Cannot detect PS after phase linking using TerraSAR-X images

[david-ncu2019]

Dear @mirzaees ,

Really sorry to bother you. I’d really appreciate it if you could take a moment to look into my case.

I’ve processed 25 TerraSAR-X (TSX) images in a descending path for land subsidence monitoring in an agricultural region of Taiwan. The pre-processing was done with ISCE, and I focused on a small area with miaplpy to test PS detection. The TSX images were kept at full resolution.

For comparison, I also processed Sentinel-1 images from the same period, which were multilooked (3 azimuth: 1 range) over a larger bounding box.

I expected the number of PS detected from TSX image processing to be significantly higher than those from the Sentinel-1A images, but surprisingly, this was not the case. This has left me quite confused. I’m uncertain if the issue stems from the ISCE processing step or if miaplpy doesn't fully support TSX images.

1. The first figure shows the bounding box for Sentinel-1 and TSX image processing.
   

2. The second figure shows the PS mask after phase linking performance on S1A images.
   

3. The final figure contains both amp_dispersion_index and top_eigenvalues raster. Even the output results show high values of amplitude dispersion index and eigenvalues phase linking performance on TSX images, but the file maskPS.h5 shows nothing. I'm really confused why this happened.
   

Any advice you can provide would be really helpful. Thank you for your time!

Best regards,
David

[mirzaees]

Hi @david-ncu2019
Sorry for my late reply
It seems like the processing for TSX was not successful and the PS mask is not actually generated
another way to generate this mask is to use temporal coherence. all the coherence values =1 are PS

[david-ncu2019]

Dear @mirzaees ,

Really thank you for your response!

I understand that your schedule may be quite busy, but I'm really grateful if you could take a moment to check my following questions.

It seems like the processing for TSX was not successful and the PS mask is not actually generated

• Actually, the output files after concatenate_patches still showed values if I checked them individually (using view.py. from MintPy). However, the creation of MaskPS was not successful → Was it due to (1) image processing (with ISCE) or (2) due to the miaplpy algorithm itself?
• If it was due to (1), what should I do to resolve the issue? For the TSX image pre-processing, I applied unpackFrame_TSX.py and stackStripMap.py.
• Is it possible to adjust the default values of phase linking functions (phase_linking and concatenate_patches) in miaplpyApp.py from the source code in installed folder?

another way to generate this mask is to use temporal coherence. all the coherence values =1 are PS

• Would you mind suggesting me the functions to perform this process? Thank you!
  (I will try playing with some functions to perform the temporal_coherence_mask first. Hope my progress aligns with yours)

[mirzaees]

Hi @david-ncu2019

If the individual patches have valid mask ps, then there was a problem during concatenate step
I can tell you more if I see the messages output after running concatenate. Also please delete the file before running this step. I don't think there is any problem in either isce or miaplpy but it might be that your run did not complete successfully and when you try running it again, it checks for the file to exist before regenerating it.
I can tell more if I you run and send me output messages
For the temporal coherence you can use mintpy function:
generate_mask.py temporal_coherence_average.tif -m 1 -o maskPS.h5

[david-ncu2019]

Dear @mirzaees ,

Thank you for your response!

I think I will rerun the phase_linking and concatenate_patches with a very small area to test it again, then provide you the output messages.