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

By: , , and 
https://doi.org/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.

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
Publisher Institute of Electrical and Electronic Engineers
Description 4 p.
Larger Work Type Conference Paper
Larger Work Subtype Conference Paper
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 July 24-29, 2011
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