SOURCE-LINKED INTELLIGENCE

The Role of Radiometric Features in Cross-Site Leaf-Wood Segmentation of LiDAR Point Clouds

arXiv · AI, language, vision and robotics · article · Sep 18, 2026 · UTC

Leaf-wood segmentation of individual trees from LiDAR point clouds is essential for quantitative structure models (QSMs) used in non-destructive biomass estimation. Existing segmentation methods typically exclude radiometric features (e.g., intensity, return number) to maximize cross-sensor compatibility. We challenge this design choice by evaluating cross-site and cross-platform generalization: training on the public Heidelberg dataset (terrestrial TLS, 1550nm) and testing on a novel dataset from Ontario, Canada (RPA-LS, 905nm). Results show that geometry-only methods - including state-of-the

Read original source ↗ Open in workspace

recordType

paper

region

Global