4.5 Article

Quantifying branch architecture of tropical trees using terrestrial LiDAR and 3D modelling

期刊

TREES-STRUCTURE AND FUNCTION
卷 32, 期 5, 页码 1219-1231

出版社

SPRINGER HEIDELBERG
DOI: 10.1007/s00468-018-1704-1

关键词

Terrestrial LiDAR; Tree architecture; Quantitative structure models; Destructive harvesting; Tree metrics

类别

资金

  1. Norwegian Agency for Development Cooperation (Norad)
  2. Australian Department of Foreign Affairs and Trade (DFAT)
  3. European Union (EU)
  4. International Climate Initiative (IKI) of the German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety (BMUB)
  5. CGIAR Research Program on Forests, Trees and Agroforestry (CRP-FTA)
  6. ERA-GAS NWO-3DforMod project [5160957540]
  7. ERC Advanced Investigator Award (GEM-TRAITS) [321131]
  8. NERC [NE/P012337/1]
  9. NERC [NE/P012337/1, NE/J023418/1] Funding Source: UKRI

向作者/读者索取更多资源

Key message A method using terrestrial laser scanning and 3D quantitative structure models opens up new possibilities to reconstruct tree architecture from tropical rainforest trees. Tree architecture is the three-dimensional arrangement of above ground parts of a tree. Ecologists hypothesize that the topology of tree branches represents optimized adaptations to tree's environment. Thus, an accurate description of tree architecture leads to a better understanding of how form is driven by function. Terrestrial laser scanning (TLS) has demonstrated its potential to characterize woody tree structure. However, most current TLS methods do not describe tree architecture. Here, we examined nine trees from a Guyanese tropical rainforest to evaluate the utility of TLS for measuring tree architecture. First, we scanned the trees and extracted individual tree point clouds. TreeQSM was used to reconstruct woody structure through 3D quantitative structure models (QSMs). From these QSMs, we calculated: (1) length and diameter of branches > 10 cm diameter, (2) branching order and (3) tree volume. To validate our method, we destructively harvested the trees and manually measured all branches over 10 cm (279). TreeQSM found and reconstructed 95% of the branches thicker than 30 cm. Comparing field and QSM data, QSM overestimated branch lengths thicker than 50 cm by 1% and underestimated diameter of branches between 20 and 60 cm by 8%. TreeQSM assigned the correct branching order in 99% of all cases and reconstructed 87% of branch lengths and 97% of tree volume. Although these results are based on nine trees, they validate a method that is an important step forward towards using tree architectural traits based on TLS and open up new possibilities to use QSMs for tree architecture.

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