leiyangleon / Geogrid

A Python module for precise mapping between (pixel index, pixel displacement) in image coordinates and (geolocation, motion velocity) in map-projected geographic Cartesian coordinates (northing/easting)

Geogrid

Note from now on, the two testGeogrid scripts (testGeogridOptical.py and testGeogrid_ISCE.py) are only hosted on the sister module autoRIFT's GitHub page (https://github.com/nasa-jpl/autoRIFT). Thus, they have been removed from this website.

Update Notes:

+ refined the workflow and ready for scaling the production of both optical and radar data results
+ improved memory use (by 50%) for autoRIFT and runtime (60x) for GeogridOptical
+ support for remote input files using GDAL virtual file systems (e.g., `/vsicurl/https://...`)
+   see: https://gdal.org/user/virtual_file_systems.html

A Python module for precise mapping between (pixel index, pixel displacement) in image coordinates and (geolocation, motion velocity) in map-projected geographic Cartesian (northing/easting) coordinates

Geogrid can be installed as a standalone Python module (only supports Cartesian coordinates) either manually or as a conda install (https://github.com/conda-forge/autorift-feedstock). To allow support for both Cartesian and radar coordinates, Geogrid must be installed with the InSAR Scientific Computing Environment (ISCE: https://github.com/isce-framework/isce2)

Geogrid can be used for dense feature tracking between two images over a grid defined in an arbitrary map-projected geographic Cartesian (northing/easting) coordinate projection when used in combination with the sister autoRIFT Python module (https://github.com/nasa-jpl/autoRIFT). Example applications include searching radar-coordinate imagery on a polar stereographic grid and searching Universal Transverse Mercator (UTM) imagery at a specified map-projected geographic Cartesian (northing/easting) coordinate grid

Copyright (C) 2019 California Institute of Technology. Government Sponsorship Acknowledged.

Link: https://github.com/leiyangleon/Geogrid

1. Authors

Yang Lei (GPS/Caltech; [e-mail]; [e-mail]);

Piyush Agram (GPS/Caltech; [e-mail])

2. Acknowledgement

This effort was funded by the NASA MEaSUREs program in contribution to the Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) project (https://its-live.jpl.nasa.gov/) and through Alex Gardner’s participation in the NASA NISAR Science Team

3. Features

4. Demo

5. Install

Please refer to the installation guide of autoRIFT repository (https://github.com/nasa-jpl/autoRIFT) for installing the Geogrid module.

6. Instructions