Satellite Remote Sensing Estimation of Ground Subsidence along Transmission and Transformation Lines Based on Multi-scale Geographically Weighted Regression

Abstract

In this paper, a 5km area along the 750kV Third passage project in Shaanxi Province is taken as the research area. Based on the analysis of the application and limitation of traditional two-dimensional regression model in land subsidence simulation, the advantages of multi-scale geographical weighted regression model in automatically calculating bandwidth and exploring spatial heterogeneity of impact factors are explored. Based on the geological environment of the region and the latest geological disaster data, seven influencing factors including slope, topographic relief, average annual rainfall, topographic humidity index (TWI), distance from river, distance from fault and distance from road were selected as dependent variables, and the SBAS-InSAR results covering the whole region were taken as independent variables. On the basis of evaluation factor analysis, The land subsidence results along the 750kV third passage project in northern Shaanxi and Guanzhong were simulated by ArcGIS platform. The evaluation results show that the fault distance and precipitation in the study area have great influence.