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利用野外实测68个样地的森林生物量数据、TM影像的单波段数据、植被指数数据以及地形数据在内的18个自变量建立了川西亚高山针叶林生物量的回归估算模型。研究表明:在建立的一元线性回归、一元非线性回归和多元线性回归生物量模型中,以多元线性回归模型在森林生物量估算中有较好的精度。
The regression model of the biomass of subalpine coniferous forest in western Sichuan was established by using 18 measured variables, including forest biomass data of 68 plots in field, single-band data of TM images, vegetation index data and topographic data. The results show that the multivariate linear regression model has good accuracy in the estimation of forest biomass in the established linear models of univariate linear regression, univariate linear regression and multivariate linear regression.