I am currently working with S1 SLC (slant range geometry) and I noticed that the product is not terrain corrected (elevation) which yields inaccurate geocoding. I can process it using the SNAP Range-doppler correction however the output product is now in the ground range geometry.
I would like to know how to perform terrain correction while preserving slant/azimuth geometry?
If not possible, how can I perform the inverse operation (GRD to SLC) once the terrain correction performed?
Additional information, I work using the python interface (Snappy).
I don’t know if I understood you correctly, but to me, slant range products and terrain corrected products are mutually exclusive.
SLC implies that the pixel geometry is by the the temporal domain (return of each signal from the ground), while terrain corrected products are defined based on actual and projected pixel positions.
Do you maybe have a reference on “terrain corrected SLC” data?
Thanks for the quick answer. I agree that SLC implies that the pixel geometry is by the temporal domain but to my knowledge it is not mutually exclusive with terrain corrected product.
What I mean by terrain corrected SLC is the following: SLC product are geolocalized assuming perfectly flat terrain. However it is rarely the case which means that points with higher altitude “arrive faster” at the sensor and shift the whole image. I would like to correct the image using the average scene height (roughly, high precision is not required).
That is still a bit confuse for me but here the following lines:
Get scene average height from DEM
Use incident angle and trigonometry to obtain the shift
Thanks, ellipsoid-correction with average height is close to what I was looking for.
I am indeed working in open water and needed to preserve the topographic information contain in SLC product while still correcting the average effects.