A model for extracting large deformation mining subsidence using D-InSAR technique and probability integral method
(1. Jiangsu Key Laboratory of Resources and Environmental Information Engineering,
China University of Mining and Technology, Xuzhou 221116, China;
2. School of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, China;
3. Zhejiang Geological Prospecting Institute, China Chemical Geology and Mine Bureau, Hangzhou 310002, China)
China University of Mining and Technology, Xuzhou 221116, China;
2. School of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, China;
3. Zhejiang Geological Prospecting Institute, China Chemical Geology and Mine Bureau, Hangzhou 310002, China)
Abstract: Due to the difficulties in obtaining large deformation mining subsidence using differential Interferometric Synthetic Aperture Radar (D-InSAR) alone, a new algorithm was proposed to extract large deformation mining subsidence using D-InSAR technique and probability integral method. The details of the algorithm are as follows: the control points set, containing correct phase unwrapping points on the subsidence basin edge generated by D-InSAR and several observation points (near the maximum subsidence and inflection points), was established at first; genetic algorithm (GA) was then used to optimize the parameters of probability integral method; at last, the surface subsidence was deduced according to the optimum parameters. The results of the experiment in Huaibei mining area, China, show that the presented method can generate the correct mining subsidence basin with a few surface observations, and the relative error of maximum subsidence point is about 8.3%, which is much better than that of conventional D-InSAR (relative error is 68.0%).
Key words: D-InSAR; genetic algorithm; probability integral method; mining subsidence