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Python tool for InSAR Rate and Time-series Estimation

PyRate is a Python tool for estimating the average displacement rate (velocity) and cumulative displacement time-series of surface movements for every pixel in a stack of geocoded unwrapped interferograms generated by Interferometric Synthetic Aperture Radar (InSAR) processing. PyRate uses a "Small Baseline Subset" (SBAS) processing strategy and currently supports input data in the GAMMA or ROI_PAC software formats.

The PyRate project started in 2012 as a partial Python translation of "Pirate", a Matlab tool developed by the University of Leeds and the Guangdong University of Technology.

The full PyRate documentation is available at


The following system dependencies are required by PyRate:

  • Python, versions 3.6, 3.7 or 3.8.
  • GDAL, versions 3.0.2 or 3.0.4
  • Open MPI, versions 2.1.6, 3.0.4, 3.1.4 or 4.0.2

The versions of each package stated above have been tested to work using GitHub Actions continuous integration testing.

Python dependencies for PyRate are:



Details of all install options are given in the PyRate documentation.

PyRate and its Python dependencies can be installed directly from the Python Package Index (PyPI):

pip install Py-Rate

Alternatively, to install from source and create an executable program in Linux, enter these commands in a terminal:

cd ~
git clone
python3 -m venv ~/PyRateVenv
source ~/PyRateVenv/bin/activate
cd ~/PyRate
python3 install

This will install the above-listed Python dependencies and compile the executable program pyrate. To learn more about using PyRate, type pyrate command in the terminal:

>> pyrate --help
usage: pyrate [-h] [-v {DEBUG,INFO,WARNING,ERROR}]
          {conv2tif,prepifg,correct,timeseries,stack,merge,workflow} ...

PyRate workflow:

    Step 1: conv2tif
    Step 2: prepifg
    Step 3: correct
    Step 4: timeseries
    Step 5: stack
    Step 6: merge

Refer to for
more details.

positional arguments:
    conv2tif            Convert interferograms to geotiff.
    prepifg             Perform multilooking, cropping and coherence masking to interferogram geotiffs.
    correct             Calculate and apply corrections to interferogram phase data.
    timeseries          Timeseries inversion of interferogram phase data.
    stack               Stacking of interferogram phase data.
    merge               Reassemble computed tiles and save as geotiffs.
    workflow            Sequentially run all the PyRate processing steps.

optional arguments:
  -h, --help            show this help message and exit
                        Increase output verbosity


To run the test suite, enter these commands in the terminal:

pip install -r requirements-test.txt
python3 -m pytest -m "not slow" tests/

To run the tests for a single module (e.g., use this command:

python3 -m pytest tests/

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