Subsidence map in 3d view

The wavelength of Sentinel-1 is about 5 cm and strongly interacts with smaller vegetation cover such as shrubs. Ich these shrubs slightly change between two image acquisitions coherence rapidly decreases.

It cannot be increased by methods of data processing. Higher coherence can be achieved through precise orbit parameters, shorter time intervals and longer wavelengths (ALOS PALSAR with L-band, ca. 21 cm is less sensitive to smaller surface cover changes).

So all you can do with sentinel is applying the orbit files before your co-registration (also increase the number of GCPs) and hope that the coherence is of better quality.

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Ok, I will give it a try.
Thank you!

"Select a point where you assume no change and read the value. Let’s say its 45 cm

Subtract 45 from your imagein order to have zero values at those areas with no change. The remaining variation should be due to subsidence between two overpasses."

can you explain it briefly … you say “45 cm”… from where I get this value for my case… is it from phase or coherence …from coherence map> properties> pixel information tab>band… little confused

this value is hypothetical, it replaces any value you measure at your location where you don’t expect change. You measure it from the unwrapped phase.

ok I understood … but ABraun can you show me procedure of subtraction step wise … that you mentioned

"Subtract 45 from your imagein order to have zero values at those areas with no change. The remaining variation should be due to subsidence between two overpasses:

Assuming that your unwrapped phase is “Unwrapped Phase_ifg_srd_VV_05Dec2008_24Apr2009”
and your reference height is 15:

Right-click on your unwrapped phase open Band maths and enter
Unwrapped Phase_ifg_srd_VV_05Dec2008_24Apr2009 - 15

If the measured value is negative, add it instead.

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`

in this picture pixel value show 2o8 … what does it mean`

if you expect no subsidence at this location it means that your subsidence map is 208 mm too high. If there was no change at this pixel there should be a zero. After unwrapping your product a product of relative changes within the raster, given as absolute values (mm in this case if you applied the formula correctly).

So make your raster 208 smaller and you should theoretically have the absolute height changes during the two overpasses.

However, there’s a strong ramp in your image wich distorts the result massively. I don’t think you did anything wrong so far but maybe there’s too much time between your images.

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is there any option in sentinel 1 toolbox by which i can get the information of incidence angle of satellite of any radar radar image.

There is the incidence angle tie point grid and also the incidence near and far in the abstracted metadata.

i am trying to unwrapped the phase on VMware … it seems a never ending process… it shows treesize 33876567 , pivots 1376897546, improvements 11567898… what does these term means… is there any way to know how much time it takes…

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Going back to the post of Sept. 8-th.

How to find the “incident_angle” in order to process the data?
Is it in the metadata?

hello ABraun
is there any option in sentinel 1 toolbox from where i can get the wavelength information of my terrasar image…

you said that the crop possess of eliminating the pixel that have low coherence will be done on unwrapped phase … but when i do this process on unwrapped phase … a error message is shown…

but when i did it on coherence image only the required pixel remain no error message shown… is it correct…

I can’t help you when I don’t know the error message.
As you work with the information of the unwrapped phase you need to mask out the locations with low coherence there, of course. It’s kind of map algebra with two rasters: If coherence is low, set unwrapped phase to nan/invalid.

Wavelength is 3.1 cm - I didn’t find it on the rush in the metadata, sorry.

and where i can get the information of incident angle in sentinel 1

incidence angle is dependent from the distance to the sensor.
So there is always a difference between the far and the near range.:
You find it under Abstracted_Metadata:

If you want the incident angle of a specific pixel, you can open it as a Tie-Point-Grid:

can u please check weather … the steps I did is right??

  1. this is my unwrapped phase

  1. then I did the band math …

  1. here is new image after doing the band math calculation

  1. then I am opened up the coherence image … and did the crop out process of eliminating pixel that have low coherence value…

then I am identifying the stable pixel, the highlighted one…

what will I do now…

I don’t know how I can it explain it any better than above.
You don’t get information about subsidence from the coherence layer. You only use it as a spatial indicator of quality of your phase information. Therefore, you don’t apply the masking of low coherence on the coherence but on the unwrapped phase information (band 3 in your case). Then you will have the areas where your information is reliable. You can also lower the threshold to 0.4 in order to get larger valid areas.

Sorry, but it seems that you follow a recipe while you aren’t aware of the meaning of the single steps. InSAR is not trivial, undoubtedly. But one should be clear about what is done and why before processing.

and again:

However, there’s a strong ramp in your image wich distorts the result massively. I don’t think you did anything wrong so far but maybe there’s too much time between your images.

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Hi Dipankar,

I’d like to say what is mentioned by ABraun in most digestible words, In InSAR Processing chain there are a lot of steps, SNAP concise most of this steps in general and short by including the other within the major steps, the other thing I’d say is each process step has many parameters, in any processing case we try to play with this parameters increase or decrease according for example to study area the per.Basline and TemBasline, Atmoshperic effects and so on, So try to play with those parameters by taking in your account a short TemBaseline for instance in Sentinel-1B only six days, that would clarify many matters for you.