Spatial occupancy index of tree crown: Can provide new perspectives for quantifying structural complexity of individual tree crowns
Date:2026-06-10 clicks:
Impact Factor:11.4
DOI number:10.1016/j.rse.2026.115277
Affiliation of Author(s):东北林业大学
Journal:Remote Sensing of Environment (Q1)
Place of Publication:荷兰（阿姆斯特丹）
Key Words:LiDAR; Crown volume; Structural complexity of the tree crown; Ecological niche; Tree competition
Abstract:The structural complexity of tree crown describes the intricate arrangement and occupancy of leaves and thin branches in the canopy, which is crucial to shaping the stability of forest ecosystem. Numerous studies have provided sufficient theoretical basis and effective quantitative indexes for structural complexity, there are still some bottlenecks, such as: ecological niche occupancy and tree competitiveness have not yet been incorporated into the evaluation system for forest structural complexity; and the in-depth analysis of structural complexity at the individual scale has been ignored. In view of the above limitations, this study proposed a novel synergistic index, namely, the spatial occupancy index of tree crown (SOI) and taken the unmanned aerial vehicle laser scanning (ULS) and terrestrial laser scanning (TLS) data of 14 plots of typical natural secondary forests and plantation (including six dominant tree species: Korean larch, Korean pine, Birch, Manchurian ash, Mongolian oak, and the plantation of Korean pine) as examples. Firstly, an optimized algorithm (i.e., 3D alpha shape-voxelization (3D-ASV)) was proposed to efficiently calculate the crown volume; Secondly, a coupling index based on crown volume was proposed to efficiently quantify the structural complexity and ecological niche of tree crowns. The results indicated that the 3D-ASV algorithm provides an obvious advantage in estimating tree crown volume, with the highest correlation with AGB (r = 0.63). Crucially, SOI is a comprehensive and effective index for quantifying structural complexity of tree crown, that is, SOI is not only highly positive correlation with canopy entropy, canopy cover, canopy top rugosity, fractal dimension (i.e., 0.72 vs. 0.52 vs. 0.57 vs. 0.40), but also compensates for their limitations in explaining tree competitiveness. We believe that SOI will complement the lack of structural complexity at the individual scale, and has the potential to become an ecological analysis and detection tool of forest structure, which will enable us to deepen our understanding of the theory of ‘structure determines function’ of ecosystems, and further promote the incorporation of ecological theories into forest management.
Co-author:Zhen Zhen,Zengrui Zhang,Xuebing Guan,Jiayao Wang
First Author:Yuting Zhao
Indexed by:Journal paper
Correspondence Author:Yinghui Zhao*
Document Code:115277
Discipline:Engineering
Document Type:J
Volume:335
Page Number:115277
ISSN No.:0034-4257（印刷版）/ 1879-0704（电子版）
Translation or Not:no
Date of Publication:2026-01-01
Included Journals:SCI
Links to published journals:https://www.sciencedirect.com/journal/remote-sensing-of-environment