Mapping the distribution of materials in hyperspectral data using the USGS Material Identification and Characterization Algorithm (MICA)

Kokaly, R. F.; King, T. V. V.; Hoefen, T. M.

Abstract:

Identifying materials by measuring and analyzing their reflectance spectra has been an important method in analytical chemistry for decades. Airborne and space-based imaging spectrometers allow scientists to detect materials and map their distributions across the landscape. With new satellite-borne hyperspectral sensors planned for the future, for example, HYSPIRI (HYPerspectral InfraRed Imager), robust methods are needed to fully exploit the information content of hyperspectral remote sensing data. A method of identifying and mapping materials using spectral-feature based analysis of reflectance data in an expert-system framework called MICA (Material Identification and Characterization Algorithm) is described in this paper. The core concepts and calculations of MICA are presented. A MICA command file has been developed and applied to map minerals in the full-country coverage of the 2007 Afghanistan HyMap hyperspectral data. ?? 2011 IEEE.

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Conference Paper

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70036150

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Kokaly, R. F.; King, T. V. V.; Hoefen, T. M.

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1572

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English

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International Geoscience and Remote Sensing Symposium (IGARSS)

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Mapping the distribution of materials in hyperspectral data using the USGS Material Identification and Characterization Algorithm (MICA); 2011; Conference Paper; International Geoscience and Remote Sensing Symposium (IGARSS); Kokaly, R. F.; King, T. V. V.; Hoefen, T. M.