检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:杜志 陈振雄 贺东北 孙华[2] 王金池 张文凡 DU Zhi;CHEN Zhenxiong;HE Dongbei;SUN Hua;WANG Jinchi;ZHANG Wenfan(Central South Academy of Inventory and Planning of NFGA,Changsha 410014,Hunan,China;Research Center of Forestry Remote Sensing&Information Engineering,Central South University of Forestry and Technology,Changsha 410004,Hunan,China;Forest Survey and Planning Institute of Xizang Autonomous Region,Lhasa 850005,Xizang,China)
机构地区:[1]国家林业和草原局中南调查规划院,湖南长沙410014 [2]中南林业科技大学林业遥感信息工程研究中心,湖南长沙410004 [3]西藏自治区林业调查规划研究院,西藏拉萨850005
出 处:《中南林业调查规划》2025年第1期70-76,共7页Central South Forest Inventory and Planning
基 金:国家林业和草原局中南调查规划院自主立项项目“激光雷达多尺度森林蓄积量监测技术研究”(No.2023011)。
摘 要:以湖南省马尾松、栎类2个树种(组)为研究对象,利用地基激光雷达扫描样木,获取树高、胸径、地径等林木参数,基于激光雷达点云数据构建树高曲线模型和材积模型,并以解析木调查实测数据为对照,检验点云数据提取的林木参数精度和评估林业数表模型的适用性。结果表明:1)地基激光雷达提取的林木参数与同口径解析木实测数据无显著差异,马尾松、栎类2个树种(组)点云数据提取的胸径估计精度均达98%以上,树高估计精度在92%以上,材积估计精度在90%左右;2)基于点云数据所建的二元立木材积模型、一元立木材积模型和地径材积模型拟合精度高,其中二元立木材积模型的R2均达0.99、预估精度(P)超过98%,马尾松、栎类2个树种(组)的树高曲线模型的P达96%,与实测数据所建模型的拟合精度相近。由此可见,地基激光雷达技术可实现非破坏性、快速精准的林木参数提取,构建基于点云数据的高精度林业数表模型,为限制或禁止采伐情况下的林业数据获取和数表模型研建提供了一种新的解决方案。Taking two tree species(groups)of Pinus massoniana and Quercus spp.in Hunan Province as research objects,this study utilized terrestrial laser scanning(TLS)to obtain tree parameters such as tree height,diameter at breast height(DBH),and ground diameter.Tree height curve models and volume models were constructed based on TLS point cloud data.The accuracy of the tree parameters extracted from the point cloud data was tested,and the applicability of the forestry table models was evaluated by comparing with measured data from dendrometric analysis.The results indicated that:1)there was no significant difference between the tree parameters extracted from TLS data and those obtained from dendrometric analysis.The estimation accuracy of DBH extracted from point cloud data for both Pinus massoniana and Quercus spp.reached above 98%,while the estimation accuracy of tree height exceeded above 92%,and that of volume was around 90%.2)The binary standing timber volume models,univariate standing timber volume models,and ground diameter volume models built using point cloud data exhibited high fitting accuracy.The determination coefficients of the binary standing timber volume reached 0.99,with an estimation accuracy exceeding 98%.The tree height curve models for both two tree species(groups)had an estimation accuracy of 96%,matching the fitting accuracy of models constructed from measured data.In conclusion,terrestrial laser scanning technology enabled non-destructive,rapid,and precise extraction of tree parameters,allowing for the construction of highly accurate forestry table models based on point cloud data.This approach provides a new solution for forestry data acquisition and table model development under conditions where logging is restricted or prohibited.
分 类 号:S757.2[农业科学—森林经理学]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.13