These are the right steps of ALOS-PALSAR coregistration and creating interferogram,
1- Select the HH or VH, or both polarization
2- Coregistration (one pair and one stack with multiple images)
3- ALOS Deskewing (for the ASF/SSARA data)
4- Interferogram Formation
5- Coherence Estimation
6-Goldstein Phase Filter (on Ifg)
7-Topographic Phase Removal (SRTM 1sec)
But here corr. with GCP not corr. for S1TOPS? what mean stack tool?
anthor question please, are there a way to know corr. accuracy for azmiuth and for range?
Thank you, dear Falah, for all your answer …and I read most post here about this matter and also your P.HD thesis.
I know about ALOS-PLASER and don’t have a problem, but I want to ask you how I get co-registration accuracy for Sentinel -1, as you see here I apply coregistration for TOPS with ESD but you go to InSAR stack tool in SNAP v.7 I can’t found co-registration accuracy values
But I can found co-registration accuracy values if follow steps:
1- Sentinel-1 split
2- S-1 apply orbit
3- S-1 deburst
4- coregistration with GCPS as shows in below pic.
The image pair has a temporal baseline of 12 days and perpendicular baseline of 170 m. Unfortunately, that’s the only pair I have that satisfies the 150-300 m perpendicular baseline requirement for DEM generation. There is no 6-day pair available also. My AOI is within 2 subswaths (IW2 and IW3). I’ve merged the 2 subswaths after the ‘coregistration and interferogram formation’ process (i.e., BG–>ESD–>IFG–>DEB).
Here are some additional information after the coreg and ifg process.
Goldstein Phase Filtering
-Adaptive Filter Exponent: 1.0
-FFT Size: 64
-Windw Size: 3
Snaphu Export
-Statitical-cost mode: TOPO
-Initial method: MCF
-Number of Tile Rows and Columns: 20
-Number of Processors: 4
Row and Column Overlaps: 200
Tile Cost Threshold: 500
Lower the exponent to 0.4 during the Goldstein phase filter and check if less discontinuities are left after filtering.
Test different snaphu settings (MST or MCF, SMOOTH instead of TOPO, different tiling…)
Unwrapping can have problems for strong phase discontinuities or in shadow areas. There’s no ultimate solution to this. So you can only try different settings and compare.
I see. Unfortunately, I do not have any ascending images for the AOI, only descending images with one data pair satisfying the 150-300m perp baseline requirement.
FYI, the upper middle portion (with white to yellow colors) is actually a forested area. I hope to have the appropriate set of parameters to at least produce a reasonable S1 derived DEM.
I tried to lower the number of tile rows and columns (i.e., 5 and 1) few days ago while waiting for your suggestion but it always returns an error. I am stuck with 10 for both. I am relying now on the statistical-cost mode and initial method for the improvement if there is.
I’m trying to generate DEM in Snap software with Cosmo SKYmed images.
My datas have three difeerent temporal baseline (short, middle and long time).
I have made all processing step for DEM generation (coregistration-interferogram-goldstein phase filter-snaphu export-snaphu import-phase to elevation-range doppler terrain correction).
When I produced DEM, image have 2 bands (elevation and elevatin_VV).
1- Which is real InSAR DEM? I think “elevation_VV” isnt it?
2- When generate DEMs for all data, short baseline data have avarage 27 m error from my real DEM , in addition, other datas elevation_VV bands have so irrelevant values. Do you think what is the problem ?
The problem in your case is probably the perpendicular baseline. If it is too small, the fringes in the interferogram represent too much elevation difference.
Please have a look at the InSAR Stack tool to check the perpendicular baseline and the altitude of ambiguity of the image paris. The latter determines how much elevation difference is represented by one fringe.
Can you please also show the interferograms of the three pairs?
according to these guidelines a perpendicular baseline of 150-300 m is recommended. While the first one is clearly beyond that, the second ones are rather short.
I suspect that the first one suffers from baseline decorrelation (please check the notes on the critical baseline), the second ones are not detailled enough to provide information on fine topographic variations.
Lastly, temporal decorrelation clearly leads to low coherence and random phase signals in the second and third. Is there much vegetartion in your area?
the unwrapping parameters can help to remove smaller errors or tweak the best possible results, but they cannot restore information lost due to phase decorrelation.
Ideally, you have a 1-day image pair with 150-300 m of perpendicular baseline from the dry season with the least possible vegetation cover. That’s all you can do from the data acquisition side. If this still results in bad quality, there is too much vegetation in the area for proper interferometry.
I’m afraid, yes. Any place on earth with vegetation is difficult for interferometry unless you have bistatic data.
Please also have a look here: Generate DEM in forest area