Creation of digital terrain models using an adaptive lidar vegetation point removal process

Commercial small-footprint lidar remote sensing has become an established tool for the creation of digital terrain models (DTMs). Unfortunately, even after the application of lidar vegetation point removal algorithms, vertical DTM error is not uniform and varies according to land cover. This paper presents the results of the application of an adaptive lidar vegetation removal process to a raw lidar dataset of a small area in North Carolina. This process utilized an existing lidar vegetation point removal algorithm in which the parameters were adaptively adjusted based on a vegetation map. The vegetation map was derived through the exclusive use of the lidar dataset, making the process independent of ancillary data. The vertical error and surface form of the resulting DTM were then compared to DTMs created using traditional techniques. The results indicate that the adaptive method produces a superior DTM.