Land subsidence processes in deep mining areas have long time durations, and land deformation models should be obtained using many field observations. In this paper, the capability of monitoring deep mining subsidence of ALOS PALSAR pairs with short and long time baselines has been investigated in the area of Xuzhou, Jiangsu province. For the image pairs with poor temporal baselines, it is difficult to correctly generate the whole subsidence basin, and more information is lost in the areas that have rapid changes in deformation and vegetation. Therefore, an approach combining differential interferometric synthetic aperture radar (D-InSAR) results and probability integral model (PIM) results, to generate the whole mining subsidence basin, is proposed. D-InSAR-derived subsidence observations are used to deduce prediction parameters, and then the parameters and mining conditions of working faces are used in a probability integral model to obtain the whole subsidence basin. The results are compared with levelling field survey data, and the prediction results and levelling measurements agree well with each other.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.