用哑变量方法构建东北落叶松和栎类分段地上生物量模型

Using dummy variable approach to construct segmented aboveground biomass models for larch and oak in northeastern China

采用单一的非线性方程拟合生物量模型常会导致小径阶林木的估计有偏。以东北地区落叶松和栎类的地上生物量数据为例,提出采用哑变量方法改进立木生物量估计模型的预估效果,并建立了2个树种的一元和二元立木生物量模型。结果表明:哑变量方法能解决小径阶林木的偏估问题,同时能在一定程度上改善对整个模型的预估效果;所建模型能同时适用于胸径<5 cm的幼树和胸径≥5 cm的林木;二元生物量模型的平均预估误差均在5%以下,可应用于东北地区各类森林资源清查中落叶松和栎类的生物量估计。

Using single nonlinear equation with constant parameters to simulate tree biomass may result in obvious biased estimation for small diameter class saplings. Based on the aboveground biomass data of larch and oak in northeastern China, an approach with dummy variable was presented which could improve the estimation of tree biomass, and one-and two-variable tree biomass models for the two tree species were constructed. The results showed that： 1） the approach not only was effective in solving the problem of biased estimation for small saplings, but also improved the prediction results of biomass model for all sample trees to some extent; 2） the constructed models were suitable for both saplings with diameter at breast height （DBH） less than 5 cm and trees with DBH more than 5 cm for biomass estimation of larch and oak trees in all kinds of forest inventory in northeastern China, and through the two-variable biomass models, the mean predicting error was all less than 5%.