Treegraph: tree architecture from terrestrial laser scanning point clouds.
Name
Remote_Sens_Ecol_Conserv_-_2024_-_Yang_-_Treegraph__tree_architecture_from_terrestrial_laser_scanning_point_clouds.pdf
Description
visibility:open
Size
4.3 MB
Format
Adobe PDF
Checksum (CRC64NVME)
IYu1VI2t53o=
Resource type
Journal article
Date published
June 3, 2024
Abstract
Accurate quantification of tree architecture is critical to interpreting the growth, health and functioning of trees and forests. Terrestrial laser scanning (TLS) offers millimetre‐level point cloud data, but current approaches to 3D tree reconstruction from TLS point clouds primarily focus on retrieving total volume at tree scale for aboveground biomass (AGB) estimation. Few methods have been designed specifically to provide tree architectural properties, including branch‐level morphology and topology, rather than AGB; derived topological traits have tended to be a compromise, and of secondary importance to volume. We present , a new approach explicitly designed to retrieve the architectural traits of trees at multiple scales, from the whole tree scale down to individual branches and internodes, using TLS data with limited assumptions about tree form. It provides morphological traits such as branch length and diameter, alongside topological traits including parent–daughter connections of branches and internodes, furcation (branching) number and branch order. We compare ‐derived morphological and topological traits with manual measurements of branches from eight destructively harvested trees, yielding RMSE values of 0.60 m (5.96%) for branch length, 2.99 cm (33.45%) for branch diameter, 0.46 (19.38%) for furcation number and 0.08 m (33.16%) for internode length, respectively. In a broader application to 603 trees from tropical, temperate and urban forests, we demonstrate that the derived morphological and topological traits support testing of structure‐related metabolic scaling theories. Testing branches over 10 cm in diameter across 18 657 branching nodes shows that ‐derived branch‐level scaling exponents deviate from WBE predictions, exhibiting area‐preserving behaviour while displaying asymmetry in length and diameter of daughter branches. Available as open‐source Python software, provides fine‐level branching network information, promoting improved insights into tree structure and function. This data‐driven approach reduces the need for empirical heuristic parameters, which has the potential for advancing large‐scale ecological studies on tree architecture.
Funder
| Funder name | Awards |
European Research Council, European Union | Grant no. 757526. Tropical Forest Degradation Experiment (FODEX) |
European Metrology Programme for Innovation and Research, European Union | Grant no. ENV55. Metrology for Earth Observation and Climate Project (MetEOC-2) |
National Centre for Earth Observation, United Kingdom | NE/P011780/1 |
Natural Environment Research Council, United Kingdom | NE/N00373X/1 |
University College London, United Kingdom | 0000 0001 2190 1201 |
Journal title
Remote Sensing in Ecology and Conservation
Article number
rse2.399
Publisher
John Wiley & Sons Ltd. on behalf of Zoological Society of London
Place of publication
UK
ISSN
2056-3485
eISSN
2056-3485
Official URL
Rights statement
In Copyright
Additional information
IF = 5.787 (2023-2024)