Estimation of tree crown volume from airborne lidar data using computational geometry

Although simple geometrical shapes are commonly used to describe tree crowns, computational geometry enables calculation of the individual crown properties directly from airborne lidar point clouds. Our objective was to calculate crown volumes (CVs) using this technique and validate the results by comparing them with field-measured values and modelled ellipsoidal crowns. The CVs of standing trees were obtained by measuring the crown radii at different heights, integrating the obtained crown profiles as solids of revolution, and finally averaging the volumes obtained from the four separate profiles. With the lidar data, the CVs were extracted using 3D alpha shape and 3D convex hull techniques. Crown base heights (CBHs) were also estimated from the lidar data and used to exclude echoes from the understory, which was also done using field-based CBHs to exclude this error source. The results show that the field-measured CVs had a high correlation with lidar-based estimates (best R 2 = 0.83), but the lidar-based estimates were generally smaller than the field values. The best correspondence (root mean square difference (RMSD) = 45.0%, average difference = –24.7%) was obtained using the convex hull of the point data and field-measured CBH. The CBHs were consistently overestimated (RMSD = 37.3%; average difference = –20.0%), especially in spruces with long crowns. Thus using lidar-based CBH also increased the inaccuracy of the CV estimates. While the underestimation of CV is mainly explained by the inadequate number of echoes from the lower regions of the crowns, the CVs obtained from the lidar were better than those obtained with ellipsoids fitted by using general models for crown dimensions. The utility of the estimated CVs in the prediction of stem diameter is also demonstrated.