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 / plot displacement time-series of one pixel: nbviewer
   • Read HDF5 files in Matlab: m file

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

   • Calculate multilook number for InSAR processing with ISCE: nbviewer
   • 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
   • Plot GPS as quiver on top of InSAR data: nbviewer
   • Average velocity estimation demonstration: nbviewer

1. Single interferogram processing with ISCE2

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

2. Stack of interferograms processing with ISCE2 stack processors

   • Sentinel-1 TOPS mode SAR data with topsStack
   • StripMap mode SAR data with stripmapStack

3. Manipulate ARIA standard InSAR products with ARIA-tools

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