Use of synthetic bands derived from mixing models in the multispectral classification of remote sensing images

An analysis of the use of features derived from class proportions in a pixel for the multispectral classification of reforested areas in Landsat images is performed. Through a linear mixing model, synthetic bands derived from those proportions are obtained either using the constrained or the weighted least squares procedures. The method indicates that the synthetic bands offer an alternative to well-known dimensionality reduction techniques such as principal components or canonical analysis. Furthermore, those bands provide a useful tool for visual interpretation, since they contain information that is related to physical concepts (proportions) more easily assimilated than class spectral signatures.