The fast high-efficiency inspection for mining subsidence of mine-area is a reliable way for forecasting accident and evaluating losing expense.In order to monitor mining subsidence of exploitation mine efficiently,we use LiDAR data and bring forward a novel hierarchical filtering method for points cloud classification.We layered the original point-cloud data according to height value,classified them into ground and non-ground parts by the analysis of connectivity.Then the adaptive least squares interpolation method was used to make an interpolation of the ground for achieving the digital elevation model (DEM) of mining area in different time and to estimate subsidence of mine-area.The results show that LiDAR datamation can be greatly reduced.In the mean time,the time spending for calculation,was shorten and computational complexity was simplified as well.Therefore,the method of subsidence estimation based on LiDAR points cloud can be great beneficial to monitoring environment of mine area.