Investigation for the Surface Deformation of Tanggula Mountain Permafrost Using Distributed Scatterer INSAR

Tanggula Mountain is located in the hinterland of Qinghai-Tibet Plateau (QTP), and the spatial distribution of permafrost has relatively strong heterogeneity. In recent years, permafrost is quickly degrading due to climate warming and human activities. The freeze-thaw cycles of the active layer on the permafrost cause seasonal uplift and subsidence. And it is difficult to accurately retrieve the surface deformation using the Temporarily Coherent Point synthetic aperture radar interferometry (TCPInSAR) in low-coherent permafrost areas, because there are few coherent targets identified in this area. To improve the density of measurement points, an improved TCPInSAR technique, namely Distributed Scatterers and Coherent Targets InSAR (DS-CTInSAR) is proposed in this paper. The Anderson-Darling (AD) test is used to extract statistically homogeneous pixels (SHP), and the regularized M-estimators method is adopted to estimate the covariance matrix, then the eigenvalue decomposition (EVD) method is used to estimate the optimal phase in this process. Applying this DS-CTInSAR algorithm to 29-C band Sentinel-1 images with a 12 days revisit time from 2019/1/10 to 2019/12/24, we find that this technology greatly improves the density of measurement points, and compared with the NSBAS technology, the two results are consistent, exhibiting good correlations 0.91. The InSAR results show that the average annual deformation rate is −24.87~23.61mm/yr in the study area.