Adaptive Filtering of Aerial Laser Scanning Data

Filtering non-terrain points from raw laser scanning data is the most important goal to improve productivity in DTM generation. Filtering algorithms are built on assumptions about what discriminates terrain points from points on other objects (e.g. buildings and vegetation). In most cases, a single measure is used to accept or reject points. In this paper a three-stage raw data classification algorithm is presented. After a preliminary interpolation to a grid, a region growing based on height differences is applied. Segments from the region growing are classified as terrain, building or vegetation, based on their geometric and topological description. Terrain grid cells are conditionally low-pass filtered, to remove low vegetation. A piece-wise approximation of the terrain surface is computed, built from the grid cells classified as terrain. Finally, raw data are accepted as terrain within a given distance from the surface. Results obtained on a ISPRS filter test data set are shown to illustrate the effectiveness of the procedure. 1 Currently visiting professor at Delft University of Technology, Dept. of Earth Observation and Space Systems