The main objective of this chapter is to present a comprehensive data fusion and machine learning algorithm applied to a fused multispectral image toward appropriate feature extraction, adaptive classifier selection, content-based mapping, interpretation, and environmental decision analyses. The remote sensing techniques to be emphasized in this chapter include:

contemporary data fusion technology that is applied to multispectral remote sensing images

intelligent feature extraction methods such as regular, deep, and fast learning methods for intelligent feature extraction empowering better environmental decision analyses

An illustrative example is also presented stepwise for demonstration for water quality monitoring in Lake Nicaragua, Central America.