基于线性光谱混合模型的混合像元分解研究——以合肥市为例

利用Landsat ETM+数据,在水体掩膜的基础上,采用线性光谱混合模型(Liner Spectral Mixture Model,LSMM)进行混合像元分解,得到合肥市高反射率地物、低反射率地物、植被和土壤四种端元的丰度图像以及RMS误差分量图像.应用线性光谱混合模型研究城市地表组分组成,端元(End-member)选取是模型成败的关键.通过分别采用手动选取端元和利用纯像元指数(PPI)法选取端元两种方法,从定性角度对比两种方法得到的结果,结果表明在本研究区内手动选取的端元比PPI选取的端元模型拟合精度更高,能够得到更高精度的分量图像.

The Unmixing Study Based on Linear Spectral Mixture Model —A case study in Hefei

Based on the ETM+ data and water mask,this paper used Linear Spectral Mixture model(LSMM) for Spectral Un-mixing,and the abundance images of the four end-members,the high Albedo,the low Albedo,vegetation and soil and RMS error image in Hefei were obtained.For the study of the urban surface components of the composition based on Linear Spectral Mixture model,the choosing of end-member is the key to success.By using the manual selection method and Purity Pixel Index(PPI) method respectively,this paper compared the results of the two methods from the qualitative point of view.The RMS showed that the manual selection method is better than the PPI method in this study area.It could gain the weight image with more precision than the PPI method.