Leaf area index (LAI) is a key parameter for studying global terrestrial ecology and environment and has great ecological significance. How to accurately measure and calculate structural parameters of trees has become...Leaf area index (LAI) is a key parameter for studying global terrestrial ecology and environment and has great ecological significance. How to accurately measure and calculate structural parameters of trees has become an urgent matter. This paper reports the use of terrestrial laser scanning (TLS) as a measurement tool to achieve accurate LAI estimation through point cloud preprocessing measures, the LeWos algorithm, and voxel methods. The accuracy and feasibility of this indirect measurement method were explored. It is found that the single wood structure parameters extracted from TLS have a good linear relationship with manual measurement, and the extraction errors meet the requirements of real-scene conversion. The study also found when the voxel size is consistent with the minimum distance of the point cloud set by TLS instrument, it has a strong correlation with the measured value of canopy analyser. These results lay the foundation for conveniently and quickly obtaining structural parameters of trees, tree growth state detection, and canopy ecological benefit assessment.展开更多
叶面积的大小可以对树木的生长和生命活动产生深远的影响,进而关系到树木生物量的变化和森林生态的发展趋势,叶面积的研究可以对树木的相关分析起到较为关键的作用。基于黑龙江省48株红松人工林解析木数据和排水法测定的叶面积数据,建...叶面积的大小可以对树木的生长和生命活动产生深远的影响,进而关系到树木生物量的变化和森林生态的发展趋势,叶面积的研究可以对树木的相关分析起到较为关键的作用。基于黑龙江省48株红松人工林解析木数据和排水法测定的叶面积数据,建立基础线性回归模型,后引入随机效应参数构建混合效应回归模型以提高拟合效果和预估精度。在加入树木层次的随机效应时,最终得到的最优混合效应模型含有3个随机效应参数,分别为枝条基径的对数(lnBD)、枝条长度的对数(lnSL)、树高的对数(lnHT)。该模型的R_(a)^(2)=0.86,平均绝对偏差M_(AE)=0.3428,均方根误差R_(MSE)=0.4841,统计指标较仅包含固定效应的基础线性模型均有较好的提高。综合分析得出该模型可以较好地对红松枝条叶面积大小进行描述。基于该模型计算红松树冠叶面积并得到混合效应预估模型,混合模型的R a 2=0.83,R_(MSE)=0.4429。通过检验结果可知该模型可以较好地对红松树冠叶面积进行预估计算,为日后该地区人工红松的经营提供良好的指导方向。展开更多
文摘Leaf area index (LAI) is a key parameter for studying global terrestrial ecology and environment and has great ecological significance. How to accurately measure and calculate structural parameters of trees has become an urgent matter. This paper reports the use of terrestrial laser scanning (TLS) as a measurement tool to achieve accurate LAI estimation through point cloud preprocessing measures, the LeWos algorithm, and voxel methods. The accuracy and feasibility of this indirect measurement method were explored. It is found that the single wood structure parameters extracted from TLS have a good linear relationship with manual measurement, and the extraction errors meet the requirements of real-scene conversion. The study also found when the voxel size is consistent with the minimum distance of the point cloud set by TLS instrument, it has a strong correlation with the measured value of canopy analyser. These results lay the foundation for conveniently and quickly obtaining structural parameters of trees, tree growth state detection, and canopy ecological benefit assessment.
文摘叶面积的大小可以对树木的生长和生命活动产生深远的影响,进而关系到树木生物量的变化和森林生态的发展趋势,叶面积的研究可以对树木的相关分析起到较为关键的作用。基于黑龙江省48株红松人工林解析木数据和排水法测定的叶面积数据,建立基础线性回归模型,后引入随机效应参数构建混合效应回归模型以提高拟合效果和预估精度。在加入树木层次的随机效应时,最终得到的最优混合效应模型含有3个随机效应参数,分别为枝条基径的对数(lnBD)、枝条长度的对数(lnSL)、树高的对数(lnHT)。该模型的R_(a)^(2)=0.86,平均绝对偏差M_(AE)=0.3428,均方根误差R_(MSE)=0.4841,统计指标较仅包含固定效应的基础线性模型均有较好的提高。综合分析得出该模型可以较好地对红松枝条叶面积大小进行描述。基于该模型计算红松树冠叶面积并得到混合效应预估模型,混合模型的R a 2=0.83,R_(MSE)=0.4429。通过检验结果可知该模型可以较好地对红松树冠叶面积进行预估计算,为日后该地区人工红松的经营提供良好的指导方向。