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14 - Hyper- and Multispectral Visible and Near-Infrared Imaging Analysis

from Part III - Analysis Methods

Published online by Cambridge University Press:  15 November 2019

By
William H. Farrand ,
Erzsébet Merényi  and
Mario C. Parente
Edited by
Janice L. Bishop ,
James F. Bell III  and
Jeffrey E. Moersch
Janice L. Bishop
Affiliation:
SETI Institute, California
James F. Bell III
Affiliation:
Arizona State University
Jeffrey E. Moersch
Affiliation:
University of Tennessee, Knoxville
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Summary

Multi- and hyperspectral sensors in the visible to short-wave infrared (0.4–2.5 μm) are sensitive to spectral features caused by electronic charge transfer and transition metal crystal field band as well as molecular overtone absorptions. This chapter reviews several processing techniques used to map materials on planetary surfaces based on their reflectance spectra in this spectral region. Techniques that are reviewed include spectral matching in the form of spectral angle and spectral information divergence, linear and nonlinear spectral unmixing, partial unmixing/matched filters, and machine learning approaches in the form of self-organizing maps, neural network classification, and support vector machines.

Keywords

mineralogyspectroscopyhyperspectralmultispectralspectral unmixingmachine learningmatched filterspectral end-membersintrinsic dimensionalityPancam
Type
Chapter
Information
Remote Compositional Analysis
Techniques for Understanding Spectroscopy, Mineralogy, and Geochemistry of Planetary Surfaces
 , pp. 307 - 323
Publisher: Cambridge University Press
Print publication year: 2019

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