A Reproducible Methodology for 3D Tree-Structure Mensuration and Risk-Oriented Decision Support: Integrating SfM–MVS, Field Referencing, and Rule-Based TRAQ/ALARP Logic

Abstract

This manuscript presents a transferable and reproducible methodology for quantitative 3D tree-structure mensuration and transparent, rule-based decision support for tree risk management. The workflow integrates (i) Structure-from-Motion/Multi-View Stereo (SfM–MVS) reconstruction from multi-view imagery, (ii) independent referencing to ensure metric scaling and a consistent local frame, and (iii) point cloud analytics to derive branch-level geometric descriptors (e.g., base diameter, length, inclination, slenderness, and projected reach). A clear rule-based layer operationalizes Tree Risk Assessment Qualification (TRAQ)-style risk components and As Low As Reasonably Practicable (ALARP) principles to map geometry and exposure into auditable management recommendations (e.g., monitoring intervals, pruning/weight reduction, supplemental support, and exclusion-zone planning). To provide a real-data example, the demonstration uses the public Fuji-SfM apple orchard dataset, including three neighboring trees with partially overlapping crowns for tree instance extraction and subsequent TRAQ/ALARP scenarios on an outer tree. The proposed decision layer is intentionally based on external geometry and exposure; internal decay indicators and species-specific mechanical properties (e.g., Modulus of Elasticity (MOE), Modulus of Rupture (MOR)) are outside this demonstration and should be incorporated via complementary diagnostics in operational deployments.

Plant phenotyping relevance

SfM–MVSと点群解析による樹木・枝の3D形状形質抽出が中心的な方法論であり、実データでの適用も含むため。

Code and data availability

The paper's analysis code (pipeline_PAPER.py, fuji_sfm_extract_trees.py) and implementation defaults are stated to be provided in the Supplementary Material, but no public repository or authors' URL is given in the supplied blocks, so the code asset requires contacting the authors. The Fuji-SfM apple orchard pointcloud

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