Point-cloud segmentation of individual trees in complex natural forest scenes based on a trunk-growth method

Abstract

Forest resource management and ecological assessment have been recently supported by emerging technologies. Terrestrial laser scanning (TLS) is one that can be quickly and accurately used to obtain three-dimensional forest information, and create good representations of forest vertical structure. TLS data can be exploited for highly significant tasks, particularly the segmentation and information extraction for individual trees. However, the existing single-tree segmentation methods suffer from low segmentation accuracy and poor robustness, and hence do not lead to satisfactory results for natural forests in complex environments. In this paper, we propose a trunk-growth (TG) method for single-tree point-cloud segmentation, and apply this method to the natural forest scenes of Shangri-La City in Northwest Yunnan, China. First, the point normal vector and its Z-axis component are used as trunk-growth constraints. Then, the points surrounding the trunk are searched to account for regrowth. Finally, the nearest distributed branch and leaf points are used to complete the individual tree segmentation. The results show that the TG method can effectively segment individual trees with an average F-score of 0.96. The proposed method applies to many types of trees with various growth shapes, and can effectively identify shrubs and herbs in complex scenes of natural forests. The promising outcomes of the TG method demonstrate the key advantages of combining plant morphology theory and LiDAR technology for advancing and optimizing forestry systems.

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

“…In areas where vegetation was sparse, entire trees were successfully identified (Figure 6A), unlike in areas with dense vegetation (Figure 6B). Although similar CSP algorithms have successfully delineated trees with overlapping canopies in LiDAR point clouds [53,65,67], the crown conditions present on most of the seismic lines found in this study appear to have been too complex to be accurately separated by LiDAR 360's CSP-based tree detection algorithm. The algorithm was able to identify individual trees in the canopy (Figure 6C), albeit very rarely.…”

“…Specifically, multi-stemmed individual trees and shrubs were identified by the software during point cloud classification as multiple individual trees rather than as a single tree. Over-segmentation has been observed in highly clustered environments when DBSCAN methods are utilized [65], and this is supported by the adjusted ground count and density data (those that included all shrubs ≥ 1.3 m tall in the plots) still being significantly lower than the counts and densities produced from the point cloud. A single Alnus viridis shrub can have dozens of stems, and although they all originate from a single base,…”

“…The trunk growth (TG) algorithm segmentation method also takes branching patterns of canopies into consideration [65]. This method has four primary steps: trunk extraction, fragment merging, trunk growth, and localization of branch and leaf points.…”

Using InVEST to evaluate water yield services in Shangri-La, Northwestern Yunnan, China

“…The wet and dry seasons extend from June to October and November to May, respectively. Shangri-La City has a complex and diverse topography with the local climate characterized by high spatial variability ( Liu et al, 2021b ). Other climate characteristics of the region include a high atmospheric transparency, increased daytime solar radiation, and rapid increases in temperature, resulting in a large diurnal temperature range.…”

Tree Reconstruction using Topology Optimisation

“…The segmentation phase has many variants, which reflect the variety of features that may be used to separate trees. Trunk identification methods [2][3][4] look for near-vertical cylindrical shapes in the point cloud as the basis for locating the individual trees. Crown methods [5] look for conical or dome-shaped crowns within the point cloud.…”