Towards DTM generation from LIDAR data in hilly terrain using wavelets

LIght Detection And Ranging (LIDAR) for terrain and land surveying has contributed to many environmental, engineering and civil applications. However, the analysis of Digital Surface Models (DSMs) from complex LIDAR data is still challenging especially for highly sloped landscapes. Commonly, the first task to investigate LIDAR data point clouds is to separate ground and object points as a preparatory step for further object classification aiming at the generation of Digital Terrain Models (DTMs). In this paper, object and ground separation in hilly terrain from LIDAR point clouds is addressed by employing wavelets. The results show its potential for terrain feature extraction from LIDAR data as input for further classifiers.