I am following a paper and am trying to write their process with snappy. It is talking about using coherence and they posted the method (picture below) they used with snap and I am wondering why one should create a product using the Interferogram tool instead of the Coherence tool? I am a little confused about what the difference is. Doesn’t an interferogram create a coherence raster?
Coherence Estimate coherence from stack of coregistered images
Interferogram Compute interferograms from stack of coregistered S-1 images
You need the interferogram tool because that is the tool that calculates the actual phase map used to calculate elevation change. Coherence shows the reliability of the pixels. You cannot do InSAR using coherence only.
The Interferogram tool generates both inteferogram and coherence rasters.
As InSAR processing is computationally demanding you should do your processing via GPT to avoid large performance degradation due to snappy/Python. You can use the snapista Python wrapper:
Hi @mengdahl ,
Could you share a tutorial or an example that explains how to apply Interferogram and Coherence tools as snappy’ Operators?
Thanks in advance!
It depends on how you are using snappy, but in principle pure GPT-processing is always faster. If you want to control your processing from Python look into snapista.
@mengdahl
And is there any tutorial of snapista that indicates which are the Operators to connect recursively (as nodes to the principal graph) to perform correctly the interferometry procedure?
I am trying to follow those steps, but I am not sure which are the Operators that we need to link before the Operator ‘Interferogram’, ‘Double-Difference-Interferogram’ or ‘Three-passDInSAR’ ( Differential Interferometry). Could you share any explanation link or tutorial??
Many thanks in advance!