Abstract
Abstract. Persistent Scatterer Interferometry for SAR data (PSInSAR) improves the ability of conventional InSAR time-series methods by detecting and analysing pixels where the portion of spatiotemporal decorrelations on the phase is negligible. Using dual/quad polarized SAR data provide us with an additional source of information to improve further the capability of InSAR analysis. In this paper, we present a method to enhance PSInSAR using polarimetric optimization method on multi-temporal polarimetric SAR data. The optimization process has been implemented to minimize the Amplitude dispersion Index (ADI) of pixels in SAR images over the time based on the best scattering mechanism. We evaluated the method on a dataset including 17 dual polarization SAR data (HH/VV) acquired by TerraSAR-X data from July 2013 to January 2014 over Tehran plain, Iran. The area has been affected by high rate (> 20 cm/yr.) of surface subsidence due to groundwater overexploitation. The effectiveness of the method is compared for both agricultural and urban regions affected by land subsidence. Furthermore single pole and optimized polarization results are compared together and with external observations from GPS measurements. The results reveal that using optimum scattering mechanism decreases the ADI values in urban and non-urban regions and increase the PS Candidate pixels (PSC) about three times and subsequently improves the PS density about 50% more than using single channel datasets.
Highlights
Differential Interferometric SAR (DInSAR) technique is a powerful technique to map surface deformations in a wide area with high spatial resolution (Massonnet et al, 1993; Amelung et al, 1999; Lu et al, 2005; Li et al, 2008; Motagh et al, 2010)
We evaluated a method to combine Amplitude Dispersion Index optimization with phase stability criteria and temporal coherence to improve the performance of Stanford Method for Persistent Scatterers (StaMPS) method for Persistent Scatterer Interferometric SAR (PSInSAR) analysis using dual polarimtery SAR data
Our finding shows that implementing phase stability criteria after this step meaningfully improves the density of PSC/PS pixels in both urban and non-urban regions
Summary
Differential Interferometric SAR (DInSAR) technique is a powerful technique to map surface deformations in a wide area with high spatial resolution (Massonnet et al, 1993; Amelung et al, 1999; Lu et al, 2005; Li et al, 2008; Motagh et al, 2010). To analyse the surface deformation in time and space, time-series analysis of Synthetic Aperture Radar, i.e., Small Baseline Subsets (SBAS) and Persistent Scatterer Interferometric SAR (PSInSAR) is needed to be applied. These methods extend the capabilities of InSAR technique by identifying and processing pixels with negligible effect of decorrelations (Ferretti et al, 2001; Mora et al, 2002; Hooper et al, 2007). The improvement is based on minimizing ADI criteria for selecting PSC pixels in dual polarimetry X-band SAR data, which is followed by reproducing the SAR scenes in optimized scattering mechanism before applying StaMPS method for PS analysis. We test our method for a dataset of 17 dual polarization X-band SAR data (HH/VV) acquired by TerraSAR-X satellite between July 2013 and January 2014 over Tehran plain
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