# Normalize Incidence angle

Thank you, @ABraun, I’ve read the post you offered , we can normalize the incidence angle, but how to normalize the different incidence angle to 36 degrees? a specific number,

I have never heard of such a thing, sorry
Why would someone do that?

Hello,

Unfortunately SNAP does not perform incidence angle normalization. This is an important step for SAR data acquired in wide swath mode such as SENTIENL-1.
Here is an interesting paper that explains how to perform incidence angle correction. https://www.degruyter.com/view/j/geo.2016.8.issue-1/geo-2016-0029/geo-2016-0029.xml

Thank you very much, @ABraun, In order to eliminate the error caused by the change of the local incidence angle ( Wagner, 1999a), In this forum, I learned a lot from your replies.

Thank you, @johngan, I’ll try and use the methods in the literature you provided!

I think SNAP actually does. Flattening to Gamma corrects radiometric distortions caused by topography. It is based on this work:
http://ieeexplore.ieee.org/document/5752845/
http://www.tandfonline.com/doi/abs/10.5589/m11-059?mobileUi=0&journalCode=ujrs20

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Hello mikellei.
I met this problem before. here is the link (Is there a fixed degree of angle for normalization in terrain correction?) I post several months ago, hope it might be helpful.

yes, gamma-naught is independent on local incidence angle.
However for some researchers like me or mikellei, the parameter we want is just normalized sigma-naught.

You can do an approximate incidence angle correction (i.e. normalization) for wide swath SAR images by assuming a simple relationship, like linear, between the incidence angle and backscattering coefficient. This relationship can be determined empirically using sample windows of sigma0 at different incidence angles. I have determined with my colleague incidence angle correction for the S-1 EW images over sea ice. The results can be also applied for other C-band images over sea ice, see
http://ieeexplore.ieee.org/document/8022896/

These incidence corrections are always approximate as a SAR image includes targets with different incidence angle vs. sigma0 relationships. But we have found that this approximate correction greatly improves SAR image classifications.

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Well done! Thanks for your great work, mmakyen

The lookDirection of Sentinel-1 is Right only?

Yes, only right looking. You can refer to https://sentinel.esa.int/web/sentinel/missions/sentinel-1/instrument-payload

Thank you for your information, I’ve read it carefully these days, the method in this article can solve this problem, however, I am facing with a new problem: I can’t build a linear relationship between them,

Thank you very much, I can’t build a linear relationship between siggma0 and incidence angels inSNAP, I cant not upload a screenshot, the approache discussed in this paper is capable of solving this problem,

Thank you for your help, I’ll try it again,