Airborne light laser detection and ranging (LiDAR) can obtain three-dimensional point cloud data with high accuracy, can reach the ground surface through forest leaves, and reflect the continuous terrain features of the study area quickly and accurately, which is conducive to the establishment of a high-resolution digital elevation model (DEM). In this paper, cloth simulation filtering (CSF) algorithm is applied to filter the airborne LiDAR data. By setting the number of particles generated in the algorithm and the threshold of ground point classification, the ground point cloud is extracted from six groups of point cloud data under different terrain conditions, and the Kappa coefficient of classification is between 0.851 and 0.954. The DEM of 1 m×1 m is generated from the ground points extracted by the CSF algorithm, and the DEM provided by the research area is linearly fitted. Experimental results show that the regression line fitting goodness factor R² is larger than 0.99 and the root mean square error is between 0.10451 and 0.30387. The cloth simulation algorithm has few parameters for extracting ground points of the point cloud and is suitable for a wide range of terrain. The high-resolution DEM generated by the proposed algorithm can well express the continuous undulating surface changes and terrain features of the region.