[1]胡云帆,张怀清,安锋,等. 基于激光点云的橡胶树参数反演与数字孪生构建[J].西北林学院学报,2024,39(2):1-12.[doi:10.3969/j.issn.1001-7461.2024.02.01]
　HU Yun-fan,ZHANG Huai-qing,AN Feng,et al.Hevea brasiliensis Property Retrieval and Construction of Digital Twin Based on Laser Scanning Data[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2024,39(2):1-12.[doi:10.3969/j.issn.1001-7461.2024.02.01]
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 基于激光点云的橡胶树参数反演与数字孪生构建()
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《西北林学院学报》[ISSN:1001-7461/CN:61-1202/S]

卷:
第39卷
期数:
2024年第2期
页码:
1-12
栏目:
出版日期:
2024-03-31

文章信息/Info

Title:
Hevea brasiliensis Property Retrieval and Construction of Digital Twin Based on Laser Scanning Data
文章编号:
1001-7461(2024)02-0001-12
作者:
 胡云帆1; 张怀清2; 安锋3; 云挺1; 4*
 (1.南京林业大学 信息科学技术学院，江苏 南京 210037；2.中国林科院 资源信息所，北京 100091；3.中国热带农业科学院 橡胶研究所，海南儋州热带农业生态系统国家野外科学观测研究站，海南 海口 571737；4.南京林业大学 林学院，江苏 南京 210037)
Author(s):
 HU Yun-fan1; ZHANG Huai-qing2; AN Feng3; YUN Ting1; 4*
 (1.College of Information Science and Technology,Nanjing Forestry University,Nanjing 210037,Jiangsu,China; 2.Institute of Forest Resource Information Techniques,Chinese Academy of Forestry,Beijing 100091,China; 3.Rubber Research Institute,Chinese Academy of Tropical Agricultural Sciences,Hainan Danzhou Agro-ecosystem National Observation and Research Station,Haikou 571737,Hainan,China; 4.College of Forestry,Nanjing Forestry University,Nanjing 210037,Jiangsu,China)
关键词:
 ; 地基激光点云; 点云簇过分割; 空间殖民算法; 树木骨架重建; 林木参数提取; 数字孪生
Keywords:
 ; ground-based laser point cloud;  point cloud cluster over-segmentation;  space colonization algorithm;  tree skeleton reconstruction;  forest parameter retrieval;  digital twin
分类号:
TP 391.9
DOI:
10.3969/j.issn.1001-7461.2024.02.01
文献标志码:
A
摘要:
 基于激光雷达(Light Detection And Ranging，LiDAR)数据重建树体三维模型并精准获取林木空间枝干结构参数对林木性状评价、森林动态经营管理与可视化研究具有重要意义。为此提出一种基于骨架细化提取的树木模型重建方法。首先，采用FocusS350/350 PLUS三维激光扫描仪获取3块不同树龄橡胶树的样地数据。然后，作为细化建模的重点，将枝干点云从原始树点中分离出来，再将其过度分割为若干点云簇，通过相邻点云簇判断是否有分枝以及动态确定骨架点间距，并将其运用在空间殖民算法以此来生成树的三维骨架点和骨架点连通性链表，根据连通链表结构自动识别树木中的主枝干和各个一级分枝，再通过广义圆柱体生成树干完成树木三维重建。最后，利用数字孪生技术对这3块不同树龄样地树木进行三维实景建模，使其穿越时空在同一空间中重现，以便更为直观地观察树木在生长过程中的形态变化。该算法得到的橡胶树胸径与实测值比对为，决定系数（R2）>0.91，均方根误差(root mean square Error，RMSE)<1.00 cm；主枝干与一级枝干的分枝角为，R2>0.91，RMSE<2.93；一级枝干直径为，R2>0.90，RMSE<1.41 cm；将3个树龄放在一起计算其生长参数，并与实测值进行对比，发现该算法同样适用于异龄林样地的各个生长参数计算。同时发现橡胶树的一级枝条的直径越大，其相对应的叶团簇体积就越大。运用人工智能的理论模型来处理林木的激光点云数据，旨在为森林的可视化以及树木骨架结构的智能化分析与处理等研究领域提供有价值的参考。
Abstract:
 Accurate tree skeleton reconstruction and growth parameter retrieval from light detection and ranging (LiDAR) data is an essential prerequisite for forest information investigation and phenotypic characteristic acquirement.This research proposed an approach of tree skeleton modeling based on skeleton refinement extraction using computer graphics techniques.First,FocusS350/350 PLUS 3D laser scanner was used to obtain the sample data of three tropical rubber (Hevea brasiliensis) sample plots with different tree ages.Then,as the focus of the advanced modeling,the stem point cloud was separated from the original tree points.Next,the tree was over-segmented into several point cloud clusters.The adjacent point cloud clusters were used to determine whether there were branches,and the spacing of skeleton points was dynamically determined,that was then applied to the spatial colonization algorithm to generate the three-dimensional skeleton points and the skeleton point connectivity list of the tree,and the generalized cylinder generated the tree trunk to complete the 3D reconstruction of the tree.Finally,the three-dimensional real-scene modeling of the three samples of different tree ages was carried out to reproduce the trees in the same space through time and space to observe the morphological changes of the trees in the growth process more intuitively.The comparisons between the rubber tree diameter obtained from the algorithm and the measured value were as follows:the coefficient of determination R2 was greater than 0.91,and the root mean square error (RMSE) was less than 1.00 cm.The branching angle between the main stem and the first-order branch stem was:the coefficient of determination R2 was greater than 0.91,and the root mean square error RMSE was less than 2.93.The diameter of the first-order branch stem was that the coefficient of determination R2 was greater than 0.90,and the root mean square error RMSE was less than 1.41 cm; The growth parameters of three different ages were calculated together and compared with their measured values,from which it was found that the algorithm was also applicable to calculating various growth parameters in uneven-aged forest plots.At the same time,it was found that the diameter of the first branch of H.brasiliensiss was positively correlated with the volume of the corresponding leaf cluster.In this study,the theoretical model of artificial intelligence is applied to the laser point cloud data processing of trees,which can provide a reference for the forest visualization,and intelligent analysis and processing of tree skeleton structure.

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备注/Memo

备注/Memo:
 收稿日期：2023-02-18修回日期：2023-06-09
基金项目：国家自然科学基金(31770591,32071681)；江苏省自然科学基金面上项目(BK20221337)；江苏省农业自主创新项目(CX(22)3048)；自然资源部国土卫星遥感应用重点实验室开放基金(KLSMNR-G202208)。
第一作者：胡云帆。研究方向：林业人工智能。E-mail：1575494152@qq.com
*通信作者：云挺，博士，教授。研究方向：林业信息化、计算机应用技术。E-mail：yunting@njfu.edu.cn
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