Based on the biomass data of 150 spruce sampling trees,by using conventional regression methods and dummy variable modeling approach,one variable and two or three variables biomass models were established for the total aboveground biomass and the biomass of components for spruce in Heilongjiang and Jilin provinces.The results showed that the total aboveground biomass models had the highest prediction accuracy(96% or more)and the leaf biomass models had the lowest prediction accuracy which still reached more than 87%.The prediction of other models reached more than 91% and the total relative error was controlled within ±5%.The prediction accuracy and the determination coefficient of biomass models were improved with the increase of the explanatory variables.After the introduction of the dummy variable,the prediction accuracy and the determination coefficient was improved meanwhile the standard error and the total relative error was reduced for one variable and two or three variables biomass models.Dummy variable can improve the prediction effect of the model.
YANG Ying
,
RAN Qixiang
,
CHEN Xinyun
,
OU Qiangxin
. Research on Dummy Variable in Aboveground Biomass Models for Spruce[J]. Forest and Grassland Resources Research, 2015
, 0(6)
: 71
-76
.
DOI: 10.13466/j.cnki.lyzygl.2015.06.014
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