Automated First-Order Tree Branch Modeling at Plot- and Individual-Tree-Levels From Close-Range Sensing for Silviculture and Forest Ecology

First-order branches, which are directly attached to the stem, form the primary structure of an individual tree. They play a crucial role in determining the tree’s photosynthetic efficiency and reproduction capabilities. Until recently, to nondestructively retrieve first-order branches remains a great challenge. Terrestrial laser scanning (TLS) has gained prominence in forest inventories, achieving promising estimations of fundamental metrics. These successes indicate that TLS could be a promising tool to acquire individual tree branch information. Previous studies on branch modeling have predominantly focused on the tree-level or simulation data, with limited occlusion effects. This study addresses the gap between the practical need and current research by developing an automated algorithm to retrieve the first-order branches from the plot-level TLS data and demonstrating the applicability and potential of TLS data in silviculture and ecology applications. The method was tested on 416 trees across six plots, categorized into three complexity levels. The experiment results indicated a varying accuracy of the branch detection and length estimation across different plot complexity levels. Specifically, plot 1 exhibited the highest branch detection accuracy, i.e., 71.42% recall and 73.15% precision, and the highest accuracy of branch length estimation was observed in plots 2 and 3, i.e., approximately 52.90 cm in root-mean-square error (RMSE) and 63.96% in RMSE%. The accuracy of branch detection generally decreased with increased plot complexity, as the average
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-scores of “easy,” “medium,” and “difficult” plots are 64.73%, 63.29%, and 48.63%, respectively. Notably, the proposed method works for the first-order branch modeling at both plot- and individual-tree-levels, though the experiment is primarily based on the plot-level data. This study demonstrates the capability of close-range point clouds in the retrieval of branch structures and underscores its potential in comprehensive forest structure analyses.