摘要
【目的】以湖南省栎类树种为试点,开展基于高精度地基激光雷达的非破坏性数据采集的立木材积模型构建及应用研究。【方法】使用地基激光雷达扫描栎类单木143株,利用点云数据提取林木参数,选择符合生物学特性的模型为备选,使用Marquardt迭代法和加权最小二乘法进行模型拟合,根据模型拟合、模型评价和模型适用性检验结果选择最优立木材积预测模型。【结果】使用点云提取参数构建的传统一元和二元立木材积模型的R^(2)大于0.9,估计值标准差小于0.1,总相对误差和平均系统误差小于3%,预估精度均在95%以上,二元立木材积模型平均百分标准误差小于7%,一元立木材积模型平均百分标准误差小于16%;通过分析单木分段材积与整体材积之间的关系,以相对树高0.276位置处的直径结合树高构建立木材积模型,所建模型在所有立木材积模型中精度最高,R^(2)为0.992,估计值标准差小于0.03,优于传统立木材积模型,提升了材积的预估精度。利用地基激光雷达点云数据构建的立木材积模型的预测单木材积与实测单木材积之间无显著性差异。【结论】利用点云数据提取的林木参数具有较高的精度,可以替代实测的林木参数进行相关模型构建;构建的立木材积模型精度能够满足湖南省日常林业调查需要,为今后的模型构建提供一种无损技术手段;提出的新参数能够提升立木材积模型的精度,为立木材积模型构建提供了一种新的思路。
【Objective】To carry out the research and application study of tree standing volume modeling based on non-destructive data collection by high-precision terrestrial laser scanning using Quercus species in Hunan Province as a pilot project.【Method】143 single trees of Quercus species were scanned by Terrestrial Laser Scanning,the parameters of the trees were extracted from point cloud data,the model that meets the biological characteristics was selected as an alternative,and the Marquardt iterative method and the weighted least squares method were used to fit the model,and the optimal timber standing volume model was selected based on the results of the model fitting,the evaluation of the model and the test of the applicability of the model.【Result】The R^(2) of the traditional one-dimensional and two-dimensional lumber models constructed using point cloud extraction parameters was greater than 0.9,the remaining standard deviation was less than 0.1,the total relative error and average systematic error were less than 3%,and the prediction accuracy was over 95%.The average percent standard error of the two-dimensional lumber model was less than 7%,and that of the onedimensional lumber model was less than 16%.By analyzing the relationship between the volume of individual tree segments and the overall volume,it is proposed to construct a standing volume model by combining the diameter with the height at the position of 0.276 relative to the height of the tree,and the model constructed has the highest accuracy among all the standing volume models,with an R^(2) of 0.992 and a residual standard deviation of less than 0.03,which is superior to the traditional standing volume model,and enhances the accuracy of the standing volume prediction.And there was no significant difference between the estimated and measured wood volume of the wood standing volume model constructed using Terrestrial Laser Scanning point cloud data.【Conclusion】The forest parameters extracted from the point cloud data have high accuracy,and can replace the measured forest parameters for the related modeling;the accuracy of the constructed timber standing volume model can meet the needs of the daily forestry survey in Hunan Province,and provide a non-destructive technical means for the future modeling;the proposed new parameters can improve the accuracy of the timber standing volume modeling,and provide a new way of thinking for the construction of timber standing volume model.
作者
兰俊宇
唐杰
曹文昊
周晟
王金池
孙华
LAN Junyu;TANG Jie;CAO Wenhao;ZHOU Sheng;WANG Jinchi;SUN Hua(Research Center of Forestry Remote Sensing&Information Engineering,Central South University of Forestry&Technology,Changsha 410004,Hunan,China;Hunan Provincial Key Laboratory of Forestry Remote Sensing Based Big Data&Ecological Security,Central South University of Forestry&Technology,Changsha 410004,Hunan,China;Key Laboratory of National Forestry and Grassland Administration on Forest Resources Management and Monitoring in Southern China,Central South University of Forestry&Technology,Changsha 410004,Hunan,China;Central South Academy of Inventory and Planning of NFGA,Changsha 410014,Hunan,China)
出处
《中南林业科技大学学报》
北大核心
2025年第12期36-46,共11页
Journal of Central South University of Forestry & Technology
基金
国家自然科学基金项目(32471861,31971578)
湖南省科技创新计划(科技创新领军人才)项目(2023RC1065)。
关键词
湖南省
栎类树种
地基激光雷达
立木材积模型
削度方程
单木参数提取
Hunan Province
Quercus species
terrestrial laser scanning
standing volume model
taper equation
single-tree parameter extraction
