Exploring Stand Parameters Using Terrestrial Laser Scanning in Pinus tabuliformis Plantation Forests

The rapid and precise acquisition of forest stand parameters is a key challenge in forest resource assessment. Terrestrial laser scanning (TLS) provides a fast and accurate method, but its accuracy is influenced by factors like tree segmentation parameters. This study focuses on Pinus tabuliformis plantations in the Caijiachuan watershed, Jixian, Shanxi, on the Loess Plateau. Based on field survey data, including tree number, height (H), diameter at breast height (DBH), and biomass, high-precision point cloud data were acquired using TLS. A comparative shortest path (CSP) algorithm was used for individual tree segmentation to investigate the effect of parameter selection on measurement accuracy. The results show that minimum tree height has a significant impact on segmentation accuracy. As the minimum tree height increased from 3.0 to 5.5 m, the recall rate (R) decreased while the precision (P) increased. The highest precision (F-score = 0.9470) and biomass estimation accuracy (0.9066) were obtained with a minimum tree height of 4.5 m, and the best extraction accuracies for H and DBH (0.9677 and 0.9518) were obtained at 5.0 m. Optimizing the minimum tree height parameter improves segmentation accuracy, thereby enhancing the use of TLS for soil and water conservation on the Loess Plateau.