MintPy-tutorials contains the documentations for the MintPy repo, mainly in Jupyter Notebook.

1. Small baseline time series analysis with smallbaselineApp. This tutorial walks through the various processing steps of InSAR time series analysis using MintPy.

   • ISCE/topsStack + MintPy (Sentinel-1 on Fernandina volcano, Galápagos): nbviewer
   • ARIA + MintPy (Sentinel-1 on San Francisco): nbviewer

2. Visualizations

   • Interactive time-series with tsview
   • Interactive coherence matrix with plot_coherence_matrix
   • Interactive transection with plot_transection
   • Google Earth doc

3. Read / write data files

   • Read GMT *.grd file: nbviewer
   • Read / save time-series HDF5 file into text file: nbviewer
   • Read HDF5 files in Matlab: m file

4. Custom applications. List of examples of how to build customized application using mintpy modules or processing recipe using mintpy scripts.

   • Create water mask in radar coordinates: nbviewer
   • Tropospheric delay correction using GACOS products: nbviewer
   • Post-processing of single interferogram after ISCE/stripmapApp: nbviewer
   • Geo / radar coordinates conversion: nbviewer
   • Extract / plot displacement time-series of one pixel: nbviewer
   • Plot GPS as quiver on top of InSAR data: nbviewer
   • Average velocity estimation demonstration: nbviewer

5. Simulation of 3D phase time-series. An example of simulating displacement, tropospheric delays, topographic residuals and phase ramps to construct a 3D raw phase time-series: nbviewer. Handy tools for algorithm developers.

1. Single interferogram processing with ISCE2

   • Sentinel-1 TOPS mode SAR data with topsApp
   • StripMap mode SAR data with stripmapApp

2. Manipulate ARIA standard InSAR products with ARIA-tools

   • Downloading GUNW products using ariaDownload
   • Preparing GUNW products for time series analysis using ariaTSsetup