You could try different values in different images and see which one produces better results. Then, use this value as default for automatic processing. Maybe you can use ratios or other sources (i.e. S2) to improve the threshold selection to create the water mask
I have tried StatisticsOp but there is no value that is near tresshold.
The value with the best result is aaproximately 0.01(1.06E-2 log) for this image. I do not know which value from stats I could use, it seems there is no value close to the best tresshold.
I don’t think this is possible in SNAP alone. You can try to export your raster values as a table (can be automated), then create a histogram out of it (https://docs.scipy.org/doc/numpy/reference/generated/numpy.histogram.html) and search for the local minimum in python. There are either functions to do this or you can transform the histogram into a function (regression curve) and search for local minima by yourself. If you want to do this automated a bit of programming is required, I guess.
Hi, look up “Thresholding”, in particular “Jenks Natural Breaks”. I have used other softwares “Slice” tool in the past to reclassify bi-modal images. Not sure if available in STEP. I think there are Python scripts available.