I am performing classification of sentinal-1 data to a binary image in to water and non-water by thresholding. Can I do terrain correction after classification of data(ie. on binary image) ?
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That is possible and should be no problem. Just make sure you select nearest neighbor resampling for your binary image in the terrain correction step so that the values will not be recalculated or averaged.
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Ok. Thank You @ABraun.
One more thing, out of gamma naught and sigmma naught product which one would give better result for water binary classification using thresholding teq.
I’d say it doesn’t make a difference because they mostly differ regarding topographic features and volume scattering.
You are saying they differ in topographic features and volume scattering. But these factors will have lot to do on the final backscattered values . Ultimately, the classified images obtained from these two different inputs will give different outputs. So, how can you say that their wont be any difference if I am not wrong.
Greetings!
Thank you for the detailed steps for products processing. From the other hand, I have assumed some controversial with @lveci answer
That is, you missed the Thermal Noise Removal (TNR) step for SLC products, but from the @lveci answer I understand that this step is required.
Than, you recommend the TNR for GRD products, but @lveci told that TNR is already applied.
Sure, your answer partially explains the relevance of this step here
But how can I check the presence of Thermal noise in products I need?
Thank you
if TNR is already applied to all GRD products (I’m not sure) I should probably remove if from the list.
There is a flag in the metadata that should clarify the issue.
Thank you for reply
Dear @ABraun,I didn’t want to confuse you. It is just to clarify some issues with the Sentinel-1 products processing.
I don’t insist on the TNR irrelevance for the GRD processing.
The trouble is that I still can’t find out how to check the Thermal noise presence in my products.
And would you mind to explain, whether users should apply the TNR for SLC?
Appreciate for you answer
I have checked the metadata, but have found only this (marked “Product callibrated”)
But I think this is not about the Thermal noise removal because it is a “correction”, not “calibration”
And what does the “flag” mean in the “Unit” sample of the metadata table?
Thank you
Hi @ABraun,
I was calculating the LOS displacement with the SLC data by following the TOPSAR tutorial (http://step.esa.int/docs/tutorials/S1TBX%20TOPSAR%20Interferometry%20with%20Sentinel-1%20Tutorial.pdf).
In this tutorial, it didn’t mention about the calibration and correction.
Do you recommend doing these steps?
radiometric correction is applied to the backscatter intensity. When you derive displacements with interferometry, you are working with the phase. Calibration is not needed, it moreover destroys the complex information required for InSAR. You only need to terrain correct your data in the end.
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Really thanks for your reply!
But if I calibrate it and keep the complexity, then it won’t destroy the complex information?
If so, will it be better after calibration?
that is true. But the quality of the phase will not improve.
OK, I understand that! Really thanks for your explanation!!
what is the need for doing terrain flattening on water surfaces?
Shouldn’t filtering be a step right before RDTC and after Terrain flattening. As per your flow the Speckle Filtering sits right after calibration to beta0 and right before terrain flattening
To my understanding, filters should be applied to the original image geometry, so at least before RDTC - here we agree. I’m not sure if it makes a large difference if it is applied on the adjusted radiometry (e.g. in areas of foreslopes and backslopes) or not. It could be that it those areas are better smoothed if the filtering comes afterwards. Is there any reference on this maybe?
It is my intuitive feeling that we filter the corrected radiometry, so right at the end of the radiometric correction and right before the geometric correction. Don’t you think it is not right to filter out the beta0 image before we perform the radiometric terrain flattening?
it does make sense 
I’ll update my suggestion above.