川西亚高山针叶林生物量遥感估算模型研究

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。

Application of Remote Sensing Model in Biomass Estimation of the Subalpine Coniferous Forest

Based on the data on forest biomass collected from 68 sampling plots and single-band TM data, 18 variables were selected to build the estimation regression model to predict the biomass of the sub-alpine coniferous forest in western Sichuan province. In the establishment of the monadic linear regression, the non-linear regression and the multivariate linear regression model of forest biomass,the results showed that multiple linear regression model was more accurate.