【摘要】 本文首先对TM影像进行了几何纠正、辐射校正、大气校正;然后根据混合像元的结构特征,利用TM数据从植被指数(NDVI)中采用“等密度模型”和“非密度模型”提取了宜昌南部地区的植被覆盖度。在用“非密度模型”反演植被覆盖度的过程中,叶面积指数(LAI)是一个必要的参数,本文提出了一种改进的借助可见光波段和近红外波段反射值来提取叶面积指数(LAI)的方法。通过和MODIS数据反演结果比较表明:“非密度模型”的估算精度要高于“等密度模型”;利用“等密度模型”和“非密度模型”反演植被覆盖度是可行。更多还原

【Abstract】 In the paper,Geometric、radiometric and atmospheric correction of the images are performed firstly.secondly,According to the sub-pixel structure characteristic, the potential of deriving vegetation fraction from normalized difference vegetation index using the TM data and resorting to“Dense Vegetation Model”and “Nondense Vegetation Model”, is studied in an area in the south of Yichang. During the process of deriving percent vegetation cover using “Nondense Vegetation Model”, Leaf Area Index (LAI) is a necessary parameters, an improved method for deriving LAI from visible and near infrared measurements above a soil background is proposed. We acquire the vegetation fraction of the study area with MODIS data, then compare it to that derivred from TM data, we can detect that the accuracy rate of vegetation fraction using “Nondense Vegetation Model”is higher than that from “Dense Vegetation Model”; the comparision also suggests that the method of using “Dense Vegetation Model”and “Nondense Vegetation Model”to achieve Vegetation fraction is feasible.更多还原