Examining the Role of UAV Lidar Data in Improving Tree Volume Calculation Accuracy

Traditional forest inventories are based on field surveys of established sample plots, which involve measurements individual trees within a plot and the selection proper allometric equations for tree volume calculation. Thus, accurate properly selected two crucial factors providing high-quality volumes. One key problem is difficulty in accurately acquiring height data, resulting high uncertainty calculation when diameter at breast (DBH) alone used. This study examined using different means impact models estimation accuracy. Masson pine eucalyptus plantations Fujian Province, China, were as examples; their heights measured three ways: an 18-m telescopic pole, UAV Lidar (unmanned aerial vehicle, light detection ranging) direct measurement felled trees, with latest one reference. The DBH-based DBH–height-based corresponding to specific species used calculations results show that (1) volumes calculated from lower than those models. On average, underestimated by 0.018 m3 0.117 eucalyptus, respectively, while relative root-mean-squared errors (RMSEr) 24.04% 33.90%, model; (2) extracted data was more because pole method generally height, especially taller length (18 m our study); (3) methods greatly impacted accuracies DBH–height model. telescopic-pole-measured resulted error 9.1–11.8% calculations. research implies incorporation DBH can effectively improve could be new direction collection future.