Hybrid of Two Persistent Scatterer Interferometry Methods in Order to Subsidence Monitoring

Temporal and geometrical decorrelation often prevents SAR conventional interferometry from being an operational tool for surface deformation monitoring. Persistent Scatterer Interferometry (PSI) techniques presented to overcome the limitation of SAR conventional interferometry and use amplitude analysis and considering temporal deformation model for PS pixel selection fail to identify PS pixels in rural areas lacking man-made structures. On the other hand, the high subsidence rates lead to not be fulfilled the required condition for unwrapping (Nyquist sampling criterion) and significant phase unwrapping errors in novel PSI algorithm (StaMPS) that applies amplitude analysis as well as phase stability in order to select the PS pixels without using a pre-define deformation model. Therefore, in this paper we present an enhanced algorithm based on PSI in order to estimate deformation rate in rural area undergoing high and nearly constant deformation rate using the available SAR images. The proposed approach integrates the merits of all existing PSI algorithms in PS pixel selection and phase unwrapping. PS pixels are selected based on the amplitude information and phase stability and their phase are compensated for APS and nonlinear deformation contribution by applying temporal filter. Deformation rate is then estimated using LAMBDA method that is a fast and optimal without considering Niquist sampling criterion. The approach was applied to the ENVISAT ASAR images of Southwestern Tehran basin and the results were evaluated with leveling data and the maximum difference rate across the leveling stations was 5 cm/yr demonstrating the high performance of the proposed algorithm in comparison with the obtained results from other interferometry methods. Moreover, the presented algorithm was applied to the simulated data and the value of RMSE was obtained 0.003 m/yr confirming this success.