利用东北林区云冷杉林、落叶松林、樟子松林、红松林、栎树林、桦树林、杨树林、榆树林、椴树林和水胡黄林10种森林类型的1 947个样地的激光雷达数据和地面实测蓄积量数据,首先通过多元线性回归和非线性回归方法,分别建立基于机载激光雷达数据的森林蓄积量回归估计模型,并通过对比分析,确定统一形式的基础回归模型;然后利用哑变量建模方法,建立基于不同森林类型参数和相同激光雷达变量的蓄积量模型。结果表明,研究建立的10种森林类型的线性蓄积量回归模型的解释变量个数在2~7之间,确定系数在0.460~0.858之间;非线性蓄积量回归模型的解释变量个数在2~4之间,确定系数在0.461~0.846之间。基于点云平均高度和平均强度建立的10种森林类型的二元蓄积量模型(研究称之为标准模型),其确定系数在0.440~0.815之间,平均预估误差在2.88%~4.42%之间,平均百分标准误差在16.76%~25.52%之间,预估精度基本达到森林资源规划设计调查技术规定要求。依据研究建立的10种森林类型的蓄积量模型,可以编制基于激光雷达数据的航空林分材积表,在森林资源调查实践中推广应用。

Based on the airborne laser scanning(ALS) data and field measurement data of 1 947 sample plots distributed across the spruce & fir(Picea spp.& Abies spp.),larch(Larix spp.),Mongolian scotch pine(Pinus sylvestris var mongolica),Korean pine(Pinus koraiensis),oak(Quercus spp.),birch(Betula spp.),poplar(Populus spp.),elm(Ulmus spp.),linden(Tilia spp.),and other three precious broadleaved species(Fraxinus mandshurica,Juglans mandshurica & Phellodendron amurense) forest stands in Northeast China,the stand volume regression models were developed through multiple linear regression and nonlinear regression methods,and the base regression model was determined with comparison and analysis.Then,the integrated stand volume models with stand type-specific parameters and the same ALS variables were developed,using the dummy variable modeling approach.The results showed that multiple linear volume regression models developed in this study for the 10 stand types have 2~7 explainable variables and the coefficients of determination(R ²) are between 0.460~0.858;and the nonlinear models have 2~4 explainable variables and the R ² are between 0.461~0.846.The two-variable nonlinear volume models based on mean height and mean intensity of point clouds are defined as standard volume models,of which the R ² are between 0.440~0.815,the mean prediction errors(MPEs) are between 2.88%~4.42%,and the mean percent standard errors(MPSEs) are between 16.76%~25.52%,which almost meet the need for precision requirements of the regulation on forest management inventory.According to the stand volume models developed in this study for 10 forest types,aerial stand volume tables based on ALS data can be established,which may be applied in forest management inventory.