Hi @ABraun, I completed all the steps of stamps like “stamps(1,1)” ,“stamps(2,2)”,“stamps(3,3)”,“stamps(4,4)”,“stamps(5,5)”,“stamps(6,6)”,“stamps(7,7)”,“stamps(8,8)” with single patch.
with 6 Patches, matlab throwing error. So I proceed with 1 patch only.
I removed the extra file from diff0 folder, I think same date file should be there the in diff0 and in rslc.
Could it be that the data preprocessed in snap2stamps is faulty? Sometimes one of the interferograms was not processed correctly, causing the scripts to raise an error. How many input files are you using and do all interferograms look alright? Please visually check each of them.
Data preprocessed in snap2stamps was faulty. I thinks there was a faulty data also in my master image.
I processed again from the starting.
This time i did not get a single error and completed all stamps() steps smoothly.
Got all the plots as mentioned in the StaMPS manual.
Thank you very much for guiding me, It is a great experience and learning for me.
they are technially alright, yes, although you need more images for StaMPS. Can’t say if the phase quality is sufficient for interferometry. I had problems in muddy delta regions as well. The more images you get (at regular intervals) the higher the chances for successful analyses.
Are these results alright? what are the attributes of good results of stamps? I mean how can I get to know that my results are alright or have some errors?
and now I want to process IW2 as well and I was getting error in step 2. Now I am trying with 2 patches that might solve the problem.
If displacement maps of all dates look different, there is large contribution of phase noise and atmosphere. It is not uncommon that some interferograms are different from the rest, when there was heavy rainfall, for example. But if the majority does not agree on a certain pattern I wouldn’t trust too much. The average displacement will then be just a mathematical expression of random patterns instead of representing a continuous movement.
If you really want to analyze the time between April 2020 and March 2021, you need at least one image per month.
I agree this looks quite heavily biased by atmosphere. But good job on getting the results in the first place! If you have the computing capacities, you can try to double the amount of images which also reduces the time between two images to 50%. This could give you higher coherence and more stable results. At the moment, the inteferograms look too different.
Is there some other way for reducing the atmospheric noise except increasing the number of interferograms? I used default parameters of StaMPS during the whole process. Can this bias be reduced by changing any parameter? Or re-running step 6 and 7 multiple times can be done to reduce this bias?