Location: Watershed Management ResearchTitle: Errors in LiDAR-derived shrub height and crown area on sloped terrain) Author
Submitted to: Journal of Arid Environments
Publication Type: Peer reviewed journal
Publication Acceptance Date: 11/23/2010
Publication Date: 12/22/2010
Citation: Glenn, N.F., Spaete, L.P., Sankey, T.T., Derryberry, D.R., Hardegree, S.P., Mitchell, J.J. 2010. Errors in LiDAR-derived shrub height and crown area on sloped terrain. Journal of Arid Environments. 75(4):377-382. Interpretive Summary: LiDAR is a remote sensing tool most frequently used to measure ground topography, but is also very useful in measuring the 3-dimensional structure of vegetation. The latter application has mostly been directed toward characterization of forest plant communities. LiDAR detection of lower-stature plant communities is more difficult, but is improving with newer, higher resolution instrumentation. In this study, LiDAR was used to characterize the size and shape of individual sagebrush plants to evaluate alternative data-processing protocols, and to determine the magnitude of height- and shape-detection errors cause by steep topography. In general, both height and crown area of sagebrush were underestimated by LiDAR, but these errors can be expected to be reduced by increasing laser point densities. Slope had little effect on the magnitude of vegetation measurement errors. Improved LiDAR technology will greatly enhance our ability to understand and characterize these extensive semi-arid plant communities.
Technical Abstract: This study developed and tested four methodologies for determining shrub height measurements with LiDAR data in a semiarid shrub-steppe in southwestern Idaho, USA. Unique to this study was the focus of sagebrush height measurements on sloped terrain. The study also developed one of the first methods towards estimating crown area of sagebrush from LiDAR. Both sagebrush height and crown area were underestimated by LiDAR. Sagebrush height was estimated to within +/- 0.26 – 0.30 m (two standard deviations of standard error). Crown area was underestimated by a mean of 49%. Further, slope had a relatively low impact on sagebrush height and crown area estimation. From a management perspective, estimation of individual shrubs over large geographic areas can be accomplished using a 0.5 m rasterized vegetation height derivative from LiDAR. While the underestimation of crown area is not compelling, we suggest that this underestimation would improve with higher LiDAR point density (>4 points/m2). Further studies are warranted for development of biomass estimates from LiDAR height and crown area derivatives.