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Readers and Writers for the SCEC Commuinity Geodetic Model InSAR Products

OVERVIEW

We aim to present the SCEC CGM InSAR Product as a single HDF5 file that can be parsed and presented by the SCEC CGM website.

For standard users: we want the CGM website to run a script that extracts a velocity or time series at one or more lon/lat pairs and returns a time series in geoCSV for the user.

For advanced users: we want the user to download the full SCEC CGM HDF5 file and parse their own useful features with some guidance and reading tools from SCEC.

CGM InSAR HDF5 STRUCTURE

The current HDF5 structure is envisioned as follows:

SCEC_CGM_InSAR.hdf5
    ├── Product_Metadata
    │   └── Attributes
    │     ├── version, data_production_date, filename
    │     ├── scec_website_link, documentation_link, citation_info, DOI 
    │     └── contributing_institutions, contributing_researchers 
    └── Track_D071
        ├── Attributes
        │   ├── platform, orbit_direction
        │   ├── polygon_boundaries
        │   ├── geocoded_increment, geocoded_range, approx_posting, grdsample_flags
        │   ├── los_sign_convention, lkv_sign_convention
        │   ├── coordinate_reference_system
        │   ├── time_series_units, velocity_units
        │   ├── dem_source, dem_heights
        │   ├── start_time, end_time, n_times
        │   ├── reference_image
        │   └── reference_frame
        ├── Grid_Info
        │   ├── lon_array
        │   ├── lat_array
        │   ├── lkv_east_ll_grd
        │   ├── lkv_north_ll_grd
        │   ├── lkv_up_ll_grd
        │   └── dem_ll_grd   
        ├── Time_Series
        │   ├── Time_Series_Grids (format: yyyymmddTHHMMSS, UTC time)
        │   │   ├── 20150327T135156_ll_grd
        │   │   ├── 20150421T135158_ll_grd
        │   │   └── 20150515T135159_ll_grd
        │   │   └── ....
        │   └── Uncertainties
        │       └── (undecided)
        └── Velocities
            ├── velo_unc_grd(undecided)
            └── velocities_grd

PACKAGING INSTRUCTIONS (for SCEC CGM Team)

Directions to package up CGM InSAR HDF5 file from local files:

  1. Git clone "InSAR_CGM_readers_writers" repo onto your local machine. Install requirements if necessary (can set up dedicated conda environment if desired). Install software by calling python setup.py install
  2. Get into directory where you want to do the HDF5 packaging.
  3. From working directory, call cgm_generage_empty_configs.py . . This will generate two empty files into the working directory, "file_level_config.txt" and "TRAC_metadata.txt"
  4. Manually fill in all the fields for the appropriate track(s) being packaged in both file_level_config.txt and TRAC_metadata.txt. Information regarding highest-level product metadata or file I/O options specific to your file system will be placed in the file_directory config. Track-specific metadata (nothing file-specific) will be placed in the TRAC_metadata config. When you're done, feel free to move TRAC_metadata into a more reasonable directory closer to the data, and feel free to rename it. Just make sure it can be properly found in the file_level_config.
  5. From the working directory, call cgm_write_hdf5.py file_level_config.txt

USER'S CORNER FOR SCEC HDF5 FILE

  1. If you plan to read HDF5 into Python: Git clone "InSAR_CGM_readers_writers" repo onto your local machine. Install requirements if necessary (if desired, you can set up dedicated conda environment in requirements.txt). Install software by calling python setup.py install
  2. Check out an HDF5 file. One option is to view the basic metadata and its contents in bash:
#!/bin/bash 
h5dump --contents test_SCEC_CGM_InSAR_v0_0_1.hdf5    # basic table of contents 
h5dump --header test_SCEC_CGM_InSAR_v0_0_1.hdf5      # detailed metadata table 
h5dump --a /Product_Metadata/version test_SCEC_CGM_InSAR_v0_0_1.hdf5  # view value of attribute

Alternately, you can look at the basic metadata in gdal:

#!/bin/bash
gdalinfo test_SCEC_CGM_InSAR_v0_0_1.hdf5

As a third option, you can look at the basic metadata in Python:

#!/usr/bin/env python
import cgm_library

filename = "test_SCEC_CGM_InSAR_v0_0_1.hdf5"
cgm_library.io_cgm_hdf5.read_cgm_hdf5_demo_python(filename);

Extracting Layers

You can extract pixels as GeoCSV using this library. Each pixel's time series will be saved in a GeoCSV file.

#!/usr/bin/env python
import cgm_library

reference_pixel = [-116.57164, 35.32064];
los_angeles = [-118.2437, 34.0522];
pixel_list = [reference_pixel, los_angeles];
cgm_library.hdf5_to_geocsv.extract_csv_from_file("test_SCEC_CGM_InSAR_v0_0_1.hdf5", pixel_list, ".");

You can also extract a layer of data for a particular track into a GMT grid file. A GMT installation with GDAL is required. (for more: https://docs.generic-mapping-tools.org/latest/cookbook/features.html?highlight=ndvi#reading-more-complex-multi-band-images-or-grids)

#!/bin/bash

# FILE CONFIGURATION
infile="test_SCEC_CGM_InSAR_v0_0_1.hdf5"
track="Track_D071"
dataset="Velocities/velocities"   # reference the file's metadata table (h5dump -n) for exact dataset architecture
outfile="D071_vels.grd"

# EXTACT A SINGLE GRD FILE FROM HDF5 FILE!!!!  
# All three lines are necessary for a complete data extraction.  
gmt_range=`h5dump -a //$track/Grid_Info/gmt_range $infile | grep -o "[0-9.-]*/[0-9.-]*/[0-9.-]*/[0-9.-]*"`   # value of gmt_range attribute. 
gmt grdedit $infile=gd?HDF5:"$infile"://$track/$dataset -R$gmt_range -G$outfile   # send layer out to grdfile, using GDAL. 
gmt grdedit $outfile -T    # turn the file to pixel node registration. Must be done in second step.  

# GMT PLOTTING. 
Range="-121/-115/32/37"
gmt makecpt -T-32/7/1 -Croma > mycpt.cpt
gmt grdimage $outfile -R$range -JM5i -B1 -Cmycpt.cpt -K -P > out_vel.ps #

Results for extracting the GMT grd file of velocities in Track D071 are shown below:

Velocities

SOFTWARE TO-DOS FOR SCEC TEAM

To implement the HDF5 file format, the CGM team must create:

  1. Function(s) to construct the SCEC CGM HDF5 from the CGM analysis [for internal use only]. DONE
  2. Example reader functions to read the full SCEC HDF5 file into a practical data structure, as an advanced user would do, in several commonly used programming languages:
    • Python
    • bash/gmt
    • Matlab
    • Jupyter Notebook
  3. A tool to extract a certain pixel's time series from the HDF5 and convert it into a geoCSV.
  4. Detailed documentation of the CGM product.
  5. Next steps: Make binary executable to take only one track out of multi-track file