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Article

Influencing Factors in Estimation of Leaf Angle Distribution of an Individual Tree from Terrestrial Laser Scanning Data

1
State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
2
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
3
Key Laboratory for Silviculture and Conservation of Ministry of Education, Beijing Forestry University, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2021, 13(6), 1159; https://doi.org/10.3390/rs13061159
Received: 25 January 2021 / Revised: 15 March 2021 / Accepted: 16 March 2021 / Published: 18 March 2021
(This article belongs to the Special Issue Leaf and Canopy Biochemical and Biophysical Variables Retrieval)
Leaf angle distribution (LAD) is an important attribute of forest canopy architecture and affects the solar radiation regime within the canopy. Terrestrial laser scanning (TLS) has been increasingly used in LAD estimation. The point clouds data suffer from the occlusion effect, which leads to incomplete scanning and depends on measurement strategies such as the number of scans and scanner location. Evaluating these factors is important to understand how to improve LAD, which is still lacking. Here, we introduce an easy way of estimating the LAD using open source software. Importantly, the influence of the occlusion effect on the LAD was evaluated by combining the proposed complete point clouds (CPCs) with the simulated data of 3D tree models of Aspen, Pin Oak and White Oak. We analyzed the effects of the point density, the number of scans and the scanner height on the LAD and G-function. Results show that: (1) the CPC can be used to evaluate the TLS-based normal vector reconstruction accuracy without an occlusion effect; (2) the accuracy is slightly affected by the normal vector reconstruction method and is greatly affected by the point density and the occlusion effect. The higher the point density (with a number of points per unit leaf area of 0.2 cm−2 to 27 cm−2 tested), the better the result is; (3) the performance is more sensitive to the scanner location than the number of scans. Increasing the scanner height improves LAD estimation, which has not been seriously considered in previous studies. It is worth noting that relatively tall trees suffer from a more severe occlusion effect, which deserves further attention in further study. View Full-Text
Keywords: occlusion effect; leaf angle distribution; terrestrial laser scanning; computer simulation occlusion effect; leaf angle distribution; terrestrial laser scanning; computer simulation
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MDPI and ACS Style

Jiang, H.; Hu, R.; Yan, G.; Cheng, S.; Li, F.; Qi, J.; Li, L.; Xie, D.; Mu, X. Influencing Factors in Estimation of Leaf Angle Distribution of an Individual Tree from Terrestrial Laser Scanning Data. Remote Sens. 2021, 13, 1159. https://doi.org/10.3390/rs13061159

AMA Style

Jiang H, Hu R, Yan G, Cheng S, Li F, Qi J, Li L, Xie D, Mu X. Influencing Factors in Estimation of Leaf Angle Distribution of an Individual Tree from Terrestrial Laser Scanning Data. Remote Sensing. 2021; 13(6):1159. https://doi.org/10.3390/rs13061159

Chicago/Turabian Style

Jiang, Hailan, Ronghai Hu, Guangjian Yan, Shiyu Cheng, Fan Li, Jianbo Qi, Linyuan Li, Donghui Xie, and Xihan Mu. 2021. "Influencing Factors in Estimation of Leaf Angle Distribution of an Individual Tree from Terrestrial Laser Scanning Data" Remote Sensing 13, no. 6: 1159. https://doi.org/10.3390/rs13061159

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