go to the color manipulation tab and switch to the table coloring. There you can define value ranges and assign colors (also transparent ones) to the different ranges.
Positive means subsidence and negative signifies uplifting?
I have done the following steps to build maps of Uplifting and subsidence (map of displacement)
After completing the steps above, we performed the following steps:
1- Exporting data for SNAPHU processing
2-Importing results from SNAPHU processing
3- Phase to Displacement By Operator
4- Create Stack (Coherence + Displacement)
5- Geocoding(Range Doppler Terrain Correction Operator)+Elevation
6- By Band Maths: Made DisUP35Coh & DisUP50Coh (Map of displacement that Coherence upper 0.35 and 0.50):
if (coh_IW3_VV_22Sep2016_31Aug2018 > 0.35) then (displacement_slv1_22Sep2016_VV) else (NaN)
Track is Descending and other properties are:
Now ,The question is: what is the positive and the negative in these maps?
Positive = Subsidence ?
Negative = uplift?
DisUP60Coh-Garmsar.kmz (2.4 MB)
Thank in advance
that depends on the date of your master and slave image. The difference indicates the change between both dates. But note that the map only displays the change along the line of sight, not absolute vertical displacement.
- Difference between vertical and LOS displacement
- Vertical displacement senitnel 1 interpretation
- Vertical and horizontal displacement
- The phase shift originates from horizontal or vertical displacements
Does the pattern make sense to you?
Very thanks ABraun
I have read the above, but this question remains for me!
I got the old image as masters and newer image as slave .
the phase and Coh are
IF phase converted to displacements and track be descending , the positive signal is uplifting or subsidence?
I am processing Landslide data but through DInSAR but couldnot found any reliable results.(Landslide events dated 13 Aug 2017 and 29 june 2018) at different sites with AOI in the same swath IW2 of Sentinel 1A images.
Wish to process a fresh from start. Would you please guide me if i share my location with you?
Like data acquisition, base line guidance, processing parameters and other related help.
sorry, I can’t grant to keep track of every step. What about the comments on your questions in other topics?
There are answers to almost any question in this forum:
- general workflow: Interferogram Formation - Subtract topographic phase check box
- full tutorial on subsidence monitoring: https://eo-college.org/resources/insar_deformation/
- notes on image selection and constraints: How can we calculate the volume of displaced material with displacement band(displacement_VV)?
- atmospheric disturbance: Subsidence Map
- InSAR - A practical approach: Have a look the comment on landslides in chapter 4.1.4
Because of the constraints (topography, surface change, atmosphere, long temporal baseline), many studies favor PS InSAR for landslide analysis:
If they leave any questions, feel free to ask.
Thanks a lot.
I successfully found subsidence in Mexico city where coherence is good. But in my area coherence is very poor. Tried temporal diff of 12,36,96 days but could not succeed. I feel DINSAR will not be helpful here.
I will check these docs and will keep on moving.
Thanks for providing so many sources for us about INSAR and PS INSAR.
Here I have a question about both methods.
When we do D-INSAR, we can unwrap the phase and get the displacement using all pixels and then output the displacement results with high correlation coefficient which we considered the results more reliable.
When we do PS D-INSAR, my understanding is that we need to select Persistent Scatter first and then use their interferogram only to do phase unwrapping.
What do you think the difference of displacement results will be with D-INSAR and PS D-INSAR since we consider all phase for INSAR and only high quality phase for PS INSAR when phase unwrapping?
basically yes. But if the areas of hígh coherence are not connected in the image, unwrapping errors might occur which falsely add up the fringes in the image.
yes, PS are selected based on their temporally stable amplitude. Then, interferograms are computed only for these areas.
as said, in traditional DInSAR, all pixels are included in the unwrapping. if you have a larger region with high coherence (e.g. desers, urban areas, or few vegetation), this works fine. If you have only small patches of high backscatter (and coherence) PS InSAR might be the better choice.
Some of the pros and cons are evaluated in this review paper: https://www.sciencedirect.com/science/article/pii/S0924271615002415
These article also compares both methods: https://ieeexplore.ieee.org/document/6350555
Thank you for your reply. I will further look into this.
Andreas, how did you overlay the coherence mask on the displacement map? Thanks
you either define a nodata value in the properties of the displacement map or you add both rasters to one view with the layer manager.
I’ve been reading this forum for the last few months and and confused by this. I haven’t seen any reference to the step of subtracting a value of a pixel you know has a change of 0. I’ve been following this workflow: https://rus-copernicus.eu/portal/wp-content/uploads/library/education/training/HAZA03_Land-Subsidence_Mexico-city.pdf and it does not reference that step at all. Can you elaborate? If I were to subtract some value from my entire image what exactly would that be taking out? Atmospheric effects? Change in the satellite position?
InSAR is a relative measurement. It generates a raster which tells how much a surface changed between two images. But the range of the result is relative as well, it has no absolute minimum/maximum.
Consider the range of your result lies between -32 and -35 mm. Does that mean the entire study area sank down this amount? Not really. So you you look at your area and take one area which seems to be stable and read the displacement value. Let’s say it is -33 mm. So we add these to the entire image to level out the offset. Your new displacement image ranges between -2 and + 1 mm. These can be now understood as absolute values which represent what actually happened at each pixel.
How the threshold value is selected for masking out area with low coherence? I am working land subsidence on coastal area which is not vegetated but some sparse trees are present. most of the area is barren so what should be the coherence threshold value? please reply. Thank you
this depends on your interferogram. Low enough to maintain a consistent pattern of fringes but high enough to mask out areas with random patterns. You have to try a bit and compare the results.
I can’t tell you the exact threshold of coherence, but based on this image, there is nothing to analyze in the center of the image. The parts in the west and east look like unwrapping could work.
what should i do? any suggestion?