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Proceedings Paper

Spectral library generation for hyperspectral archaeological validation
Author(s): Kelly Canham; William Middleton; David Messinger; Nina Raqueno
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Paper Abstract

Fractional abundance maps have been produced from Hyperion hyperspectral data over Oaxaca, Mexico, by applying a new spatially adaptive spectral unmixing algorithm. The goal of this research is to produce land-use maps for aiding archaeologists studying the Zapotec civilization. However, to correlate the fractional abundance maps generated from the HSI image processing, a relationship between the known materials located in Oaxaca, Mexico, and the spectral profiles of these materials must be established. A field campaign during December 2011, (the dry season in Oaxaca) took place for the explicit task of obtaining spectral profiles of the most common materials found in the region. Ground-truth information was collected for three Oaxaca valleys (Tlacolula, Yanhuitlan, and Ycuitla). Common materials and associated regions were recorded and material samples were collected at many of these locations. Laboratory reflectance spectral profiles of the collected material samples are measured after the field campaign using a FieldSpec Pro. Wavelength ranges of the FieldSpec Pro spanned 350-2500nm matching that of the hyperspectral imagery collected from the Hyperion sensor on board the EO-1 satellite. GIS maps of the three valleys in Oaxaca, Mexico, are used to identify where these samples were collected and correspond to the laboratory measured material samples. The spectral library entries obtained correspond to bare soils, senescent agricultural vegetation, senescent natural vegetation, and terra cotta tile.

Paper Details

Date Published: 14 May 2012
PDF: 12 pages
Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 839012 (14 May 2012); doi: 10.1117/12.918676
Show Author Affiliations
Kelly Canham, Rochester Institute of Technology (United States)
William Middleton, Rochester Institute of Technology (United States)
David Messinger, Rochester Institute of Technology (United States)
Nina Raqueno, Rochester Institute of Technology (United States)

Published in SPIE Proceedings Vol. 8390:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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