Abstract:In this paper, we use the synthetic aperture radar time series analysis method to analyze the deformation of Yangjuzhuang, a residential area in the Huainan mining area. We use 13 consecutive Sentinel satellite radar images from December 2016 to May 2017 (one cycle of 12 d). According to the deformation characteristics of the mining area, we propose a combined prediction model of grey support vector machine (GM-SVR) to predict the deformation of the mining area. The results of this model are compared with the results of the traditional single gray model and the support vector machine prediction model. The results show that the combination of InSAR time series analysis technology and the GM-SVR model can realize the rapid deformation monitoring and disaster prevention of the mining area, and provide a new method for the monitoring and early warning of mining disasters.
LI Jinchao,GAO Fei,LU Jiaguo et al. Deformation Monitoring and Prediction of Residential Areas Based on SBAS-InSAR and GM-SVR[J]. jgg, 2019, 39(8): 837-842.