Giant, Mintpy, Stamps. Which is more automated and user-friendly?

Microwave Toolbox Interferometry
#1

I know each of those software has their advantages and disadvantages. Which is more commonly used by members of this community ? Or should I ask which one can provide more dependable results for deformations related to earthquakes, over bare desert areas with very minimal vegetation and Urban localities?

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#2

I think MintPy is user friendly and it is actively maintained. Very easy to talk to the author if there are issues.

StaMPS is very popular but it seems the author is not maintaining it anymore so bugs are not fixed. I have to get my solutions from this forum.

I’m not sure about Giant.

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#3

The GIAnT software is obsolete now. It only runs under Python v2.x, and the developers stopped working on it at least three or four years ago. I switched from GIAnT to MintPy about two years ago and it is much easier to use and provides dependable results. MintPy runs under Python 3.x and is actively maintained on GitHub. If you have InSAR data processed in a consistent way that is prepared for time-series processing, then MintPy is very easy to use. Both GIAnT and MintPy implement Small BASeline (SBAS) time-series analysis that works well in areas of good InSAR coherence.

StaMPS is a more sophisticated time-series analysis that implements both SBAS and a type of persistent scatterer InSAR analysis (PS-InSAR) that can help in areas of low coherence. It runs under Matlab, so you are required to have a Matlab license. I have not tried to work with StaMPS other than a few sample datasets, so I am not really a good person to comment on it. Many people use it, so I believe it is dependable when operated correctly.

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#4

I really appreciate your contribution. It’s currently too difficult for my institution to acquire paid software licenses, so definitely stamps won’t work for me.

#5

Is there a tutorial or Snap-to-MintPy work flow? Since I am completely new to MintPy and I have only been using Snap and Snap-Phu on windows.

#6

Yes, there is a brief description of a SNAP-to-MintPy workflow on this MintPy documentation page “SNAP input data · insarlab/MintPy Wiki · GitHub”:
SNAP input data · insarlab/MintPy Wiki · GitHub

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#7

Hi dear EJFielding, there is an python code to export csv from h5 for time series that we achieved from mintpy?

#8

The MintPy and MintPy Tutorial GitHub repositories have a number of examples of Python code to export the results in different formats. I don’t remember a script to write out csv, but there are other scripts that could be adapted.