John Schott


This paper is available on the publisher's website (additional fees may apply) at: The spectral remote sensing field has evolved over several decades from color imagery to multispectral imagery to today’s imaging spectrometer data. The goal of this evolution was to acquire increasingly detailed information about material types on the earth’s surface. The expectation was that adding more spectral bands would add increasing material separability and increasing information about the condition (e.g. water quality or vegetation health) of a given material. This paper will address the extent to which these expectations are being realized (i.e. are 100 bands dramatically better than 3 bands). In addition, the algorithms that have been developed by the remote sensing community for understanding (i.e. unmixing) mixtures of materials based on spectral content are briefly introduced. Finally, the potential to utilize imaging spectroscopy in other applications areas is discussed.

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Department, Program, or Center

Chester F. Carlson Center for Imaging Science (COS)


RIT – Main Campus