Tree Crown Width Estimation, Using Discrete Airborne LiDAR Data

Light detection and ranging (LiDAR) is a promising technology for extracting forest biophysical parameters, including tree height, total volume, biomass, etc. However, tree crown width estimation at the individual level is challenging due to overlapping crown surfaces in urban forests. The objective of this study, therefore, is to develop an approach for estimating tree crown width at the individual tree level using airborne LiDAR data in an urban area. To reach this objective, we constructed a general geometric model for each tree, centering at the tree position on the ground to fit the LiDAR-derived crown surface and then predicted crown width using tree height and shape-related parameters as independent variables and the ground measurement of all the crown widths identified by LiDAR data as dependent variables. Analyses of results suggest that tree crown widths in a mixed forest can be successfully extracted through model-based linear regression analysis, which can explain 88.5 % of variance as...