Vegetation and slope effects on accuracy of a LiDAR-derived DEM in the sagebrush steppe

Abstract

This study analysed the errors associated with vegetation cover type and slope in a Light Detection and Ranging (LiDAR) derived digital elevation model (DEM) in a semiarid environment in southwest Idaho, USA. Reference data were collected over a range of vegetation cover types and slopes. Reference data were compared to bare-ground raster values and root mean square error (RMSE) and mean signed error (MSE) were used to quantify errors. Results indicate that vegetation cover type and slope have statistically significant effects on the accuracy of a LiDAR-derived bare-earth DEM. RMSE and MSE ranged from 0.072 to 0.220 m and from −0.154 to 0.017 m, respectively, with the largest errors associated with herbaceous cover and steep slopes. The lowest errors were associated with low sagebrush and low-slope environments. Although the RMSEs in this study were lower than those reported by others, further refinement of the accuracy of LiDAR systems may be needed for fine-scale vegetation and terrain applications in rangeland environments.