Benthic habitats are the different bottom environments as defined by distinct physical, geochemical, and biological characteristics. Remote sensing is increasingly being used to map and monitor the complex dynamics associated with estuarine and nearshore benthic habitats. Advantages of remote sensing technology include both the qualitative benefits derived from a visual overview, and more importantly, the quantitative abilities for systematic assessment and monitoring. Advancements in instrument capabilities and analysis methods are continuing to expand the accuracy and level of effectiveness of the resulting data products. Hyperspectral sensors in particular are rapidly emerging as a more complete solution, especially for the analysis of subsurface shallow aquatic systems. The spectral detail offered by hyperspectral instruments facilitates significant improvements in the capacity to differentiate and classify benthic habitats. This paper reviews two techniques for mapping shallow coastal ecosystems that both combine the retrieval of water optical properties with a linear unmixing model to obtain classifications of the seafloor. Example output using AVIRIS hyperspectral imagery of Kaneohe Bay, Hawaii is employed to demonstrate the application potential of the two approaches and compare their respective results.