I performed the SLC data using SNAP
1 TOPSAR Deburst
2 Calibration to Sigma0
3 Speckle filtering
4 Range Doppler Terrain Correction
For the radiometric calibration results, the VV is right, but the VH is incorrect.
Thermal noise is not present in every product. In case you don’t rely on highly accurate radiometric values you can also skip it.
The orbit file adds information about the geometric location of your product. If you want to combine it with other data it can improve the position accuracy.
Your suggested workflow is sufficient for most applications.
Thanks for your reply, I follow your suggestion to perform the Sentinel-1A data using SNAP. In the previous results, when the radiometric calibration was performed, the results of VV polarization are zeros, only the VH polarization is correct. Can you supply an email for me, thus I can transform the results to you.
Yes, before the radiometric calibration both of the intensity of VV and VH are correct. When the radiometric calibration was implemented, the calibrated VV are zeros, and the calibrated VH is correct.
What order should I take steps in ?I’ve seen one of the above threads says that it should be good after orbit to apply thermal noise removal in order to decrease radiometric variation between subswath.
Best regards!
Thanks for your reply .Do you mean orbit before thermal noise removal is better ?What are the differences between the various epolynomial degrees and which is recommended?
Thank you for help
Hello,
I understand the theoritical difference between beta0 and sigma0, if I want to do intensity correlation analyisis between 2 images, or in this case 3 images. I was usggested to use sigma0, however the area I am working is very hilly and has some mountains. The values of sigma0 and beta0 are ofcouse different from pxel to pixel, but only beta0 allows me to do terrain flatering.
What do you suggest I can do for my application in this case?
Thank you