An Adaptive Method for the Construction of Digital Terrain Model from Lidar Data

To generate a DTM, measurements from above-ground features such as buildings, vehicles, and vegetation have to be classified and removed, which is nontrivial. The above-ground features present great challenges in conjunction with varying slopes of the ground. In this paper, we present a method to remove above-ground LiDAR measurements and generate DTMs by using adaptive window size according to the local gradients. Iterative construction measurements are performed until difference between two iterations are minimum. In our experiments, we apply our method to the LiDAR data acquired from the downtown region of New Orleans. It was demonstrated that the adaptive window method can remove most of the above-ground points effectively.