Filtering is a key way to classify ground and non-ground points from LiDAR data. Current LiDAR filtering methods, implemented mostly through single LiDAR point cloud only, lack real data source references, subsequently there may be many errors. In view of this situation, this paper presents a new approach based on topographic change detection for airborne LiDAR filtering. In this method, LiDAR point cloud data are accurately registered with existing DEM data and harmonization to the same coordinate system. Then, we implement grid-based organization of LiDAR point cloud data to make corresponding regions of LiDAR point cloud data and existing DEM data correspond to each other. Finally, we filter LiDAR data based on topographic change detection. In order to verify the algorithm, two types of data with different terrain characteristics-urban and mountain were tested. The experimental results indicate that the approach put forward in this paper is effective in filtering out non-ground points from both urban and mountainous areas, while retaining topographic details.