A novel geometric feature-based wood-leaf separation method for large and crown-heavy tropical trees using handheld laser scanning point cloud

ABSTRACT

As the prerequisite of non-destructively measuring structural parameters and leaf distribution, wood-leaf separation plays an essential role in forest inventories. However, fewer studies focus on the separation and measurement of large tropical trees with heavy crowns and complex branch structures. This study proposed a novel method to automatically separate the leaf and wood points of large tropical trees based on geometric features. Instead of identifying all wood points using the same rules, we used different methods to separate small and large wood components, respectively. The identification of small wood components was implemented mainly by the differences in point density and linear distribution pattern between leaf and wood points, while the identification of large wood components was implemented through the comprehensive analysis of verticality, linearity, anisotropy, as well as point density. To improve the separation accuracy and implementation effectiveness, the segment-wise and point-wise methods were combined in this study. The robustness and generalization of the proposed method were tested using two datasets, i.e. twenty large tropical trees with heavy crowns and twenty-four general tropical trees without heavy crowns. The separation results verified that the proposed method could achieve good separation of wood and leaf points of large crown-heavy tropical trees with the accuracy of up to 91.5%. The highest separation accuracy of general tropical trees was about 95.03%. The examination of the tropical trees without heavy crowns demonstrated that the proposed method has promising robustness and generalization ability. In addition, to fill the gap in the large tropical tree point clouds, an open-source dataset library was built for the wood-leaf separation research, including manually labelled 20 large crown-heavy tropical trees with different types of branch structures and basic structural parameters of each tree (tree height, crown spread, and diameter at the breast height (DBH)).

KEYWORDS:

• wood-leaf separation
• large and crown-heavy tropical trees
• complex branch structure
• handheld laser scanning

Highlights

• Extract wood points of varied size wood components using different methods.

• Achieve leaf-wood separation of large tropical trees with accuracy up to 91.5%.

• Analysis of influence of tree shape, crown size, branch structures.

• Dataset library of large and crown tropical trees.

Acknowledgements

This work was supported by the Research Institute of Land and Space (project: 1-CD81) and the PhD fellowship from the Hong Kong Polytechnic University. M.S. Wong thanks the funding support from the General Research Fund (Grant No. 15603920 and 15609421), and the Collaborative Research Fund (Grant No. C5062-21GF) from the Research Grants Council, Hong Kong, China. The authors sincerely thank the editors and reviewers for their constructive comments and suggestions.

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data Availability statement

The HLS dataset used in this paper is openly available on the web:https://www.dropbox.com/scl/fo/bshwkkd0tfv4tlp4u7vcx/h?dl=0&rlkey=de4q6d598xfcg5r2v2ln4gnp5.

Additional information

Funding

The work was supported by the Research Institute of Land and Space [1-CD81]; General Research Fund [15603920,15609421]; Research Grants Council, University Grants Committee [C5062-21GF].