Individual tree TLS point clouds for tree volume estimation

Description

Dataset This dataset is based on terrestrial laser scanning (TLS) data acquired during winter 2020/2021 in leaf-off conditions, with a Leica BLK 360 instrument following a tree-centric scanning pattern. The data was acquired on two sites (47.42°N 8.49°E and 47.504°N, 7.78°E), both of which were managed mixed temperate forest stands. Individual trees were semi-automatically segmented from the co-registered TLS point clouds.

Background Accurate estimates of individual tree volume or biomass within forest inventories are essential for calibration and validation of biomass mapping products based on Earth observation data. Terrestrial laser scanning (TLS) enables detailed and non-destructive volume estimation of individual trees, with existing approaches ranging from simple geometrical features to virtual 3D reconstruction of entire trees. Validating such approaches with weight measurements is a key step before the integration of TLS or other close-range technologies into operational applications such as forest inventories. In this study, we firstly evaluate individual tree volume estimation approaches based on 3D reconstruction through quantitative structure models (QSM) against destructive reference data of 60 trees and compare them to operational allometric scaling models (ASM). Secondly, we determine the explanatory power of TLS-derived geometric parameters regarding total tree, stem, coarse wood and fine branch volume.