Prediction Of 3D Surface Deformation In Mining Area Based On Time Series InSAR

Interferometric synthetic aperture radar(InSAR)is a kind of earth observation technology which has attracted much attention in recent years.It is favored by experts and scholars because it is different from the traditional observation technology and can obtain the surface deformation information in all day,all-weather and large range.After decades of continuous development and technological progress,people have researched and developed synthetic aperture radar differential interferometry(D-InSAR),multi temporal InSAR(MT InSAR)and multi aperture InSAR(MAI)based on InSAR technology In addition,it has done a lot of research in many fields,such as urban surface subsidence,landslides,mining subsidence,glacier drift and so on.The surface subsidence caused by mining resources in mining area will bring a series of problems such as ecology,economy and social security.Therefore,it is of great significance to establish the surface subsidence model of mining area by using InSAR technology and study the temporal and spatial evolution law of surface subsidence after mining resources.Because the traditional D-InSAR technology can only obtain the line of sight(LOS)deformation of the surface,it can not reflect the actual three-dimensional deformation information of the surface in space,and can not accurately extract the large gradient deformation information of the surface.In view of these problems,this paper intends to use SBAS InSAR technology to obtain the time series deformation information of the mining area surface,extract the deformation variables of the mining area surface in the horizontal plane,and predict the vertical deformation value of the mining area surface combined with the power exponent knoth time function model,and finally establish the mining area surface three-dimensional deformation model.The main achievements are as follows.(1)This paper analyzes and studies the current domestic and foreign research status of mining surface subsidence monitoring,as well as the main technical means and results of monitoring,and analyzes which monitoring method is more suitable according to the conditions of the selected area to be studied.In view of the problems that traditional monitoring methods can not obtain large-scale surface deformation information of mining area,the surface water accumulation area of the study area is large,and there are many weeds and shrubs covering,and taking into account the research data accessibility,economic adaptability,radar band penetration effect and other factors,the appropriate radar image data and radar image processing methods are selected to obtain the surface time series deformation value.(2)The unknown parameters of the power exponent knoth time function model are retrieved by using the time series InSAR monitoring data of the mining area,and the maximum subsidence value of the surface monitoring points in the study area is predicted by using the power exponent knoth time function model.Due to the large gradient of surface subsidence in the mining area,it is beyond the monitoring range of conventional D-InSAR technology,so it is unable to accurately obtain the surface subsidence value of the mining area.In this paper,the SBAS InSAR technology is used to process the SAR image of the mining area to obtain the time series deformation value of the surface.According to the surface deformation value of the mining area,the particle swarm optimization(PSO)algorithm is used to retrieve the parameters of the exponential knoth time function model,and the subsidence curve model of the surface monitoring points is established.Finally,the final deformation value of the mining area surface points is predicted according to the established subsidence model.(3)Through the combination of theoretical research and practical engineering cases,the 3D deformation information of mining area surface is extracted,and the 3D deformation subsidence prediction model is constructed.In this paper,according to the line of sight(LOS)deformation value of radar,the relationship components and vertical deformation variables in the horizontal plane in the east-west and North-South directions are derived,and the three-dimensional information is extracted from the time series deformation results of the study area obtained by the time series InSAR technology.Combined with the mining area surface horizontal deformation extracted from the final deformation value obtained by time series InSAR and the vertical component extracted from the mining area surface based on the power exponent knoth model,a three-dimensional surface deformation subsidence prediction model is constructed.Combined with a coal mining face in Huainan mining area,the 3D deformation prediction model is used to extract the surface deformation information and construct the 3D deformation model.At the same time,the measured leveling data and plane CORS data of the surface movement and deformation observation station are collected to verify the established model.The results show that,according to the selected several representative subsidence feature points,the verification results show that:compared with the standard value,the maximum average error of the time series InSAR monitoring value is 0.0219m,and the maximum mean error is 0.0352m;compared with the standard value,the maximum average error of the model fitting subsidence value is 0.0308m,and the maximum mean error is 0.0423m.Figure[34]table[9]reference[134]...