Work

Integrating terrestrial and canopy laser scanning for comprehensive analysis of large old trees: Implications for single tree and biodiversity research

Year: 2025

Type: article

Abstract: Large old trees provide multiple ecosystem services and contribute disproportionately to forest biomass and biodiversity. Yet their canopies remain among the least‐explored terrestrial habitats, despite their structural influence on key ecological processes such as light interception, moisture regulation, carbon storage and habitat formation. While terrestrial laser scanning (TLS) captures tree structure primarily from the ground, it struggles with occlusion and reduced precision in dense upper canopies, limiting information on fine‐scale branches and canopy vegetation. To address this, we introduce canopy laser scanning (CLS). We lifted a high‐end laser scanner into the canopy of six large, old trees by using scaffolding or climbers. Four trees are in diverse tropical rainforests in Colombia, Brazil and Peru and have large complex crowns with dense foliage. Two ‘giant’ trees stand out in Tasmania's wet, temperate eucalypt forests. Combining canopy and terrestrial scans resulted in a consistent high point cloud quality. The combined point clouds exhibited uniform point densities throughout the entire tree (downsampled to 1 cm), enabling a thorough examination of both the tree structure and its associated vegetation. Quantitative Structure Models (QSMs) showed, on average, a 20% increase (compared to TLS) in estimated branch volume and length, particularly concentrated in the upper crown region. We identified key epiphytic groups for a 5 × 5 × 5 m 3 subset of a tree. Our results show that CLS improves point cloud precision and reduces occlusion, enabling more accurate assessments of tree architecture and canopy biodiversity. Where feasible, this advancement creates new opportunities for 3D modelling of microhabitats, estimating aboveground carbon stocks, monitoring species and studying ecological dynamics.

Source: Remote Sensing in Ecology and Conservation

DOI: 10.1002/rse2.70021