Research On Surface Deformation Monitoring In Changning Area Based On InSAR Technology

Surface deformation has been one of the direct causes of secondary geological disasters,which brings a huge threat to the safety of human life and property.As a type of surface deformation,earthquake induced surface deformation may lead to secondary geological disasters such as landslides,collapses and falling off of dangerous rocks.Therefore,effective monitoring of surface deformation is particularly important.InSAR technology,as one of the new surface deformation monitoring methods,is widely used in surface deformation monitoring with the advantages of high coverage,high precision and all-weather observation.D-InSAR technology based on InSAR technology is to extract deformation information from two or more SAR images of different time phases in the same research area,and improve the monitoring accuracy to millimeter level.However,D-InSAR is also affected by atmospheric delay and spatiotemporal incoherence,while SBAS technology can obtain the long-term time-series shape rate information in the study area on the basis of D-InSAR,and can overcome the influence of atmospheric delay and spatiotemporal incoherence,so it is widely used in long-term surface deformation monitoring.On June 17,2019,an M_S6.0 earthquake occurred near Shuanghe town?28.34°N,104.90°E?,Changning County.In this paper,the"6.17"Changning earthquake deformation area is taken as the research area,supported by the 23 sceneries Sentinel-1A track raising data from October 24,2018 to July 27,2019 D-InSAR and SBAS techniques are used to process the deformation information of the study area,and on the basis of Okada dislocation model to simulate the inversion of coseismic deformation characteristics.The main work and research results are summarized as follows:?1?Based on InSAR technology,the application of D-InSAR and SBAS in surface deformation monitoring is mainly studied.Sentinel-1A data,DEM data and precise Orbit data required by the experiment are collected according to the research content,and Sentinel-1A data is preprocessed and the visibility of the research area is analyzed.?2?D-InSAR technology is used to deal with the two pairs of images of VV polarization and VH polarization in the study area respectively,obtain the differential interference deformation map,and compare and analyze the Changning earthquake deformation field according to the fringe map and the unwrapping map generated by the differential interference.The results show that the deformation field obtained from VV polarization data can reflect the seismic deformation area and deformation variables more effectively.?3?Based on the analysis results of D-InSAR,23 VV polarized Sentinel-1A orbit rising data from 20181024 to 20190727 are selected and processed by SBAS method.The long-time surface deformation rate and cumulative deformation variable map of Changning earthquake deformation field are obtained.The analysis shows that the deformation rate characteristics of the study area are consistent with the deformation trend monitored by D-InSAR,and the obvious deformation date is after the earthquake.?4?Through the downsampling of the deformation field obtained by D-InSAR and nonlinear inversion of the geometric parameters of the seismogenic fault in the seismic deformation area by Okada dislocation model,the seismic deformation field is inversed by linear simulation.The results show that the deformation area of the simulated deformation field is obvious,and the fault characteristics are obvious.The seismic moment of inversion is 9.09×10¹⁷Nm,and the magnitude of M_w6.0 is consistent with the national seismic survey center.?5?The results show that VV polarization data is more suitable for the extraction of deformation information in Changning earthquake deformation area.D-InSAR technology and SBAS technology can reflect the surface deformation characteristics in time and space,and Okada dislocation model can be used to simulate the inversion of deformation field to more directly reflect the deformation area and fault distribution.