Abstract:The Yellow river delta region has many wetlands, farmlands and large areas, making it difficult for PS-InSAR technology to obtain high-density surface deformation information. In this paper, we study a surface deformation monitoring method of Yellow river delta based on distributed scatterers InSAR(DS-InSAR). In this method, we select homogeneous pixel points through confidence interval estimation, then we extract the corresponding phase value of dominant scatterers by eigenvalue decomposition method to achieve phase optimization. We determine distributed scatterers according to spatio-temporal coherence, and finally solve time-series surface deformation information. Using 26 Sentinel-1A images as data sources, we extract the surface subsidence information of the Yellow river delta from December 2019 to December 2020. Compared with the results of the PS-InSAR method, the point density increases by 5.56 times. The correlation coefficient between the points with the same name and the deformation rate obtained by this method is 0.727, indicating that the two methods are in good agreement. The experimental results showed that there are four obvious subsidence areas in the studied area, and the maximum subsidence rate was -238 mm/a. Analysis and field investigation show that the main influencing factors are underground brine and oil and gas exploitation.
CAO Jiantao,ZHENG Xiangyuan,FAN Hongdong et al. Surface Deformation Monitoring in the Yellow River Delta by Using DS-InSAR Technique[J]. jgg, 2022, 42(11): 1177-1183.