Method of Normalized Multiple Endmember Spectral Mixture Analysis and Its Application
基于光谱归一化的变组分光谱混合分析(NMESMA)方法及其应用

For the low and medium spatial resolution remote sensing images,the issues of mixed pixels are particularly prominent,which does not only influence the accuracy of image classification,but also greatly hinder the development of quantitative remote sensing of land surface.Therefore,mixed pixels unmixing of remote sensing images and quantitative extraction of land coverage information have attracted more interest in recent years.In this paper,focused on quantitative extraction of land cover information,a method of integration of the Normalized Spectral Mixture Analysis (NSMA) and Multiple Endmember Spectral Mixture Analysis (MESMA) have been proposed to extract the quantitative information of vegetation,soil and impervious surface using the medium-resolution remote sensing image (Landsat TM),based on Vegetation-Impervious Surface-Soil (V—I—S) Model.Comparative analysis indicated the accuracy of the unmixing by using the Normalized Multiple Endmember Spectral Mixture Analysis (NMESMA) method is higher than that of the conventional fixed endmember of spectral mixture analysis.NMESMA can solve the mixed pixel problem of the high spectral heterogeneity in urban landscape effectively.Therefore,the proposed methodology can be used to extract urban land surface information effectively,and to analyze the urban ecological environment change.