MintPy-tutorials contains the documentations for the MintPy repo, mainly in Jupyter Notebook.
Contents (nbviewer)
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Small baseline time series analysis with
smallbaselineApp
. This notebook walks through the various processing steps of InSAR time series analysis using MintPy. -
Visualizations
- Interactive time-series with tsview
- Interactive coherence matrix with plot_coherence_matrix
- Interactive transection with plot_transection
- Google Earth doc
-
Read / write data files
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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
-
Single interferogram processing with ISCE2
- Sentinel-1 TOPS mode SAR data with topsApp
- StripMap mode SAR data with stripmapApp
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Stack of interferograms processing with ISCE2 stack processors
- Sentinel-1 TOPS mode SAR data with topsStack
- StripMap mode SAR data with stripmapStack
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Manipulate ARIA standard InSAR products with ARIA-tools
- Downloading GUNW products using ariaDownload
- Preparing GUNW products for time series analysis using ariaTSsetup