西部黄土覆盖区是我国重要的煤炭生产基地，地貌及地质采矿条件复杂，黄土层厚度巨大，开采沉陷具有不同于其它矿区的特殊性，地表下沉速度大，起动距偏小，采动裂缝等非连续破坏更为严重，地表沉陷盆地形状和沉陷变形分布特征更为复杂多变。在当前技术条件下开展地表沉陷的高效监测和定量评价仍面临一定困难。近年来，合成孔径雷达干涉测量(InSAR)、无人机摄影测量(UAV photogrammetry)、激光雷达(LiDAR)等多源遥感技术迅速发展，其具备的非接触式观测、大范围覆盖、高时空分辨率等特点，能够实现地表沉陷连续性、动态性和全面性监测，通过多源观测数据的融合处理，可为西部矿区开采沉陷高效监测提供新的技术途径。综述了多源遥感技术在矿区沉陷监测中的应用进展；通过现场试验探索了InSAR、UAV photogrammetry、LiDAR用于黄土高原矿区沉陷监测的实际效果，发现在地貌复杂、地形起伏和植被覆盖及地表大梯度形变条件下， InSAR干涉失相关和大气延迟等各种误差过大；无人机航测影像构建的三维模型受植被和地形影响导致地面模型的高程精度不足；无人机激光扫描受地形坡度、点云密度和地表点水平移动的综合影响导致显著的DEM模型误差，因而当前条件下多源遥感技术均存在各自的优势、局限性和技术瓶颈。在此基础上，提出了黄土沟壑区地面点云提取及地表三维变形信息获取的算法流程；指出了基于多源遥感数据融合实现矿区沉陷三维位移精准、高效监测的技术路径；展望了构建矿区沉陷多源遥感监测智能化体系的应用前景。

The western loess-covered area is an important coal production base in China, with complex geomorphology and geological mining conditions, huge thickness of loess layer, mining subsidence with special characteristics different from other mining areas, large surface subsidence rate, small starting distance, more serious discontinuous damage such as mining cracks, and more complicated and changeable characteristics of the shape of the surface subsidence basin and the distribution of subsidence deformation. Under the current technical conditions, it is still difficult to carry out efficient monitoring and quantitative evaluation of surface subsidence. In recent years, multi-source remote sensing technologies such as Interferometric Synthetic Aperture Radar(InSAR), Unmanned Aerial Vehicle photogrammetry(UAV photogrammetry), and Light Detection and Ranging(LiDAR) have been developing rapidly, and with its features of non-contact observation, wide coverage, and high spatial and temporal resolution, it is able to realize the continuity, dynamics and comprehensive monitoring of surface subsidence. Through the fusion of multi-source observation data, it can provide a new technological way for the efficient monitoring of the mining subsidence in the western mining area. This paper summarizes the progress of the application of multi-source remote sensing technology in mining subsidence monitoring. The practical effects of lnSAR, UAV photogrammetry, and LiDAR for subsidence monitoring in mining areas on the Loess Plateau are explored through field experiments, and it is found that under the conditions of complex geomorphology, undulating topography, and vegetation cover, as well as large-gradient deformation of the ground surface, the lnSAR interferometric loss of correlation, atmospheric delays and other kinds of errors are too large. The 3D model constructed from UAV photogrammetry is affected by vegetation and terrain, resulting in insufficient elevation accuracy for the ground model. UAV laser scanning is affected by the combined effects of terrain slope, point cloud density, and horizontal movement of surface points leading to significant DEM modeling errors. As a result, multi-source remote sensing techniques under the current conditions all have their own advantages, limitations and technical bottlenecks. On this basis, the algorithmic process of ground point cloud extraction and surface 3D deformation information acquisition in the loess gully area is proposed; the technical path to realize accurate and efficient monitoring of mine subsidence 3D displacement based on the fusion of multi-source remote sensing data is pointed out; and the prospect of the application of constructing an intelligent system of multi-source remote sensing monitoring of mine subsidence is envisioned.