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2012 | OriginalPaper | Buchkapitel

10. Hyperspectral Classification

verfasst von : James K. Lein

Erschienen in: Environmental Sensing

Verlag: Springer New York

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Abstract

The detailed spectra defined in a hyperspectral images posses new image processing challenges and exciting opportunities. Unlike its multispectral counterpart, hyperspectral imagery captures a level of spectral resolution that contains unique compositional and structural information about the landscape not available in other forms of remotely sensed imagery. To exploit this source of information, thematic extraction based on hyperspectral data involves isolating spectral features in the image according to their reflectance properties followed by a comparison of these properties to those on known materials. In this chapter, we will review the methods employed to extract thematic information from hyperspectral imagery and examine the algorithms called upon to process image spectra.

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Vorheriges Kapitel Hyperspectral Sensing

Nächstes Kapitel Object-Based Analysis

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Kruse, F. A., Boardman, J. W. and Huntington, J. F. (2003). Comparison of airborne hyperspectral data and EO-1 Hyperion for mineral mapping. IEEE Transactions on Geoscience and Remote Sensing, 41(6), 1388–1400.CrossRef

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Mundt, J., Streutker, D. and Glenn, N. (2007) Partial Unmixing of Hyperspectral Imagery, Theory and Methods, Proceedings of the American Society of Photogrammetry and Remote Sensing, Tampa, Florida, 46–57.

Mitchell, J. and Glenn, N. (2009) Subpixel Abundance Estimates’ in Mixture-tuned Matched Filtering Classifications of leafy spurge (Euphorbia esula L.) International Journal of Remote Sensing, 30, 6099–6119.CrossRef

Pu, R., Gong, P., Michishita, R. and Sasagawa, T. (2008) Spectral Mixture Analysis for mapping Abundance of Urban Surface Components from the Terra/ASTER Data, Remote Sensing of Environment, 112, 939–954.CrossRef

Rogge, D., Rivard, B., Zhang, J., Sanchez, A., Harris, J. and Feng, J. (2007) Integration of spatial-spectral information for the improved extraction of endmembers Remote Sensing of Environment, 110, 287–303

Schwarz, I. and Staenz, K. (2001) Adaptive Threshold for Spectral Matching of Hyperspectral Data, Canadian Journal of Remote Sensing, 27, 216–224.

Van Der Meer, F. Vasquez-Torres, M. and Van Dyke, P. (1997) Spectral Characterization of Ophiolite Lithologies in the Troodos Ophiolite Complex of Cyprus and its Potential in Prospecting for Massive Sulphide Deposits, International Journal of Remote Sensing, 18, 1245–1257.CrossRef

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Van der Meer, F. (2004) Analysis of spectral absorption features in hyperspectral imagery. JAG: International Journal of Applied Earth Observation and Geoinformation, 5(1), 55–68.

Van der Meer, F. (2006) The effectiveness of spectral similarity measures for the analysis of hyperspectral imagery International Journal of Applied Earth Observations and Geoinformation, 8, 3–17

Willams, P., Hunt, A. and Raymond, E. (2002) Estimation of leafy spurge cover from hyperspectral imagery using mixture tuned matched filtering Remote Sensing of Environment, 82, 446–456.

Titel: Hyperspectral Classification
verfasst von: James K. Lein
Verlag: Springer New York
Buch: Environmental Sensing
Print ISBN: 978-1-4614-0142-1

Electronic ISBN: 978-1-4614-0143-8

Copyright-Jahr: 2012
DOI: https://doi.org/10.1007/978-1-4614-0143-8_10

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