Subsidence monitoring in coal area using time-series InSAR combining persistent scatterers and distributed scatterers

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.