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sorry, you are right.
The cumulative displacement is calculated using the model you chose for the time series analysis.
This reduces possible noise.

The time series in the site processing are referred to the first acquisition.
In the small area processing you can choose whether to refer them to the first acquisition or to the Master one.
However the Master acquisition may be noisy, so, the sw estimates an error and it removes it (so, the value at the master may be not zero).
The cumulative…[Read more]

yes, that is something to be tided up.
Initially, the Cum Disp tool was generated to calculate it based on the estimated coefficients of a polynomial.
Later on, I invented the smart tool, which is a non-parametric time series analysis.
So, the Cum Disp tool is consistent with the rest of the results (and it calculates the proper things) only if…[Read more]

The small area processing has been designed as a process independent from the full site analysis. Even if they can interact (see b).
So, my suggestion is:
(a) if you want to carry out different processing sessions with different parameters, you should save every time a different small area dataset. You do this using the “save” button in the small…[Read more]

Hi Santiago,
this is a small misunderstanding. To answer your question we firstly need to clarify some parameter names.
– Temporal Coherence: it’s the coherence calculated from the time series phase residues (the classic PSI parameter)
– Synthetic Coherence: it will be removed. It was a simulation
– Spatial Coherence: it’s the mean interferometric…[Read more]

Hi Santiago,
this is a small misunderstanding. To answer your question we firstly need to clarify some parameter names.
– Temporal Coherence: it’s the coherence calculated from the time series phase residues (the classic PSI parameter)
– Synthetic Coherence: it will be removed. It was a simulation
– Spatial Coherence: it’s the mean interferometric…[Read more]

Hi Santiago,
this is a small misunderstanding. To answer your question we firstly need to clarify some parameter names.
– Temporal Coherence: it’s the coherence calculated from the time series phase residues (the classic PSI parameter)
– Synthetic Coherence: it will be removed. It was a simulation
– Spatial Coherence: it’s the mean interferometric…[Read more]

-local maxima extraction with range lobes suppression
-local maxima extraction with range and azimuth lobes suppression

these two options are useful for suppressing ghost targets generated by side lobes of the impulse response of the system (cardinal sine). in fact, side lobes could already be suppressed by filters used in the focusing process.…[Read more]

in Such a case, I suggest you to read directly the data from the disk.
All parameters are written as matrixes SxL -float- (real or complex depending on the case).
you can use the function leggi included in the pcodes
Data=leggi(FileName,S,L);
FileName is a string containing the name of the file with full path.
S and L are samples and lines.
This…[Read more]

If you have more images, use them.
Using more images makes all statistical parameters more stable, and estimates are much more accurate.
If you are interested only in a given period of time, you will focus your attention there. But you have to use all images you can get.
You can e.g. use the ampl. stab. index estimated on many more images, get the…[Read more]

What Yuxiao says is partly not correct.
If the Doppler polynomial is precise, Sarproz does the job of resampling the image in the right way.
The problem is that those images highly probably do not have a reliable Doppler polynomial.
If this is the case, you will get lots of problems.
If on the contrary the Doppler polynomial is correct, you can…[Read more]

a. UW means unwrapped.
If you check it, the sw will try to read UW interferograms. Then, the multi-temporal processing (estimation of parameters) will work using Least Squares (instead of the maximization of the periodogram).

b. Ext DEM means removing the external DEM from time series.

c. the connections (temporal) coherence is calculated as…[Read more]

the title of this post is pretty misleading.
insar is relative, but it can still be accurate.
so, deformation trend, time series, cumulative displacement and any other insar product are RELATIVE to a reference point.
unless you know whether the ref. point is stable, your measurements will always be RELATIVE to it.
the true displacement value does…[Read more]

On the contrary, I believe the net disk is the major problem.
Can you check the network usage?
Or can you simply try to copy the dataset locally? Note that you do not need the SLC folder. So, I believe the rest of the folders should be quite small.

On the contrary, I believe the net disk is the major problem.
Can you check the network usage?
Or can you simply try to copy the dataset locally? Note that you do not need the SLC folder. So, I believe the rest of the folders should be quite small.

there is no evident reason for your problem
the file is 2.2MB, less than 1.5e6 points
loading the file in matlab takes a few seconds
I am wondering whether you could have problems affecting matlab and/or windows installation.
or maybe some problems in reading/writing operations: is the file on a local or external disk?
which kind of disk are you…[Read more]

the mask file is independent from the number of images
it would be nice to know how big is maschera.mat, and which is the size of your dataset (samples and lines).
by the way, which option did you use for mask generation?
are you working with windows? what’s the size of the RAM?

given the infos you posted,
I expect the geocoding through external DEM to work well

download manually the following file and place it into the same folder of main.exe
http://the.earth.li/~sgtatham/putty/latest/x86/psftp.exe

download manually the following file and place it into the same folder of main.exe
http://the.earth.li/~sgtatham/putty/latest/x86/psftp.exe