Is preprocessing S1 SLC data with snappy realistic?

I would suggest to not use esa_snappy, but rather use GPF to do all the pre-processing.

Begin by creating the Graphs in SNAP and saving them as XMLs. I then edit the XML an put easily findable parameters that I can replace without going line by line through the file, or in some of my earlier ones I would just flip through the lines and edit specific ones. I have an example of this below. Just depends what you’re comfortable with.

Use Python to setup and create all the paths from file to file, edit the XML to point to the path Input and Output, then use subprocess to run the edited XML with GPF.

I have tried to use snappy for this but it’s complicated and not well documented. I find there are little differences in many of the tools that are difficult to sort out. If you were a Java programmer you’d have an easier time of it I think. I am not.

But once set up, the above method is fairly elegant, IMHO. Here is some code to get you started,

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