Paper
14 May 2012 Spectral library generation for hyperspectral archaeological validation
Author Affiliations +
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.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kelly Canham, William Middleton, David Messinger, and Nina Raqueno "Spectral library generation for hyperspectral archaeological validation", Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 839012 (14 May 2012); https://doi.org/10.1117/12.918676
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KEYWORDS
Vegetation

Geographic information systems

Sensors

Satellite imaging

Satellites

Digital photography

Global Positioning System

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