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Atmospheric phase cannot be removed by a SNAP module as it cannot be modeled, like flat earth phase or topographic phase, for example. If you would make reference measurements of water vapor or have dense time-series data (example) you could theoretically remove the atmospherical phase distortions. This is advanced however (example 2).
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You calculate an interferogram between a pair of images. It shows you the differences between both images regarding their single phase signal. As the satellites made images from different angles and with a known distance towards each othter (perpendicular baseline) you perceive these fringes. They somehow reveal the shape (and also movement) of the terrain. Please read this document first to understand the principles why an interferogram is created and what it is able to explain. InSAR principles. There are also nice slides on the SAR EDU page for insar: https://saredu.dlr.de/unit/insar_basics
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You only have one coherence for the pair of images before and after. Generally, the coherence tells us if the signals are ‘in phase’ to each other, meaning that the emmitted waves align (somebody please correct me if I’m wrong)
If the signals are out of phase, you can’t retrive reliable information of your interferogram at those locations. You therefore usually only work with pixels with a coherence of 0.3 or above (or some other threshold). -
Values of low coherence are caused by decorrelation. There are different reasons: For example, temporal decorrelation occurs, when objects move or change between the first and the second image. Vegtetation is highly affected by deccorelation. Even when high grass is moved by the wind, decorrelation happens within seconds. This is also called volume decorrelation.
If your incidence angles of both images are too different you get low coherence values due to baseline decorrelation. You can’t do much about that.
For your example, both buildings and vegetation didn’t change their location between both images. But vegetation may have grown or somehow changed its shape and structure.
I highly recommend reading the above mentioned InSAR principles. Please have also a look at the SAR EDU page which provides excellent material for free: https://saredu.dlr.de