Subsidence monitoring in coal area using time-series InSAR combining persistent scatterers and distributed scatterers |
| |
| Institution: | 1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;2. Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China;3. Department of Geoscience and Remote Sensing, Delft University of Technology, Delft 2628CN, the Netherlands;4. Key Laboratory of Land Subsidence Monitoring and Prevention, Ministry of Land and Resources, Shanghai 200072, China;1. Faculty of Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, China;2. State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China;3. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;4. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China;5. Department of Surveying and Geoinformatics, Nanjing University of Posts and Telecommunications, 9 Wenyuan Road, Nanjing 210023, China |
| |
| Abstract: | In coal mining areas, ground subsidence persistently happens, which produces serious environmental issues and affects the development of cities. To monitor the ground deformation due to coal mining, a modified time-series InSAR technique combining persistent scatterers (PSs) and distributed scatterers (DSs) is presented in this paper. In particular, DSs are efficiently identified using classified information and statistical characteristics. Furthermore, a two-scale network is introduced into traditional PSI to deal with PSs and DSs in a multi-layer framework by taking the advantage of the robust of PSs and the widely distribution of DSs. The proposed method is performed to investigate the subsidence of Huainan City, Anhui province (China), during 2012–2013 using 14 scenes of Radarsat-2 images. Experimental results show that the proposed method can ease the estimation complexity and significantly increase the spatial density of measurement points, which can provide more detailed deformation information. Result shows that there are obvious subsidence areas detected in the test site with subsidence velocity larger than 5 cm/year. The proposed method brings practical applications for non-urban area deformation monitoring. |
| |
| Keywords: | Coal mining InSAR Persistent scatterer (PS) Distributed scatterer (DS) Two-scale network |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
