Terrain flattening and converting gamma0 to sigma0

[ABraun]

terrain flattening tries to correct the radiometric distortions caused by different local incidence angles.
That means, that originally areas facing the sensor are pictured brighter and the other ones darker. Terrain flattening then uses a DEM to re-calculate the actual radiometry based on the area illuminated per pixel.
If your DEM is bad, you could make it worse, theoretically - especially at ridges facing towards or away from the sensor. You can try the ALOS World DEM for a comparison. It also has 30 meters but was made from optical stereoscopy

ALOS｜ALOS@EORC

I made a similar comparison and found the best results gained from Terrain Flattening on GRD or SLC data:

S1 radiometric correction

I did a few tests because I still wonder about the best pre-processing parameters for Sentinel-1. I therefore downloaded a Scene from 12.09.2016 which covers Cyprus (GRD and SLC). I chose this area due to its topographic complexity and the little vegetation cover. S1A_IW_GRDH_1SDV_20160912T035113_20160912T035136_013014_0149C4_6E2F S1A_IW_SLC__1SDV_20160912T035112_20160912T035136_013014_0149C4_CF51 I wanted to see the change in the result if different input data and modules are applied. These…

Another thing is that creating Sigma out of Gamma is not a good idea. At least to my knowledge, Gamma0 is the final stage that can be reached. Why going back to Sigma?