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Retrieval of tree branch architecture attributes from terrestrial laser scan data using a Laplacian algorithm
Li, Yumei1; Su, Yanjun1,2; Zhao, Xiaoxia1; Yang, Mohan1; Hu, Tianyu1; Zhang, Jing1; Liu, Jin1; Liu, Min3; Guo, Qinghua1,2
2020
发表期刊AGRICULTURAL AND FOREST METEOROLOGY
ISSN0168-1923
卷号284
摘要Tree architecture, defined as the three-dimensional arrangement of tree above-ground elements, directly influences the biological and physical processes of vegetation such as photosynthesis and evapotranspiration. Accurate description of tree architecture is of central importance to understand the above biophysical processes. Terrestrial laser scanning (TLS) has been proved to be a promising tool to quantitatively describe tree architecture parameters. However, previous studies using TLS usually focused on architectural parameter measurements at individual tree, crown scale and leaf scales. Very few studies have achieved a comprehensive quantitative description of branch architecture (including angle, diameter, length and volume). In this study, we improved the Laplacian-Based Contraction skeletonization algorithm using the Dijkstra algorithm, developed a new path discrimination method to identify and encode branch orders, and retrieved branch architecture parameters based on branch order and topology information. To assess the influence of branching complexity and branching pattern on the estimation accuracy, we scanned 15 different sized magnolia trees without a leading stem and simulated 10 different sized trees with a leading stem. Results showed the overall branch order identification and parameters retrieval accuracy of trees with a leading stem was obviously higher than trees without a leading stem. The identification accuracy of branch order decreased with the increase in the number of branch and tree branching complexity. The estimated branch architecture parameters agreed well with ground truth measurements (R-2 up to 0.99), except for the second- and third-order branch volume. Compared with branch angle and diameter, branch length showed the best correlations with manually measured values (0.14 vs 0.002, 8.48 in RMSE; 0.99 vs 0.99, 0.78 in R-2). The second-and third-order branch volume estimations were highly underestimated compared with the ground truth values (R-2 = 0.53, RMSE = 0.0239 and R-2 = 0.70, RMSE = 0.0257 respectively). This study demonstrated that TLS was an effective way to retrieve branch architecture parameters and provided a useful tool for comprehensive studies of biophysical processes and metabolic theories in ecology.
关键词Trunk architecture Laplacian algorithm Dijkstra algorithm Terrestrial laser scan data Simulated data
学科领域Agronomy ; Forestry ; Meteorology & Atmospheric Sciences
DOI10.1016/j.agrformet.2019.107874
收录类别SCI
语种英语
WOS关键词LEAF-AREA INDEX ; GROUND-BASED LIDAR ; INDIVIDUAL TREES ; CANOPY-STRUCTURE ; BIOMASS ESTIMATION ; CROWN DEVELOPMENT ; STANDING TREES ; FOREST CANOPY ; TROPICAL TREE ; GAP FRACTION
WOS研究方向Agriculture ; Forestry ; Meteorology & Atmospheric Sciences
WOS记录号WOS:000525817500003
出版者ELSEVIER
文献子类Article
出版地AMSTERDAM
EISSN1873-2240
资助机构Frontier Science Key Programs of the Chinese Academy of Sciences [QYZDY-SSW-SMC011] ; National Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [41871332] ; CAS Pioneer Hundred Talents Program, China Postdoctoral Science Foundation [2019M650038]
作者邮箱ysu@ibcas.ac.cn
引用统计
被引频次:29[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ibcas.ac.cn/handle/2S10CLM1/21814
专题植被与环境变化国家重点实验室
作者单位1.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Univ Calif Merced, Sch Engn, Sierra Nevada Res Inst, Merced, CA 95343 USA
4.Natl Forestry & Grassland Adm, China Natl Forestry Econ & Dev Res Ctr, Beijing 100714, Peoples R China
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GB/T 7714
Li, Yumei,Su, Yanjun,Zhao, Xiaoxia,et al. Retrieval of tree branch architecture attributes from terrestrial laser scan data using a Laplacian algorithm[J]. AGRICULTURAL AND FOREST METEOROLOGY,2020,284.
APA Li, Yumei.,Su, Yanjun.,Zhao, Xiaoxia.,Yang, Mohan.,Hu, Tianyu.,...&Guo, Qinghua.(2020).Retrieval of tree branch architecture attributes from terrestrial laser scan data using a Laplacian algorithm.AGRICULTURAL AND FOREST METEOROLOGY,284.
MLA Li, Yumei,et al."Retrieval of tree branch architecture attributes from terrestrial laser scan data using a Laplacian algorithm".AGRICULTURAL AND FOREST METEOROLOGY 284(2020).
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