The urban area does have high coherence but the scene in general looks pretty noisy. Do check out filtering and Snaphu parameters.
To deal with atmosphere you can try to create more interferograms over that time period with different baselines to get a better idea of what you are dealing with. Check out the ESA InSAR tutorial and maybe Hansen’s PhD for a better understanding.
Time series approaches are the best way to deal with atmosphere - you will need to run a PSI (like StaMPS) or SBAS (MintPy) approach.
along with the above SNAPHU setting as you mentioned (except the fact that I took 1x1 patch at a time instead of 10x10). I went with the default values for Goldstein phase filtering in the process.
By different baselines you mean one master multiple slave approach to see how the deformation develops over time and correlate it with a natural phenomena that could have possibly resulted in the observation.
But one question stills remains unanswered.
How do we figure out if a fringe over a high coherence area is an atmospheric fringe or is due to actual displacement?
Thanks for the links @falahfakhri but I would like to know two basic things,
How do we know when we see displacement fringes if they are the result of actual displacement or just atmospheric fringes?
In my case, as again posting below for your reference, the displacement appears to be happening over areas with high coherence so I am wondering why would only areas of high coherence show atmospheric fringes and why can’t it be actual displacement? And if this is due to atmospheric reasons why is there a correlation with the coherence and why don’t we see them in the neighbouring areas including anywhere else in the entire sub-swath at this prominent scale?
In fact I notice all over the image some kind of correlation between high coherence values and fringes. Can someone clarify the trend? This also makes me wonder what else can define the goodness of the fringes other than the coherence map.
that is suspicious indeed. I don’t know if you can determine if some fringes are atmospherically induced or not, but the fact that they are larger than the coherence are makes it quite likely. On the other hand, I have seen wonderful fringes over ice with comparably low coherence.
You can set a low-coherence threshold for the valid pixel expression and see if the remaining pattern over the urban area makes sense. An example is given here Subsidence map in 3d view
Furthermore you can check if there was a rain event during one of both images in weather archies.
Lastly, you can try another image pair and see if the same area is covered by fringes.
It’s not possible to avoid the atmospheric delay of single interferogram, the topographic phase is correlated to the atmospheric phase as well, especially in your depicted case, there is no specific event has occurred which causes highly correlated deformation, therefore it’s not easy to differentiate between both, for more information about how the atmospheric and deformation fringes are appearing, please have a look at this,
APPLICATION OF SAR INTERFEROMETRIC TECHNIQUES FOR SURFACE DEFORMATION MONITORING
Thank you Andreas,
I will try out the method and see if it makes sense in my case.
I tried out InSAR processing on another pair of images located geographically distant from the previous data and this is how it looks
Here we can see the wrapped differential interferogram and the coherence values. The previous pattern can be seen to be again repeating, i.e. fringes in areas of high coherence.
The unwrapping algorithm, is working over big matrices, and most of the AOI is noisy, that’s why subset small area with high coherence gives better understandable results.
