Surface Subsidence Monitoring Induced by Underground Coal Mining by Combining DInSAR and UAV Photogrammetry

Abstract

Surface subsidence caused by coal mining has become an important factor that affects and restricts the sustainable development of mining districts. It is necessary to use appropriate methods for effective subsidence monitoring. It is hard to monitor large gradient ground deformations with a high accuracy by using differential interferometric synthetic aperture radar (DInSAR) technology. Unmanned aerial vehicle (UAV) photogrammetry is limited in that it monitors the basin edge by subtracting two DEMs (digital elevation models). Therefore, in this paper we propose a combination of DInSAR and UAV photogrammetry to complement the two data advantages and to achieve a high-precision monitoring of mining subsidence areas. The subsidence of coal panel 81,403 in the Yangquan coal mine was obtained using DInSAR and UAV photogrammetry technologies. The appropriate fusion points were selected for the two datasets and the agreement between the fusion data and the leveling data was verified. The results indicated that the combination of DInSAR and UAV technology could monitor the settlement more accurately than the single use of DInSAR or UAV technology.