Analysis of deformation characteristics of Xishan Loess Landslide based on time series InSAR technology
Loess landslides have the characteristics of wide range,susceptibility to rainfall,and high harmfulness,which makes their monitoring significant.However,traditional surface deformation monitoring techniques are time-consuming and laborious.In this study,the Xishan Loess Landslide in Tongren city,Qinghai province is taken as an example,the Small Baseline Subsets Interferometric Synthetic Aperture Radar(SBAS-InSAR)technique has been used to register,differential interferometry,filtering,phase unwrapping,reflatten,deformation modeling and calculation of Sentinel-1A 48 scene orbit data from March 20,2017 to December 24,2021 in the study area,and obtain the temporal deformation characteristics of the area.The results show that there are two obvious deformation areas in the Xishan landslide group.The first area is located in the northeast of the study area,with an annual average deformation rate in the direction of radar line of sight ranging from-34.27 to 2.73mm/a.The other area is located in the central part of the research area,with an annual average deformation rate in the direction of radar line of sight ranging from-30.27 to 4.20mm/a.Further combined with the analysis of the total monthly rainfall in Tongren city during this period,it is shown that rainfall has a positive feedback effect on the landslide deformation rate.Based on the result analysis and field investigation,it is shown that the SBAS-InSAR technology is effective in monitoring landslide deformation,and it provides effective technical support for the prevention and control of landslide disasters in this area.Furthermore,based on the analysis of the total monthly rainfall during this time period in Tongren city,the landslide deformation rate is positively correlated with the total monthly rainfall.Based on results analysis and field investigations,the effectiveness of SBAS-InSAR technology in landslide deformation monitoring has been demonstrated,providing effective technical supports for landslide disaster prevention and control in the region.
NETL
NSTL
万方数据
