中文摘要：

机载LiDAR系统能够快速获取大面积地表高分辨率、高精度的三维点云数据，可用于矿区沉陷信息提取，但LiDAR数据本身的误差、地表覆被和数据处理等会导致生成DEM中存在一定的不确定性。基于研究区2009、2012年2期机载LiDAR点云数据，在LiDARDEM精度与不确定性分析的基础上，利用模糊推理方法建立了基于坡度、点云密度和地表粗糙度的误差相关表面，用于差值DEM不确定性的量化与DEM最小变化阈值的探测，采用基于权重滤波窗口的贝叶斯估计判定与修正，较精确地获取了研究区地表形变信息；针对地表侵蚀等导致的地形变化信息，在坡度相关性分析的基础上，通过掩膜去除了非开采沉陷导致的地形变化信息，获取了较为精确的沉陷盆地信息。实验表明该方法适用于大面积开采沉陷监测，能够快速确定沉陷区位置，较准确获取沉陷区的分布范围、面积及体积等信息，为开采沉陷监测提供了一种新的技术手段。

英文摘要：

Airborne LiDAR system can quickly obtain 3D point cloud data of large-scale surface with high-resolution, high-precision and can be used for extraction of mine subsidence data. But the error of LiDAR data, surface cover and data pro- cessing method will lead to the uncertainty of DEM. Based on the analysis of LiDAR DEM accuracy and uncertainty of the two airborne LiDAR point cloud data in 2009 and 2012 in the study area, an error-related surface based on slope, point cloud densi- ty and surface roughness was established by using fuzzy reasoning method. The surface can be used to detect the minimum change threshold of DEM and measure the uncertainty of DEM. With the Bayesian estimation determination and correction based on weight window,the surface deformation information in the study area was obtained. Based on the analysis of the slope correlation, the terrain change information caused by the non-mining subsidence was removed by the mask, and the more accu- rate subsidence basin information was extracted. Experiments show that this method is suitable for large area mining subsidence monitoring, which can quickly determine the location of subsidence area, obtain the information such as the distribution range, area and volume of subsidence area accurately, and provide a new technical means for mining subsidence monitoring.