HR: 09:00h
AN: B41E-04    [Abstracts]
TI: Ground-return Identification of Airborne LiDAR Data in a Forested Area Using Gaussian-fitting Models
AU: * Wang, C
EM: wangchen@isu.edu
AF: Idaho State University - Boise Center Aerospace Laboratory, 322 E Front Street Suite 240, Boise, ID 83702,
AU: Glenn, N
EM: glennanc@isu.edu
AF: Idaho State University - Boise Center Aerospace Laboratory, 322 E Front Street Suite 240, Boise, ID 83702,
AU: Streutker, D
EM: stredavi@isu.edu
AF: Idaho State University - Boise Center Aerospace Laboratory, 322 E Front Street Suite 240, Boise, ID 83702,
AB: Separating ground returns from non-ground returns is a key step for LiDAR-derived Digital Terrain Model (DTM) construction in many forest LiDAR-applications. Many algorithms are designed to identify ground returns in LiDAR data by using filters to identify the LiDAR return with the local lowest elevation. However, these methods are not always reasonable for creating an accurate DTM because of: (1) the Gaussian distribution of ground-reflected LiDAR elevations, even in an ideal flat area, caused by the noise of LiDAR instrument; and (2) the ground-slope and roughness influence on LiDAR data, especially in mountainous areas. Theoretically these conditions will lead to error or underestimation of the ground elevation (and DTM). A statistical method for determining ground elevations based on Gaussian-fitting models is developed in this research. The whole study area (1km by 1km) is divided into 200 by 200 small windows (or samples) and each of samples covers 5m by 5m area. For each sample, all LiDAR elevations within it are computed to form a single or bimodal Gaussian distribution depending on the ground-cover class (bare earth or forested surface, respectively). The ground cover classification is achieved by a supervised classification of the LiDAR intensity data. The ground elevation for each sample is assigned a value based on the mean of the ground-represented Gaussian distribution. More than 100 field observations will be sampled in Fall 2007 for an accuracy assessment. The field observations will compare field- measured ground elevations with LiDAR-derived elevations.
DE: 0480 Remote sensing
DE: 0497 Wetlands (1890)
SC: Biogeosciences [B]
MN: 2007 Fall Meeting