[1]尤号田,邢艳秋*,王铮,等. 利用LiDAR离散点云估测针叶林叶面积指数[J].西北林学院学报,2014,29(03):41-47.[doi:doi:10.3969/j.issn.1001-7461.2014.03.08]
 YOU Hao-tian,XING Yan-qiu*,WANG Zheng,et al. Estimation of the Leaf Area Index of Coniferous Forests Using LiDAR Discrete Point Cloud[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2014,29(03):41-47.[doi:doi:10.3969/j.issn.1001-7461.2014.03.08]
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 利用LiDAR离散点云估测针叶林叶面积指数()
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《西北林学院学报》[ISSN:1001-7461/CN:61-1202/S]

卷:
第29卷
期数:
2014年03期
页码:
41-47
栏目:
出版日期:
2014-05-30

文章信息/Info

Title:
 Estimation of the Leaf Area Index of Coniferous Forests Using LiDAR Discrete Point Cloud
文章编号:
1001-7461(2014)03-0041-07
作者:
 尤号田1邢艳秋1*王铮2孙小添1王萌1
 (1.东北林业大学 森林作业与环境研究中心,黑龙江 哈尔滨 150040;2.吉林省基础地理信息中心,吉林 长春 130062)
Author(s):
YOU Hao-tian1XING Yan-qiu1*WANG Zheng2SUN Xiao-tian1WANG Meng
 (1.Center for Forest Operations and Environment,Northeast Forestry University,Harbin,Heilongjiang 150040,China;2. Jilin Provincial Geomatics Center,Changchun,Jilin 130062 ,China)
关键词:
 小光斑激光雷达离散点云叶面积指数针叶林多变量模型点云密度
Keywords:
 small footprint LiDAR discrete point cloud leaf area index coniferous forest multi-variable model point cloud density
分类号:
S771.5
DOI:
doi:10.3969/j.issn.1001-7461.2014.03.08
文献标志码:
A
摘要:
 通过对小光斑激光雷达离散点云数据进行处理,提取了6个变量参数分别用于估测针叶林叶面积指数,为了提高模型估测精度及弥补单变量模型的不足,在单变量模型的基础上尝试多变量组合共同用于估测森林叶面积指数,经过对比得出单变量模型中OGF模型最好,拟合相关性R=0.897,预测精度p=0.959;多变量预测模型结果差异不大,拟合相关性均>0.905,估测精度均>0.957。同时为了验证模型的推广性,对点云数据进行随机稀释操作获得4种不同密度的点云数据,分别用于验证点云密度对OGF模型及OGFLPI组合模型的影响,结果表明点云密度对模型结果的影响不大,即使在0.125倍点云密度时模型仍能较好的估测针叶林叶面积指数,满足生产需要。
Abstract:
 Based on processing discrete point cloud data of small footprint LiDAR,six variable parameters were extracted and used to estimate coniferous forest leaf area index (LAI).In order to improve the accuracy of the model and make up the deficiency of the univariate model,multi-variable combination was adopted. Compared with other univariate models,the OGF model was the most suitable one featuring in higher fitting correlation (R=0.897) and prediction accuracy (p=0.959).And there was little difference among the multi-variable prediction models whose fitting correlations were bigger than 0.905 and all the prediction accuracies were more than 0.957.In order to validate the generalization of the model,4 different densities of point cloud data which were obtained by random dilution operation,were used to verify the influence of point cloud density on OGF model as well as the combination model of OGF and LPI,respectively.The result suggested that point cloud density had little influence on the model results and could meet the need of practical production.

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备注/Memo

备注/Memo:
 收稿日期:2013-09-13 修回日期:2013-10-17
基金项目:中央高校基本科研业务费专项资金支撑项目(DL12EB07);国家自然科学基金(41171274)。
作者简介:尤号田,男,硕士,研究生。研究方向:激光雷达对森林结构参数定量估测。E-mail: wuliu2007_02@163.com
*通信作者:邢艳秋,女,博士,教授,研究方向:森工管理与林业信息工程。E-mail: yanqiuxing@nefu.edu.cn
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