Tree selection system for light-receiving logging using 3d tree measurement and sunlight simulation

Forests have multifaceted functions that are indispensable to people’s lives, such as preventing landslides and global warming. The existence of understory vegetation growing near the ground surface is considered important for maintaining these functions. In Japanese forestry, light-receiving logging is used to create a sunlight environment suitable for the growth of forest vegetation. However, the selection of trees to be cut off is left to the discretion of field workers, and there is concern about the loss of natural resources and forest functions due to incorrect selection decisions. Therefore, there is a need for a system that can quantitatively evaluate changes in the sunlight environment in the forest due to logging in advance. In this study, we propose a tree selection system based on shade simulation using a tree model for appropriate light-receiving logging. The proposed system converts tree data measured by LiDAR into a three-dimensional (3D) model, reproduces tree shadows by sunlight simulation using the 3D model, and proposes a tree selection algorithm for light-receiving logging based on the results of the simulation. Experiments in a real forest environment verified the performance of the proposed system through quantitative evaluation and confirmed that the proposed system was effective for tree selection to improve the sunlight environment in forests.