669725., 5669715., 5669705., 5669695., 5669685., 5669675., 5669665.,\n",
       "       5669655., 5669645., 5669635., 5669625., 5669615., 5669605., 5669595.,\n",
       "       5669585., 5669575., 5669565., 5669555., 5669545., 5669535., 5669525.,\n",
       "       5669515., 5669505., 5669495., 5669485., 5669475., 5669465., 5669455.,\n",
       "       5669445., 5669435., 5669425., 5669415., 5669405., 5669395., 5669385.,\n",
       "       5669375., 5669365., 5669355., 5669345., 5669335., 5669325., 5669315.,\n",
       "       5669305., 5669295., 5669285., 5669275., 5669265., 5669255., 5669245.,\n",
       "       5669235., 5669225., 5669215., 5669205., 5669195., 5669185., 5669175.,\n",
       "       5669165., 5669155., 5669145., 5669135., 5669125., 5669115., 5669105.,\n",
       "       5669095., 5669085., 5669075., 5669065., 5669055., 5669045., 5669035.,\n",
       "       5669025., 5669015., 5669005., 5668995., 5668985., 5668975., 5668965.,\n",
       "       5668955., 5668945., 5668935., 5668925., 5668915., 5668905., 5668895.,\n",
       "       5668885., 5668875., 5668865., 5668855., 5668845., 5668835., 5668825.,\n",
       "       5668815., 5668805., 5668795., 5668785., 5668775., 5668765., 5668755.,\n",
       "       5668745., 5668735., 5668725., 5668715., 5668705., 5668695., 5668685.,\n",
       "       5668675., 5668665., 5668655., 5668645., 5668635., 5668625., 5668615.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>bands</span></div><div class='xr-var-dims'>(bands)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;B04&#x27; &#x27;B03&#x27; &#x27;B02&#x27;</div><input id='attrs-9bfdf7ff-6aa8-4814-8b3d-9bc7614c367c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9bfdf7ff-6aa8-4814-8b3d-9bc7614c367c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7023a15-d21a-4b56-8eee-67473797b5ee' class='xr-var-data-in' type='checkbox'><label for='data-c7023a15-d21a-4b56-8eee-67473797b5ee' 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;B04&#x27;, &#x27;B03&#x27;, &#x27;B02&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fdc70c4c-af38-4400-a2a8-5c4993e0eb0b' class='xr-section-summary-in' type='checkbox'  ><label for='section-fdc70c4c-af38-4400-a2a8-5c4993e0eb0b' class='xr-section-summary' >Indexes: <span>(4)</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-36dd966a-c0f7-4458-b481-31fafb552ae3' class='xr-index-data-in' type='checkbox'/><label for='index-36dd966a-c0f7-4458-b481-31fafb552ae3' 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;2022-06-01&#x27;, &#x27;2022-07-01&#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-e08d153d-5096-44b6-ad16-85cbc50a06d6' class='xr-index-data-in' type='checkbox'/><label for='index-e08d153d-5096-44b6-ad16-85cbc50a06d6' 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(Float64Index([601375.0, 601385.0, 601395.0, 601405.0, 601415.0, 601425.0,\n",
       "              601435.0, 601445.0, 601455.0, 601465.0,\n",
       "              ...\n",
       "              604795.0, 604805.0, 604815.0, 604825.0, 604835.0, 604845.0,\n",
       "              604855.0, 604865.0, 604875.0, 604885.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=352))</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-63b3cd71-d89a-4476-af9c-5c033b0b4d43' class='xr-index-data-in' type='checkbox'/><label for='index-63b3cd71-d89a-4476-af9c-5c033b0b4d43' 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(Float64Index([5669795.0, 5669785.0, 5669775.0, 5669765.0, 5669755.0, 5669745.0,\n",
       "              5669735.0, 5669725.0, 5669715.0, 5669705.0,\n",
       "              ...\n",
       "              5668705.0, 5668695.0, 5668685.0, 5668675.0, 5668665.0, 5668655.0,\n",
       "              5668645.0, 5668635.0, 5668625.0, 5668615.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=119))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>bands</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8d807efb-d246-4b01-b2e6-4a9e842e96bf' class='xr-index-data-in' type='checkbox'/><label for='index-8d807efb-d246-4b01-b2e6-4a9e842e96bf' 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([&#x27;B04&#x27;, &#x27;B03&#x27;, &#x27;B02&#x27;], dtype=&#x27;object&#x27;, name=&#x27;bands&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7ff7209d-f82d-41d7-a3ad-874c4c9b19bd' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7ff7209d-f82d-41d7-a3ad-874c4c9b19bd' 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>"
      ],
      "text/plain": [
       "<xarray.DataArray (bands: 3, t: 2, y: 119, x: 352)>\n",
       "array([[[[0.1007, 0.1026, 0.0713, ..., 0.0566, 0.0427, 0.0598],\n",
       "         [0.0868, 0.101 , 0.0811, ..., 0.083 , 0.0714, 0.104 ],\n",
       "         [0.087 , 0.0872, 0.0858, ..., 0.13  , 0.097 , 0.1382],\n",
       "         ...,\n",
       "         [0.0996, 0.096 , 0.0677, ..., 0.0165, 0.0178, 0.0228],\n",
       "         [0.0599, 0.059 , 0.0776, ..., 0.015 , 0.0168, 0.023 ],\n",
       "         [0.0532, 0.0518, 0.0499, ..., 0.0145, 0.0156, 0.0192]],\n",
       "\n",
       "        [[   nan,    nan, 0.0833, ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [0.1098,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         ...,\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan]]],\n",
       "\n",
       "\n",
       "       [[[0.0966, 0.0972, 0.0716, ..., 0.0665, 0.0536, 0.0714],\n",
       "         [0.0845, 0.0871, 0.0762, ..., 0.0773, 0.072 , 0.1106],\n",
       "         [0.083 , 0.083 , 0.0882, ..., 0.1206, 0.1004, 0.1616],\n",
       "...\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan]]],\n",
       "\n",
       "\n",
       "       [[[0.0732, 0.0776, 0.0601, ..., 0.0479, 0.0394, 0.0458],\n",
       "         [0.0676, 0.078 , 0.0606, ..., 0.0708, 0.0594, 0.0787],\n",
       "         [0.0746, 0.0784, 0.0802, ..., 0.1036, 0.0727, 0.145 ],\n",
       "         ...,\n",
       "         [0.0742, 0.0708, 0.0469, ..., 0.0196, 0.018 , 0.0236],\n",
       "         [0.0438, 0.0426, 0.0546, ..., 0.0188, 0.0182, 0.0208],\n",
       "         [0.0429, 0.0431, 0.0418, ..., 0.0179, 0.0188, 0.0206]],\n",
       "\n",
       "        [[   nan,    nan, 0.093 , ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [0.1146,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         ...,\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "         [   nan,    nan,    nan, ...,    nan,    nan,    nan]]]],\n",
       "      dtype=float32)\n",
       "Coordinates:\n",
       "  * t        (t) datetime64[ns] 2022-06-01 2022-07-01\n",
       "  * x        (x) float64 6.014e+05 6.014e+05 6.014e+05 ... 6.049e+05 6.049e+05\n",
       "  * y        (y) float64 5.67e+06 5.67e+06 5.67e+06 ... 5.669e+06 5.669e+06\n",
       "  * bands    (bands) object 'B04' 'B03' 'B02'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "rgb_array=composite.to_array(dim=\"bands\").sel(bands=[\"B04\",\"B03\",\"B02\"]).astype(np.float32)/10000\n",
    "rgb_array"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Final result & conclusion\n",
    "We finally plot composites generated for 2 months. \n",
    "While this notebook ends here, for most real world cases, this is the point where you can start your actual work, as you now have gap-free equitemporal composites. \n",
    "Note that in openEO, things happen on the fly, and this method is quite efficient, so there's no need to actually store these intermediate composites somewhere before movin on, you can just take the composited data cube, and go from there!\n",
    "\n",
    "### Note on performance\n",
    "This approach was designed with efficiency in mind: we explicitly load a minimum amount of bands to construct the mask. As a result if observations are not used in the composite at all, they do not need to be loaded for the final result.\n",
    "The max-NDVI approach is however somewhat limited in this regard, because the plots of the mask show that often many chunks are needed for the final output.\n",
    "\n",
    "One other remark is that it could be an option to construct the mask at lower resolution: this would further reduce data loading times, at the cost of a somewhat less accurate max-NDVI composite.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f72af386890>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xarray.plot.imshow(rgb_array.isel(t=0),vmin=0,vmax=0.18,rgb=\"bands\",col_wrap=2)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}