Segmented taper equation was selected to model stem profile of Dahurian larch （Larix gmelinii Rupr.）. The data were based on stem analysis of 74 trees from Dailing Forest Bureau in Heilongjiang Province, Northeaster...Segmented taper equation was selected to model stem profile of Dahurian larch （Larix gmelinii Rupr.）. The data were based on stem analysis of 74 trees from Dailing Forest Bureau in Heilongjiang Province, Northeastern China. Two taper equations with crown ratio and stand basal area were derived from the Max and Burkhart’s （1976） taper equation. Three taper equations were evaluated： （1） the original equation, （2） the original equation with crown ratio, and （3） the original equation with basal area. SAS NLIN and SYSNLIN procedures were used to fit taper equations. Fit statistics and cross-validation were used to evaluate the accuracy and precision of these models. Parameter estimates showed that the original equation with inclusion of crown ratio and basal area variables provided significantly different parameter estimates with lower standard errors. Overall fit statistics indicated that the root mean square error （RMSE） for diameter outside and inside bark decreased respectively by 10% and 7% in the original model with crown ratio and by 12% and 7.2% in the original model with basal area. Cross-validation further confirmed that the original equation with inclusion of crown ratio and basal area variables provided more accurate predictions at the lower section （relative heights, 10%） and upper section （relative heights, 50%） for both outside and inside bark diameters.展开更多
In this study, compatible taper and stem volume equations were developed for Larix kaempferi species of South Korea. The dataset was split into two groups： 80% of the data were used in model fitting and the remaining...In this study, compatible taper and stem volume equations were developed for Larix kaempferi species of South Korea. The dataset was split into two groups： 80% of the data were used in model fitting and the remaining 2o% were used for validation. The compatible MB76 equations were used to predict the diameter outside bark to a specific height, the height to a specific diameter and the stem volume of the species. The result of the stem volume analysis was compared with the existing stem volume model of Larix kaempferi species of South Korea which was developed by the Korea Forest Research Institute and with a simple volume model that was developed with fitting dataset in this study. The compatible model provided accurate prediction of the total stem volume when compared to the existing stem volume model and with a simple volume model. It is concluded that the compatible taper and stem volume equations are more convenient to use and therefore it is recommended to be applied in the Larix kaempferi species of South Korea.展开更多
【目的】基于非参数理论,研究构建大兴安岭兴安落叶松(Larix gmelinii)非参数可加性树干削度方程,并与传统的Max and Burkhart参数削度方程进行对比。【方法】利用树高、胸径、不同高度处直径、不同部位高度等变量及其变形构建非参数可...【目的】基于非参数理论,研究构建大兴安岭兴安落叶松(Larix gmelinii)非参数可加性树干削度方程,并与传统的Max and Burkhart参数削度方程进行对比。【方法】利用树高、胸径、不同高度处直径、不同部位高度等变量及其变形构建非参数可加性削度方程。采用7种光滑样条函数:薄板回归样条函数(TP)、Duchon样条函数(DS)、三次回归样条函数(CR)、P-样条函数(PS)、高斯过程平滑样条函数(GP)、B-样条函数(BS)和局部回归光滑函数(LO),基于R软件mgcv包的Gamm函数对非参数模型进行拟合。【结果】使用相对直径(d/D)作为因变量,胸径的平方(D^2)、树高(H)、相对树高的算术平方根(√h/H)作为自变量,构建兴安落叶松最佳非参数可加性树干削度方程。拟合结果表明:基于CR和LO样条函数的可加性削度方程具有较小的R^2(决定系数)和较大的赤池信息量准则(AIC)值,且CR和LO的残差图重心线略呈中间高、两头低的趋势。其他基于5种光滑样条函数的可加性削度方程表现出相似的拟合结果。可加性模型除了使用LO样条函数外,其他样条函数都优于Max and Burkhart参数削度方程的拟合结果。总体检验结果表明,除了CR样条函数模型外,其他各非参数模型(TP、DS、PS、GP和BS)与拟合结果基本一致,即都优于Max and Burkhart参数削度模型的预测精度。基于树干不同高度直径预测的误差对比表明,除了CR模型外,非参数模型(TP、DS、PS、GP和BS)在大多数树干高度处直径预测的平均误差和绝对平均误差都小于Max and Burkhart参数模型预测值。【结论】非参数模型(TP、DS、PS、GP和BS)在拟合统计量、残差分布图、总体和树干不同高度处直径的预测精度都表现出一致性,并优于林业上通常使用的Max and Burkhart参数削度方程。当模型以预测为目的时,所构建的非参数可加性削度方程可用于大兴安岭兴安落叶松干形和材积预测。展开更多
【目的】基于非线性分位数回归方法构建大兴安岭落叶松(Larix gmelinii)树干削度方程,并分析比较基本模型与不同分位数(τ=0.1、0.2、0.3、0.4、0.5、0.6、0.7、0.8、0.9)模型,利用树干不同高度的上部直径进行矫正分位数组合模型预测精...【目的】基于非线性分位数回归方法构建大兴安岭落叶松(Larix gmelinii)树干削度方程,并分析比较基本模型与不同分位数(τ=0.1、0.2、0.3、0.4、0.5、0.6、0.7、0.8、0.9)模型,利用树干不同高度的上部直径进行矫正分位数组合模型预测精度,为落叶松天然林干形的精准预测提供理论依据。【方法】以大兴安岭壮志林场212株落叶松树干干形数据为研究对象,基于非线性分位数回归方法和Max and Burkhart分段削度方程,利用SAS软件中NLP过程拟合各分位数分段削度方程,把树干相对高20%、30%、40%、50%、60%、70%处的直径以及胸径到树尖的中间位置(50%*)的树干上部直径引入到分段削度方程中进行矫正,并以平均误差(MAB)和相对误差(MPB)为评价指标对削度方程进行对比分析。【结果】Max-Burkhart分段削度方程在9个不同的分位点都可以得到参数估计值,因此分位数回归削度模型可以评价在不同分位数的预测能力。未矫正的分位数(τ=0.5、0.6)模型的预测精度略优于基本模型。准确地选择矫正位置至关重要,与未矫正的基本模型相比,利用树干相对高20%和70%处的直径进行矫正不能提高各分位数组合模型的预测精度,利用树干相对高30%、40%、50%、60%处的直径以及胸径到树尖中间位置的树干上部直径进行矫正的大多数分位数组合(3、5、7、9个分位数组合)模型的预测精度都能得到提高,总体使用矫正位置分位数组合模型的预测精度顺序为40%>50%*>50%>60%>30%>20%>70%。最佳的矫正位置为树干相对高40%处,并以3个分位数的组合(τ=0.3、0.5、0.7)模型预测精度最高,与未矫正的基本模型相比,MAB和MPB均下降13.5%。【结论】在削度方程中引入一个合理的矫正位置可以提高模型的预测精度,其中,最佳矫正位置为树干相对高40%处,最优模型为3个分位数组合(τ=0.3、0.5、0.7)模型。在实际应用中,如果不考虑矫正时,建议采用分位数τ=0.5削度方程的参数估计值。展开更多
基金This study was supported by the National Natural Science Foundation of China(30972363)Special Fund for For-estry-Scientific Research in the Public Interest(201004026)+2 种基金China Postdoctoral Science Foundation(200902362,20100471014)the Fun-damental Research Funds for the Central Universities(DL10CA06)SRF for ROCS,SEM.
文摘Segmented taper equation was selected to model stem profile of Dahurian larch （Larix gmelinii Rupr.）. The data were based on stem analysis of 74 trees from Dailing Forest Bureau in Heilongjiang Province, Northeastern China. Two taper equations with crown ratio and stand basal area were derived from the Max and Burkhart’s （1976） taper equation. Three taper equations were evaluated： （1） the original equation, （2） the original equation with crown ratio, and （3） the original equation with basal area. SAS NLIN and SYSNLIN procedures were used to fit taper equations. Fit statistics and cross-validation were used to evaluate the accuracy and precision of these models. Parameter estimates showed that the original equation with inclusion of crown ratio and basal area variables provided significantly different parameter estimates with lower standard errors. Overall fit statistics indicated that the root mean square error （RMSE） for diameter outside and inside bark decreased respectively by 10% and 7% in the original model with crown ratio and by 12% and 7.2% in the original model with basal area. Cross-validation further confirmed that the original equation with inclusion of crown ratio and basal area variables provided more accurate predictions at the lower section （relative heights, 10%） and upper section （relative heights, 50%） for both outside and inside bark diameters.
基金the Korea Forest Service for funding this research(Project No.S211316L020130)
文摘In this study, compatible taper and stem volume equations were developed for Larix kaempferi species of South Korea. The dataset was split into two groups： 80% of the data were used in model fitting and the remaining 2o% were used for validation. The compatible MB76 equations were used to predict the diameter outside bark to a specific height, the height to a specific diameter and the stem volume of the species. The result of the stem volume analysis was compared with the existing stem volume model of Larix kaempferi species of South Korea which was developed by the Korea Forest Research Institute and with a simple volume model that was developed with fitting dataset in this study. The compatible model provided accurate prediction of the total stem volume when compared to the existing stem volume model and with a simple volume model. It is concluded that the compatible taper and stem volume equations are more convenient to use and therefore it is recommended to be applied in the Larix kaempferi species of South Korea.
文摘【目的】基于非参数理论,研究构建大兴安岭兴安落叶松(Larix gmelinii)非参数可加性树干削度方程,并与传统的Max and Burkhart参数削度方程进行对比。【方法】利用树高、胸径、不同高度处直径、不同部位高度等变量及其变形构建非参数可加性削度方程。采用7种光滑样条函数:薄板回归样条函数(TP)、Duchon样条函数(DS)、三次回归样条函数(CR)、P-样条函数(PS)、高斯过程平滑样条函数(GP)、B-样条函数(BS)和局部回归光滑函数(LO),基于R软件mgcv包的Gamm函数对非参数模型进行拟合。【结果】使用相对直径(d/D)作为因变量,胸径的平方(D^2)、树高(H)、相对树高的算术平方根(√h/H)作为自变量,构建兴安落叶松最佳非参数可加性树干削度方程。拟合结果表明:基于CR和LO样条函数的可加性削度方程具有较小的R^2(决定系数)和较大的赤池信息量准则(AIC)值,且CR和LO的残差图重心线略呈中间高、两头低的趋势。其他基于5种光滑样条函数的可加性削度方程表现出相似的拟合结果。可加性模型除了使用LO样条函数外,其他样条函数都优于Max and Burkhart参数削度方程的拟合结果。总体检验结果表明,除了CR样条函数模型外,其他各非参数模型(TP、DS、PS、GP和BS)与拟合结果基本一致,即都优于Max and Burkhart参数削度模型的预测精度。基于树干不同高度直径预测的误差对比表明,除了CR模型外,非参数模型(TP、DS、PS、GP和BS)在大多数树干高度处直径预测的平均误差和绝对平均误差都小于Max and Burkhart参数模型预测值。【结论】非参数模型(TP、DS、PS、GP和BS)在拟合统计量、残差分布图、总体和树干不同高度处直径的预测精度都表现出一致性,并优于林业上通常使用的Max and Burkhart参数削度方程。当模型以预测为目的时,所构建的非参数可加性削度方程可用于大兴安岭兴安落叶松干形和材积预测。
文摘【目的】基于非线性分位数回归方法构建大兴安岭落叶松(Larix gmelinii)树干削度方程,并分析比较基本模型与不同分位数(τ=0.1、0.2、0.3、0.4、0.5、0.6、0.7、0.8、0.9)模型,利用树干不同高度的上部直径进行矫正分位数组合模型预测精度,为落叶松天然林干形的精准预测提供理论依据。【方法】以大兴安岭壮志林场212株落叶松树干干形数据为研究对象,基于非线性分位数回归方法和Max and Burkhart分段削度方程,利用SAS软件中NLP过程拟合各分位数分段削度方程,把树干相对高20%、30%、40%、50%、60%、70%处的直径以及胸径到树尖的中间位置(50%*)的树干上部直径引入到分段削度方程中进行矫正,并以平均误差(MAB)和相对误差(MPB)为评价指标对削度方程进行对比分析。【结果】Max-Burkhart分段削度方程在9个不同的分位点都可以得到参数估计值,因此分位数回归削度模型可以评价在不同分位数的预测能力。未矫正的分位数(τ=0.5、0.6)模型的预测精度略优于基本模型。准确地选择矫正位置至关重要,与未矫正的基本模型相比,利用树干相对高20%和70%处的直径进行矫正不能提高各分位数组合模型的预测精度,利用树干相对高30%、40%、50%、60%处的直径以及胸径到树尖中间位置的树干上部直径进行矫正的大多数分位数组合(3、5、7、9个分位数组合)模型的预测精度都能得到提高,总体使用矫正位置分位数组合模型的预测精度顺序为40%>50%*>50%>60%>30%>20%>70%。最佳的矫正位置为树干相对高40%处,并以3个分位数的组合(τ=0.3、0.5、0.7)模型预测精度最高,与未矫正的基本模型相比,MAB和MPB均下降13.5%。【结论】在削度方程中引入一个合理的矫正位置可以提高模型的预测精度,其中,最佳矫正位置为树干相对高40%处,最优模型为3个分位数组合(τ=0.3、0.5、0.7)模型。在实际应用中,如果不考虑矫正时,建议采用分位数τ=0.5削度方程的参数估计值。
