Estimating Crown–Stem Allometry from Segmented Handheld SLAM LiDAR: Sensitivity to the Treatment of Disconnected Components

Individual-tree segmentation of dense point clouds increasingly supplies the crown dimensions from which crown–stem allometry is fitted, yet no study has measured how much the fitted crown–stem exponent changes with what is done to material a segment holds but may not own. In two 1 ha plots spanning the open-to-closed canopy gradient of a Southeast Asian tropical dry forest, scanned with handheld SLAM LiDAR against a field stem map of 1320 trees, we voxelized each of 340 segments at 5 cm, split it into 26-connected components and computed crown projected area three times with identical code: on the delivered segment, after removing every component not physically continuous with the tree’s own bole (strict) and after removing only those components in which a field-mapped stem other than this tree falls inside the component’s own footprint (conservative). In the closed evergreen stand the strict treatment moved the exponent of crown area on stem diameter from 1.54 to 1.04 (paired-bootstrap difference −0.49, 95% CI −0.65 to −0.34). The conservative treatment moved it by −0.003 (−0.005 to −0.001), and its median removal was 0.000 of a segment’s points in both stands. Removal based on stem-footprint overlap therefore moves the exponent by two orders of magnitude less than removal of every disconnected component, a contrast that bounds the sensitivity without establishing the ownership of either group. The result holds with the crown base fixed at its delivered value, with the largest segments removed and on the segments whose crown base came from the primary detection rule (−0.372, −0.587 to −0.147). Its direction also holds across bole gates, crown-base thresholds, an alpha-shape crown area and connectivity voxels of 3 to 10 cm, although its magnitude scales with the voxel (−0.89 to −0.24). The crown–stem exponent obtained from segmented closed-canopy point clouds is therefore not determined by the point cloud alone, and we quantify how much of it the analyst decides.