Practice of airborne LiDAR point cloud filtering method based on triangulated irregular network

Abstract

Airborne LiDAR (light detection and ranging) technology as the representative of active remote sensing methods, can rapid generate Digital Elevation Model (DEM) productions with high accuracy. Airborne LiDAR point cloud data filtering is the key to obtain high precision DEM. In this paper, the Triangulated Irregular Network (TIN) method is proposed for filtering LiDAR point cloud data. Firstly, organizing data by regular square grid and triangulated irregular network, then select the seeds ground points to initial sparse triangular, and densified upward and ground points are extracted in an interactive process. Finally, in experiments it is shown that the filter method can effectively remove different sizes of buildings, high vegetation and other objects, and keep topographical features better.