【摘要】 利用2011年采集的150株西藏天然冷杉数据,采用度量误差联立方程组方法同时进行整体建模和分段建模,分别建立了西藏冷杉一元、二元生物量与材积相容性模型,并分析对比两者拟合效果。结果表明:不论是一元、二元模型,采用整体建模方法都难以准确描述冷杉生物量、材积随胸径变化情况,导致径阶16 cm以下的林木立木材积和生物量估计值均小于实际值,径阶越小,偏差越大,其中4 cm径阶的预估偏差甚至达到了20%~30%;而采用分段建模方法能有效解决上述有偏估计的问题,模型改进效果十分良好,各径阶均无系统偏差;分段建立的地上生物量和立木材积方程,不论一元或二元模型,其预估精度分别达到了93.5%、92.8%以上,一元分段地下生物量方程预估精度也在91.5%以上。更多还原

【Abstract】 Based on the tree volume and biomass data of 150 Abies in Tibet, the compatible tree volume and biomass equations and biomass conversion functions were constructed by using the error-in-variable simultaneous equations and segmented modeling approach,and the fitting effect between the two models were analyzed and compared.The results show that: The whole single-tree equations is very difficult to accurately describe the biomass and tree volume with DBH variation,the whole simulation equations for single-tree tree volume and biomass may result in obvious biased estimation for small young trees(DBH < 16 cm), the prediction deviation reached 20% or even more than 30% in 4 cm diameter grade. But the segmented modeling approach can resolve the problem of systematically biased estimation in small diameter classes for commonly-used tree volume and biomass equations. Through the one or two variable-based segmented equations,both the prediction precision(P) of tree volume and above-ground biomass estimates for the whole data are more than 93.5%, 92.8%,and through the one variables-based segmented equations,the prediction precision(P) of below-ground biomass estimates for the whole data is more than 91.5%.更多还原