Automatic Change Detection from Remote Sensing Stereo Image for Large Surface Coal Mining Area

Abstract

Surface mining activities may cause the significant change of the topography and stability of landscape, which may lead to a series of environmental issues, such as water runoff, soil erosion and vegetation degradation. Thus, the characteristic of artificial landscapes should be concerned for reconstruction of mining ecosystems. Remote sensing imagery, particularly stereo image with the advantage of generating digital elevation model (DEM) efficiently can provide information of topography from the surface mining area. The purpose of this study is to monitor topographic change using remote sensing stereo image in large surface coal mine. In this study the ASTER stereo imageries collected in 2002 and 2006 were used to generate DEM. Quantitative methods such as the RMSE and topography profile were conducted to evaluate the accuracy of the ASTER DEM based on the reference 1:50000 topography map. Furthermore, the change of topographic which can be detected were developed based on the image difference by setting a threshold value and watershed transform method. The results indicated that: root-mean-square errors (RMSEs) in elevation are 25m for ASTER DEM in 2002, and 26m for ASTER DEM in 2006. The topographic change from open pit at 2002 and dump at 2006 was automatically and accurately detected, which provided quantitative information for exploiting-peeling-deserting unification of mining. Such piece of information would be very useful in mining rehabilitation and ecology restoration.