森林生物量与印度卫星数据及地学因子的相关性分析

以2006年印度卫星数据（IRS—P6）为信息源，提取4个波段值、6种波段比值、4种植被指数，利用DEM提取海拔、坡度、坡向3个地学因子，共17个变量，选取5种线性及非线性方程，对高黎贡山常绿阔叶林地面样地生物量与17个遥感及地学因子进行相关性分析．结果表明：IRS—P6的B2，B3，B5波段以及海拔与生物量达到极显著相关水平．波段比值、植被指数、坡度、坡向与生物量的相关性较差，只有少量因子达到显著相关水平．通过变量筛选及回归方程选择，IRS—P6数据可用于较大尺度森林生物量的估测．

Correlation Analysis of Forest Biomass and IRS - P6 Satellite Data Variants and Topographic Features

The correlations among forest biomass of the evergreen broadleaved forest plots in Mt. Gaoligong National Nature Reserve and 17 variants, including 4 multi - spectral bands of Indian IRS - P6 satellite data collected in 2006, 6 kinds of band ratio,4 kinds of vegetation index, and 3 geographic factors, i. e. , elevation, slope gradient and slope aspect selected by DEM method, were analyzed with 5 types of linear and nonlinear regression equations. The analyses showed： Forest biomass was significantly correlated with B2, B3 and B5 bands of IRS - P6 and elevation factors （P 〈 0.01 ）. Comparatively, the forest biomass was poorly correlated with the band ratio, vegetation indexes, slope gradient and slope aspect, few of the correlations among these variants reached significant level. Data of IRS - P6 could be used for estimation of large scale forest biomass if the variants and equations were rationally selected.