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|Table of Contents|

基于多站扫描的点云特征参数与材积结构动态分析(PDF)

《南京林业大学学报(自然科学版)》[ISSN:1000-2006/CN:32-1161/S]

Issue:
2019年06期
Page:
83-90
Column:
研究论文
publishdate:
2019-11-25

Article Info:/Info

Title:
Dynamic analysis of point cloud characteristic parameters and volume structure based on multi-station scan
Article ID:
1000-2006(2019)06-0083-08
Author(s):
JIANG Jiawen1 WEN Xiaorong12 GU Haibo1 ZHANG Zhengnan1 LIU Fangzhou3 ZHANG Yanli4 SUN Yuan12*
(1. College of Forestry, Nanjing Forestry University, Nanjing 210037,China; 2. Co-Innovation Center for the Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037,China; 3. College of Information Science and Technology, Nanjing Forestry University, Nanjing 210037,China; 4. Arthur Temple College of Forestry and Agriculture, Stephen F.Austin State University, Nacogdoches, TX 75962, USA)
Keywords:
stand structure dynamic change terrestrial laser scanner volume model Liriodendron chinense
Classification number :
S758; TP79
DOI:
10.3969/j.issn.1000-2006.201901020
Document Code:
-
Abstract:
【Objective】 The use of terrestrial laser scanner(TLS)in multistations to obtain the point cloud information of a standing tree, extracting the characteristic parameters of the point cloud distribution that expand the tree measurement factor, and establishing a volume model based on these characteristic parameters. 【Method】Liriodendron chinense plantation was studied, and the structural changes of the two stages(2014, 2017)were analyzed using the upper diameter(d)and tree height(H)of the standing tree provided by the point cloud data. The characteristic parameters of TLS point cloud named high cumulative percentage was designed and extracted, and other height-related feature parameters were extracted as a set of variables; the extracted DBH and feature parameters were considered as another set of variables; finally, the characteristic parameters were analyzed. The correlation between DBH and volume was established by stepwise regression method to build a volume model based on two sets of variables, and analyze the dynamic changes of the two phases. 【Result】The characteristic parameters H25 and Ht, var(point cloud height variance)were used to fit the two-stage volume model, and their R2 were 0.771 1 and 0.742 6, respectively. The accuracy of the model using the characteristic parameter H25 and the DBH improved. The two sets of volume models mentioned earlier were used to predict the volume change in each step; the model value and the measured value was not significantly different, and R2 is higher than 0.9. 【Conclusion】 The high cumulative percentage extracted in this study is closely related to the tree measurement factor, which can invert the dynamic structure of forest trees. The volume model developed by the research achieves high precision and can be used for the monitoring of the dynamic change in forest wood product, which provides a new reference for TLS point cloud to participate in the dynamic monitoring of forest resources.

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Last Update: 2019-11-30