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Proceedings Paper

Long-wavelength infrared hyperspectral data "mining" at Cuprite, NV
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Paper Abstract

In recent years long-wavelength infrared (LWIR) hyperspectral imagery has significantly improved in quality and become much more widely available, sparking interest in a variety of applications involving remote sensing of surface composition. This in turn has motivated the development and study of LWIR-focused algorithms for atmospheric retrieval, temperature-emissivity separation (TES) and material detection and identification. In this paper we evaluate some LWIR algorithms for atmospheric retrieval, TES, endmember-finding and rare material detection for their utility in characterizing mineral composition in SEBASS hyperspectral imagery taken near Cuprite, NV. Atmospheric correction results using the In-Scene Atmospheric Correction (ISAC) method are compared with those from the first-principles, MODTRAN©-based FLAASH-IR method. Covariance-whitened endmember-finding methods are observed to be sensitive to image artifacts. However, with clean data and all-natural terrain they can automatically locate and distinguish many minor mineral components, with especially high sensitivity to varieties of calcite. Not surprisingly, the major scene materials, including silicates, are best located using unwhitened techniques. Minerals that we identified in the data include calcite, quartz, alunite and (tentatively) kaolinite.

Paper Details

Date Published: 1 September 2015
PDF: 7 pages
Proc. SPIE 9611, Imaging Spectrometry XX, 961107 (1 September 2015); doi: 10.1117/12.2187061
Show Author Affiliations
Robert Sundberg, Spectral Sciences, Inc. (United States)
Steven Adler-Golden, Spectral Sciences, Inc. (United States)
Patrick Conforti, Spectral Sciences, Inc. (United States)

Published in SPIE Proceedings Vol. 9611:
Imaging Spectrometry XX
Thomas S. Pagano; John F. Silny, Editor(s)

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