节点文献

三维激光扫描系统在建立单株立木材积模型中的研究

RESEARCH ON ESTABLISH SINGLE TREE’S SVOLUME MODEL BY 3D LASER SCANNING SYSTEM

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 赵芳韦雪花高祥刘晓丽冯仲科

【Author】 ZHAO Fang,WEI Xue-hua,GAO Xiang,LIU Xiao-li,FENG Zhong-ke(Institute of GIS,RS & GPS,Beijing Forestry University,Beijing 100083,China)

【机构】 北京林业大学测绘与3S技术研究中心

【摘要】 本文提出了一种利用三维激光扫描系统测量立木材积并建立材积回归模型的方法。该方法是在北京鹫峰森林公园林场,利用三维扫描系统在样地内对油松、龙爪槐、银杏三种树种,共180株标准木进行立木三维扫描,可以获取精确的立木的胸径、树高、冠幅等基本测树因子,并根据点云数据构建树木模型,实现树干的三维表面重建,得到精确单木材积。然后由这些精确的单木材积数据回归建立一元立木材积模型、二元立木材积模型。通过内、外符合精度检验之后,最终所得模型所描绘的曲线与三维激光扫描所得构建的材积曲线基本上是一致,说明这种方法能够用于回归建立立木材积模型及材积表。这种方法工作效率高、不破坏树木,能够用于推广回归建立立木材积模型及材积表,对于建立新型材积模型有普遍意义。

【Abstract】 This paper puts forward a kind of make use of the 3D laser scanning system measuring volume and establish volume regression model method.This test where at JiuFeng forest park forest in Beijing,using 3D scanning system in sample plot in Pinus tabulaeformis Carr,Chinese pagoda tree,Ginkgo three tree species,180 strains standard wood for 3D scanning,can obtain accurate diameter at breast height,tree height,crown breadth basic measuring tree factor,and according to the point cloud data to construct trees model,realize the trunk of 3D surface reconstruction,get accurate single wood product.Then the accurate single wood volume data is product single tree volume regression model,binary volume regression model.Through the internal and external precision after inspection,and finally the model depicts curve and 3D laser scanning income constructed volume curve is basically consistent,shows this method can be used to return to establish single tree volume model and volume table.This method work efficiency is high,does not destroy the trees,and can be used to promote regression to establish buck volume model and volume table,for establishing the new volume model has universal significance.

【基金】 国家863项目(2009AA12Z327,2008AA121305-4);国家科技支撑计划项目(2012BAH34B01)
  • 【文献出处】 山东农业大学学报(自然科学版) ,Journal of Shandong Agricultural University(Natural Science Edition) , 编辑部邮箱 ,2013年02期
  • 【分类号】S758.1
  • 【被引频次】23
  • 【下载频次】372
节点文献中: 

本文链接的文献网络图示:

本文的引文网络