Extracting digital terrain models in forestry using lidar data
Airborne light detection and ranging (LIDAR) is emerging as a tool to provide an accurate digital terrain model (DTM) of forest areas since it can even penetrate beneath the canopy. However, the determination of DTM in dense forest areas is still a difficult task and in an early stage of development. In this paper, an adaptive prediction technique based on the least mean squares (LMS) algorithm is presented. Results for LIDAR data, taken in 1999 at the Bellingham, WV site, are considered to illustrate the applicability of the presented technique.