Airborne lidar provides an effective platform for collecting elevation data. However, the accuracy of lidar-derived digital elevation models (DEMs) can be adversely affected by natural conditions as well as methods used to process the data. Using a lidar dataset from a mountainous region of southwest Idaho, this study extends previous assessments of DEM accuracy with a focused investigation of a specific dense, low-height shrub species (Ceanothus velutinus). Bare-earth elevations were collected using survey-grade GPS and compared to lidarderived elevations to assess DEM accuracy. Results suggest that the magnitude of elevation error varied depending on morphological characteristics of ceanothus, terrain slope, and filtering parameters used to process the lidar data. When using optimal filtering parameters, root mean square error (RMSEZ) was largest in areas of ceanothus cover, ranging from 0.17 to 0.26 m in slopes <25° and 0.28 to 0.37 m in slopes ≥25°. An examination of lidar returns found that ceanothus obstructed laser pulse penetration and few returns reached the ground surface. In areas of ceanothus cover, we conclude that the obstruction of the ground surface contributed to filtering errors, which resulted in mislabeled ground returns and decreased accuracy in bare-earth DEMs. These results have implications for the use of lidar-derived DEMs in areas of ceanothus throughout western North America, and in ecosystems with similar dense shrub cover.
ASJC Scopus subject areas
- Computers in Earth Sciences