Abstract
Separating ground from nonground laser returns from airborne light detection and ranging (LiDAR) data is a key step in creating digital terrain models (DTMs). In this letter, bare-earth and forested surfaces are classified from LiDAR intensity data in a data set from central Idaho, U.S. Next, a Gaussian fitting (GF) method is applied to determine ground elevations from LiDAR elevation data according to the land-cover information. In comparison to ground-based reference data, the GF method generated an accurate DTM in this study area. Overall, the DTM underestimated the ground observations by approximately 31 cm. A combination of LiDAR intensity and elevation data may be effectively used to develop DTMs in similar terrain of relatively simple land-cover classes.
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