Reserch On Mining Subsidence Monitoring Based On SAR Image Information

Coal mining subsidence has caused problems such as soil degradation,vegetation destruction and damage to ancillary buildings(structures)in the mining area,breaking the ecological balance in the mining area and seriously affecting people's production and life.Under the urgent need of disaster prevention and reduction by the government,it is of great significance to accurately identify and monitor mining subsidence in real time with advanced monitoring means for early warning of mining subsidence damage,restoration of ecological environment and sustainable development.InSAR technology is a large range,high aging,high precision surface deformation monitoring tool,using the SAR image phase information,can accurately measure the surface movement of the mining basin edge small deformation;However,in the region with large deformation magnitude and fast deformation rate,the incoherence is serious and cannot be monitored.Aiming at the above problems,this paper takes yangquan mining area as an example to study how to use SAR image phase and amplitude information to accurately and effectively detect and obtain deformation information of large gradient and large number of grade areas in the mining area.Its main research work and achievements are summarized as follows:(1)Summarized the domestic research status and main problems of extracting large amount of deformation in mining areas based on SAR image phase information and amplitude information,and introduced the basic principle and error sources of InSAR/DInSAR technology.(2)According to the deformation characteristics and deformation rates of static and dynamic surface moving basins in different regions and stages,the mining subsidence monitoring methods of InSAR are summarized as static monitoring and dynamic monitoring in combination with the different periods of InSAR monitoring of surface moving basins.The ability of Sentinel-1A image data with C band and resolution of 20 m to monitor the surface deformation of mining area using static and dynamic methods was analyzed.(3)A method of integrating DInSAR and probabilistic integral data to extract large amount of deformation in mining area was proposed.Considering the influence of deformation monitoring gradient and various errors of DInSAR technology,two thresholds of deformation gradient value and three times median error of monitoring data are used to screen DInSAR monitoring value and probability integration predicted data,and the fusion results are compared with the measured results.The results show that the method can screen out reliable DInSAR monitoring values and improve the accuracy of DInSAR monitoring at the working face boundary.At the same time,the fusion data has a high correlation with leveling data,which can better study the large-scale deformation in the mining area,and enrich the method of DInSAR technology and probability integration method to extract large-scale subsidence in the mining area.(4)A method of using SAR image amplitude information to identify large scale subsidence areas in mining areas was proposed.Based on the amplitude information of SAR image,the time-series amplitude analysis method is used to extract the time-series surface backscattering coefficient of mining subsidence area.According to the time-series variation characteristics of surface backscattering coefficient in different regions of subsidence basin during mining activities,it is found that the surface backscattering coefficient has a high correlation with the surface subsidence rate.The results show that the surface backscattering coefficient can be used to describe the change of surface settlement rate in a large number of subsidence areas,and the dynamic surface settlement rate law can be well analyzed.The technique of using SAR image to identify a large number of subsidence areas has a good application prospect.