[1]邓洋波,余坤勇,俞欣妍,等. 基于点云体素化的单木叶面积指数地基遥感反演[J].西北林学院学报,2017,32(3):191-197.[doi:10.3969/j.issn.1001-7461.2017.03.36]
 DENG Yang-bo,YU Kun-yong,YU Xin-yan,et al. Estimation of Individual Tree Leaf Area Index of Terrestrial Remote Sensing Inversion Based on Point Cloud Voxelization[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2017,32(3):191-197.[doi:10.3969/j.issn.1001-7461.2017.03.36]
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 基于点云体素化的单木叶面积指数地基遥感反演()
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《西北林学院学报》[ISSN:1001-7461/CN:61-1202/S]

卷:
第32卷
期数:
2017年第3期
页码:
191-197
栏目:
出版日期:
2017-05-31

文章信息/Info

Title:
 Estimation of Individual Tree Leaf Area Index of Terrestrial Remote Sensing Inversion Based on Point Cloud Voxelization
文章编号:
1001-7461(2017)03-0191-07
作者:
 邓洋波12余坤勇12俞欣妍12项佳12张佳奇12刘健123*
 (1.福建农林大学 林学院,福建 福州 350002;2.3S技术与资源环境优化利用福建省高校重点实验室,福建 福州 350002;3.三明学院,福建 三明 365000)
Author(s):
 DENG Yang-bo12YU Kun-yong12YU Xin-yan12XIANG Jia12ZHANG Jia-qi12LIU Jian123*
 (1.College of Forestry,Fujian Agriculture and Forestry University,Fuzhou,Fujian 350002,China; 2.Fujian Provincial College Key Laboratory of 3S Technology and Optimization & Utilization of Environment and Resources,Fuzhou,Fujian 350002,China; 3.Sanming University,Sanming,Fujiang 365000,China)
关键词:
 叶面积指数地基激光雷达体素化点云密度
Keywords:
 leaf area index terrestrial laser scanning voxelization point cloud density
分类号:
S758.4
DOI:
10.3969/j.issn.1001-7461.2017.03.36
文献标志码:
A
摘要:
 以黑松、马尾松、荔枝、相思树为对象,采用地基激光雷达获取点云数据,基于点云体素化理论,分割叶片点云,建立“叶片—体素”的投影关系,研究体素化理论中尺度因子与点云密度对叶面积指数(LAI)反演精度的影响,实现单木LAI的高精度获取。结果表明,样木反演的LAI随着尺度因子的增大而增大,最优尺度区间为1.2~1.3,样木LAI最优反演精度范围为93.3%~99.9%,决定系数R2为0.989 3,反演结果与实测LAI具有较高相关性;在最优尺度区间下,样木LAI反演精度随着点云密度的降低而减小,最大精度为98.63%,最小精度为84.14%,点云密度对单木LAI反演精度影响不大。
Abstract:
 Terrestrial laser scanning was used to obtain point cloud of Pinus thunbergii,P.massoniana,Litchi chinensis and Acacia confusa,and blade point cloud segmentation to establish a “blade-voxel” projection relationship.The influences of the scale factor and point cloud density on LAI inversion accuracy were examined by using point cloud voxel voxelization,to simulate LAI of individual tree precisely.The results showed that the LAI inversion of sample wood increased with the increase of scale factor,where the optimal scale ranged from 1.2 to 1.3.The optimal LAI inversion accuracy of three tree species ranged from 93.3% to 99.9% and determination coefficient (R2) was 0.989 3,which exhibited relatively high correlation of LAI inversion results and the measured.Based on the optimal scale range,LAI inversion accuracy of sample wood decreased with the loss of the point cloud density,in which maximum precision was 98.63%,the minimum accuracy was 84.14%,and point cloud density did not affect LAI simulation of individual tree.

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备注/Memo

备注/Memo:
 收稿日期:2016-10-18修回日期:2017-01-10
基金项目:福建省高校产学研合作项目(2015N5010);国家林业局林业科技成果国家级推广项目([2015]13号)。
作者简介:邓洋波,男,在读硕士,研究方向:林业3S技术应用。E-mail:317735600@qq.com
*通信作者:刘健,男,博士,教授,研究方向:林业3S技术应用。E-mail:fjliujian@126.com
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