I’m currently trying to use the post-processed S-2 SYN AOD data produced by the following research
The data is generated through the application of a post-processing algorithm which combines the S-2 SYN, OL-1-ERR and SL_1_RBT files.Unfortunately, as you can see from the following image, the smile effect issue still affects the quality of the results:
I’ve already looked for a solution in the forum and found mention here:
that a processor was in development some years ago to correct this issue. Does anyone have information about whether or not this processor was indeed developed and added to Snap? Or if any alternative solution for this issue exists(maybe through some clever data cleaning in python?)
I’m not aware of such an approach.
But I can say that we have reactivated the work on the smile correction. Coincidentally at the same time as your question. This should not mean that it will be available next week. It still can take some months or we might stop further development again.