Individual Tree Structural Parameter Extraction and Volume Table Creation Based on Near-Field LiDAR Data: A Case Study in a Subtropical Planted Forest

Abstract

Individual tree structural parameters are vital for precision silviculture in planted forests. This study used near-field LiDAR (light detection and ranging) data (i.e., unmanned aerial vehicle laser scanning (ULS) and ground backpack laser scanning (BLS)) to extract individual tree structural parameters and fit volume models in subtropical planted forests in southeastern China. To do this, firstly, the tree height was acquired from ULS data and the diameter at breast height (DBH) was acquired from BLS data by using individual tree segmentation algorithms. Secondly, point clouds of the complete forest canopy were obtained through the combination of ULS and BLS data. Finally, five tree taper models were fitted using the LiDAR-extracted structural parameters of each tree, and then the optimal taper model was selected. Moreover, standard volume models were used to calculate the stand volume; then, standing timber volume tables were created for dawn redwood and poplar. The extraction of individual tree structural parameters exhibited good performance. The volume model had a good performance in calculating the standing volume for dawn redwood and poplar. Our results demonstrate that near-field LiDAR has a strong capability of extracting tree structural parameters and creating volume tables for subtropical planted forests.

Assessing the Potential of Onboard LiDAR-Based Application to Detect the Quality of Tree Stems in Cut-to-Length (CTL) Harvesting Operations

“…Kukko et al [20] employed MLS and GNSS/INS technologies, using graph optimization to refine data trajectories, thus efficiently mapping forests, and determining tree parameters. Gao et al [21] leveraged near-field LiDAR data from UAV and ground backpack scanners to determine the structural parameters of trees in subtropical planted forests. The findings affirm near-field LiDAR's effectiveness in extracting tree structural details.…”

UAV Photogrammetry for Estimating Stand Parameters of an Old Japanese Larch Plantation Using Different Filtering Methods at Two Flight Altitudes

“…Jayathunga et al [ 55 ] estimated the standard deviation of height, percentile height, coefficient of variation in height, skewness, and kurtosis, and canopy cover above mean height using Fixed-Wing UAV. Gao et al [ 56 ] combined UAV laser scanning and ground backpack laser sacking to extract individual tree structural parameters and fit volume models in subtropical planted forests in southeastern China.…”

Use of Mobile Laser Scanning (MLS) to Monitor Vegetation Recovery on Linear Disturbances

“…The complex nature of natural stands makes single tree detection in point clouds challenging; utilizing a simpler canopy detection method that does not explicitly attempt to distinguish overlapping canopies may be an alternative solution for tree segmentation in these types of environments. An example of such a method that has been successful in mature mixedwood forests is the distance judgment clustering approach [68,69]. This method assumes that the distance between trees is greater at their apex compared to the ground and uses those distances to cluster and segment trees.…”

“…One of the benefits of MLS relative to RPAS LiDAR is the increased point cloud density in the lower canopy which facilitates DBH measurements [39,69]. A number of studies have observed acceptable ranges of DBH accuracy when sampling trees in both planted and natural stands; however, the general consensus is that accuracy is highest for trees with DBHs between 10 and 20 cm [40,66,73].…”