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InSAR time series analysis in Python

PySAR is a open-source package in Python for InSAR (Interferometric Synthetic Aperture Radar) time series analysis. It reads stack of interferograms (coregistered and unwrapped) in ISCE, Gamma or ROI_PAC format, and produces three dimensional (2D in space and 1D in time) ground displacement. It includes a routine time series analysis (pysarApp.py) and some independent toolboxs. PySAR is built on the initial work done by Scott Baker. Alfredo Terrero linked PySAR product with InSAR Web Viewer.

1. Download

2. Installation

3. Running PySAR

PySAR reads a stack of interferograms (unwrapped interefrograms, coherence, wrapped interferograms and connecting components from SNAPHU if available) and the geometry files (DEM, lookup table, etc.). You need to give the path to where the files are and PySAR takes care of the rest!

Run pysarApp.py -h see the processing options.
Run pysarApp.py -H see the default template options with explanation.
Run pysarApp.py -g to generate a default template file and see the detailed settings.

Example: Kuju Volcano example with ALOS data

Download the test data: Download Link and unzip it. Run pysarApp.py with setting file as below:

cd ~/KujuAlosAT422F650/PYSAR
pysarApp.py KujuAlosAT422F650.txt

Inside pysarApp.py, it reads the unwrapped interferograms, refernces all of them to the same coherent pixel (reference point), calculates the phase closure and estimates the unwrapping errors (if it has been asked for), inverts the network of interferograms into time-series, calculates a parameter called “temporal coherence” which can be used to evaluate the quality of inversion, corrects local oscilator drift (for Envisat only), corrects stratified tropospheric delay (using pyaps or phase-elevation-ratio approach), corrects DEM error, removes phase ramps (if it has been asked for),… and finally estimates the velocity.

Check ./PIC folder for auto generated figures. Use view.py to plot 2D image and tsview.py to plot the time-series for each point. More details about this test data is in here.

velocity on Kuju

Another template example for Sentinel-1 data with ISCE/topsStack processor: FernandinaSenDT128.txt

Build your own processing recipe

PySAR is a toolbox with a lot of individual utility scripts, highly modulized in python. Check its documentaion or simple run it with -h to see its usage, you could build your own customized processing recipe! Here is an example to compare the velocities estimated from displacement time-series with different troposphric delay corrections: link

4. Documentation

5. Google Group

Join our google group https://groups.google.com/forum/#!forum/py-sar to ask questions, get notice of latest features pushed to you!

License

FOSSA Status