Title :
Extracting digital terrain models in forestry using lidar data
Author :
Younan, N.H. ; Lee, H.S. ; Evans, D.L. ; Eggleston, N.T.
Author_Institution :
Dept. of Electr. & Comput. Eng., Mississippi State Univ., MS, USA
Abstract :
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
Keywords :
geodesy; geophysical techniques; optical radar; remote sensing by laser beam; terrain mapping; topography (Earth); Bellingham; DTM; USA; United States; West Virginia; adaptive prediction; airborne method; algorithm; dense forest; digital terrain model; forest area; forested area; geodesy; geophysical measurement technique; land surface topography; laser remote sensing; lidar; terrain mapping; vegetation; Adaptive filters; Data mining; Digital elevation models; Forestry; Laser modes; Laser radar; Least squares approximation; Nonlinear filters; Predictive models; Vegetation mapping;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-7031-7
DOI :
10.1109/IGARSS.2001.977906
