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

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, , and
DOI: 10.1109/IGARSS.2011.6049370

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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.

Additional Publication Details

Publication type:
Conference Paper
Publication Subtype:
Conference Paper
Title:
Mapping the distribution of materials in hyperspectral data using the USGS Material Identification and Characterization Algorithm (MICA)
ISBN:
9781457710056
DOI:
10.1109/IGARSS.2011.6049370
Year Published:
2011
Language:
English
Larger Work Title:
International Geoscience and Remote Sensing Symposium (IGARSS)
First page:
1569
Last page:
1572
Conference Title:
2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011
Conference Location:
Vancouver, BC
Conference Date:
24 July 2011 through 29 July 2011