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<< Click to Display Table of Contents >> Interferometric Stacking - Persistent Scatterers - E-PS - Adaptative Filtering |
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Purpose
The purpose of this functionality is to enhance the standard Persistent Scatterer (PS) analysis in rural areas by implementing adaptive filtering on the interferometric phase.
This approach is inspired by the works of Ferretti (2011) and Fornaro (2015). The joint processing of PS and Distributed Scatterers (DS) can be performed independently.
To achieve this, two main steps are required. Firstly, the identification of statistically similar pixel ensembles must be conducted. This involves utilizing the Kolmogorov-Smirnov (KS) and Anderson-Darling (AD) tests based on the amplitude of a co-registered and calibrated stack of SAR data.
Secondly, for all DS identified through the statistical tests, the covariance matrix is estimated by leveraging the ensemble of similar pixels. The SLC phases corresponding to DS are optimally weighted using either the maximum likelihood estimator (MLE) under the assumption of Gaussianity, or by exploiting the largest principal component of the covariance matrix. DS exhibiting a coherence higher than a specified threshold are jointly processed with PS for the final estimation of the displacement time series.
Technical Note
After the interferograms generation, an offset phase is removed from all interferograms.
One or more pixels (Reference Points) are automatically selected by the program for the calculation of the phase offset to remove.
The number of the 'Reference Points' depends on the size of the Area of Interest. As default, just one 'Reference Point' is selected for Areas within 25 km2, (refer to the Preferences>Persistent Scatterers>Area for Single Reference Point).
At this point, the algorithm can follows two kind of directions:
•Areas of analysis with size within the value specified by the 'Area for Single Reference Point' parameter are processed using just one 'Reference point' for the entire Area.
•A second approach is carried out when larger Area has to be analyzed. Then the entire area is splitted into more sub-areas taking into account the overlap percentage too, each one with size corresponded to the input parameter. Every sub areas is processed in independent way. Finally, a mosaicing operation is carried out to merge all sub - areas and getting the whole result.
From this stage all the re-flattened interferograms, together with the phase-height pair-by-pair proportionality factors (_k_factor files, which are stored in the "work/work_interferogram_stacking"), are used to estimate the residual height and the displacement related information (i.e. velocity), which are known as low pass components. These components are removed from the re-flattened interferograms before the atmosphere estimation process takes place.
Unlike the SBAS tool, just one model is implemented:
•Linear Model, to estimate residual height and displacement velocity.
The model can be synthesized as follows:
Disp = V*(t-t0)
where Disp is the displacement at time t; V is the displacement velocity.
Input Files
Auxiliary file
Reference file generated as output of the "Connection Graph" step and possibly updated afterwards. This file is mandatory.
Parameters - Principal Parameters
Shp Map Method
This corresponds to Identification of statistically homogeneous areas (Distributed Scatterers). Two statistical tests are available:
• Kolmogorv-Smirnov (KS)
• Anderson Darling (AD)
Win Az Size (m)
This corresponds to the size of window azimuth size, expressed in meters, used by the adaptive filter.
Win Rg Size (m)
This corresponds to the size of window range size, expressed in meters, used by the adaptive filter.
Adaptive Filtering Method
This corresponds to Adaptive Spatial Phase Multilooking via Covariance Matrix to filter the DSs. Two filtering methods are available:
• Maximum Likelihood Estimation (MLE)
• Principal Component Analysis (PCA)
DS threshold
This corresponds to the threshold used to discriminate PS and DS pixels, based on the statistically homogeneous pixel map. This is retrived through the statistical test listed in the Shp Map Method filed.
The filtering is not applied to those pixels with values lower than this threshold.
Delete orig dint files
By setting this flag the original dint, generated during the interferometry step, are deleted.
Activate Filtering batch Mode
By setting this flag the Adaptive Filtering process executed in batch mode.
Batch size (acq number)
It refers to the number of acquisitions.
Rebuild All
By setting this flag the whole PS Inversion process is started from scratch.
It is advisable to leave this flag unchecked in case of process interruption, so that the products already generated have not to be computed and stored again.
Parameters - Interferogram
It brings to the interferometry section of the Preferences parameters. Any modified value will be used and stored for further processing sessions.
Parameters - Global
It brings to the general section of the Preferences parameters. Any modified value will be used and stored for further processing sessions.
Parameters - Other Parameters
It brings to the general section of the Preferences parameters. Any modified value will be used and stored for further processing sessions.
Output Files
Two sub-folders are created below the path: ProjectName_PS_processing\work\work_interferogram_stacking; the name of the two folders are Filtered and Map.
Filtered:
Directory containing the following products:
•_rsp_slc, corresponding to the filtered and coregistered SLC data.
•cc_ds, corresponding to the multitemporal coherence of the DS pixels.
•cc_ds_avg, corresponding to the average multitemporal coherence. it is generated only in case the batch mode has been enable.
Map:
Directory containing the following product:
•KS/AD_shp_neighbors, corresponding to the number of statistically homogeneous pixels. Each value ranges between 1 and the maximum value of the window (rg x az size).
The folder work_interferogram_stacking contains also the _fil_DS_dint files which correspond to the filtered interferograms.
Details specific to the Units of Measure and Nomenclature of the output products can be found in the Data Format section.
General Functions
Exec
The processing step is executed.
Store Batch
The processing step is stored in the batch list. The Batch Browser button allows to load the batch processing list.
Close
The window will be closed.
Help
Specific help document section.
Specific Function(s)
None.
Task, SARscapeBatch object, SARscapeBatch script example
References A. M. Guarnieri and S. Tebaldini, "On the Exploitation of Target Statistics for SAR Interferometry Applications," in IEEE Transactions on Geoscience and Remote Sensing” A. Ferretti, A. Fumagalli, F. Novali, C. Prati, F. Rocca and A. Rucci, "A New Algorithm for Processing Interferometric Data-Stacks: SqueeSAR," in IEEE Transactions on Geoscience and Remote Sensing. Fornaro, Gianfranco, et al. "CAESAR: An Approach Based on Covariance Matrix Decomposition to Improve Multibaseline-Multitemporal Interferometric SAR Processing." IEEE Transactions on Geoscience and Remote Sensing 53.4 (2015): 2050-2065.Lin, K.-F.