Study On Monitoring The Time Series Ground Deformation In Mining Area Based On CRInSAR And PSInSAR Integration

Our country is densly distributed with mining resourses. There are frequent minning activity and mine geological disasters in our country. Through the long term dynamical monitoring and real-time analysis of the mining area, the ground deformation and damage extent can be controlled, which are of great importantance to prevent the potential geological damage. The'differential Interferometric Synthetic Aparture Radar (DInSAR) is a newly developed ground deformation monitoring technique recently, but it may be influnced by the spatial and temperial deccorelation greatly, thus can not accordant with the requirement of high accuracy and real-time monitoring. Both the PSInSAR and CRInSAR technique are means of deformation monitoring based on time series of magnitude of Permanent Scatters (PS), which can maintain steady radar reflectivity over years, they can not be influnced that greatly by the spatial and temperial deccorelation. After differencing the phases of neighborhood PS points, the effect of atmospheric delay can be greatly weakened. Due to these, the paper will focused the study on the combination of the two techniques and apply it in the monitoring of mining subsidence, in order to improve the monitoring reliability and precision of the ground deformation.The paper demonstrates and discusseses the theory, the processing flow, the algorithm and reliability assessment in detail respectively, and presents a CRInSAR and PSInSAR combined calculation algorithm. Among this, the paper focused the study on the identification of CR points and PS points, PS-CR network forming, PS-CR combined calculation algorithm flow designing, neighborbood differential phases modeling based on linear and periodicity function modeling respectively and the algorithm of spatial and temperial phase unwrapping. The investigations and contributions performed in this paper are outlined as follows:1. A new method for CR point identification is presented, which is based on the comprehensive assessment index of the intensity and correlation coefficient. This method is used to find the CR points in the six SAR images of the study areas respectively, and the distances between the two consecutive CR points in different SAR images are used to verify the accuracy of the results. The results show that the accuracy of the new method can reach to a pixel.2. An algorithm based on combining the method of coherence factor, amplitude deviation and amplitude index thresholding is designed, which is applied in the identification of PS points over the study area with use of14SAR images. The standard deviations of amplitude, phase and coherence factor are taken as the stability analysis tool to analyze the stability of the PS candidates.3. The PS-CR integrated baseline network layout and information storage solution is propsed, on basis of which the linear and periodic deformation differential phase model on either baseline in the PS-CR integrated baseline network are established. The Delaunay triangle with distance restriction principle is applied in the process of baseline network layout, and the ajcent array model is used to store the baseline network information, which can also resolve the problem of repeated baseline detection;4. The spatial and temperal phase unwrapping algorithm in PSInSAR and CRInSAR is proposed. With use of the subsidence rates and elevation corrections calculated on the CR points as constraint for the PS network over the study area, the new algorithm estimates the global optimum solutions of subsidence rates and elevation corrections in the PS network using the parametric adjustment method. The algorithm achieves the integration of CRInSAR and PSInSAR effectively. It can revise the unreasonable uplifting points thus can reflect the subsidence truth in the area more reasonablely. It can also be more widely applied in monitoring subsidence of area without external data.5. An integrated CRInSAR and PSInSAR combined calculation algorithm and flow is proposed, which achieves effectively the combination of both techniques. In order to validate the combined calculation algorithm flow, both the simulation and real data experiments are conducted. From the simulation experiment, it can be seen that the results with the combined calculation algorithm shows better precision after adding the CR points as constraint, which validated the feasibility theoretically. In the real data experiment, the combined calculation algorithm is applied in a colliery densely distributed area around Baisha reservoir for the first time. Firstly, the linear model is used in order to detect the linear velosities in the area, the results validated that comparing to the results of the traditional PSInSAR algoritm, the new method can revise the unreasonable uplifting points thus can be more accordant with that of the leveling; Secondly, in order to study the time series of evolutionary subsidence process in the mining area, the paper chose the area closely nearby the Baisha reservoir to analysis, using the periodic function model as the deformation differential phase model. It can be seen from the results that the area experienced obviousely subsidence and the deformation magnitude accumulated to10cm over the area where colleries distribute. The results show that the accuracy can be±2.1mm with the leveling data being used as the external validation data.