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SPECTRAL IMAGING ANALYSIS MODELS: Remote Sensing Satellites Imagery Data Processing Techniques for Mineral Exploration: A Geo-science Perspective - Softcover
Synopsis
Hyperspectral Imagery combines imaging and spectroscopy in single systems which often include large data sets and require new processing methods. The spatial resolution of most space borne Hyperspectral (HSI) sensors is much coarser than the size of the objects being observed. Therefore the measured spectral signature is a mixture of the signatures of the objects in the field of view (FOV) of the sensor. One of the tedious and time consuming tasks related to hyperspectral data analysis is the identification of library candidates. The high spectral resolution can be effectively used to decompose measured spectra into its constituents by way of spectral unmixing. Spectral Unmixing is the process by which the measured spectrum is decomposed into a collection of constituent spectra (or endmembers), and a set of corresponding fractions (or abundances). Thus spectral unmixing allows us to detect and classify sub-pixel target objects by their contribution to the measured spectral signature. The application area includes Agriculture, Forestry, Geology, Hydrology, Sea ice and Water, Environment, Land cover, Mapping, Ocean and Coastal, Military Operations, Geo-explorations, and Bio-sciences.
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About the Author
He is a Doctorate’ student at Indian Institute of Technology Bombay, Mumbai. He received his graduation and post graduation both in Physics from University of Delhi. He completed his Master of Technology in Engineering Physics. He is a gold medalist recipient in Engineering Physics. His area of specialization includes Hyperspectral Remote Sensing.
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Spectral imaging analysis models
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LAP LAMBERT Academic Publishing Okt 2012, 2012
ISBN 10: 3659250325
ISBN 13: 9783659250323
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Hyperspectral Imagery combines imaging and spectroscopy in single systems which often include large data sets and require new processing methods. The spatial resolution of most space borne Hyperspectral (HSI) sensors is much coarser than the size of the objects being observed. Therefore the measured spectral signature is a mixture of the signatures of the objects in the field of view (FOV) of the sensor. One of the tedious and time consuming tasks related to hyperspectral data analysis is the identification of library candidates. The high spectral resolution can be effectively used to decompose measured spectra into its constituents by way of spectral unmixing. Spectral Unmixing is the process by which the measured spectrum is decomposed into a collection of constituent spectra (or endmembers), and a set of corresponding fractions (or abundances). Thus spectral unmixing allows us to detect and classify sub-pixel target objects by their contribution to the measured spectral signature. The application area includes Agriculture, Forestry, Geology, Hydrology, Sea ice and Water, Environment, Land cover, Mapping, Ocean and Coastal, Military Operations, Geo-explorations, and Bio-sciences. 264 pp. Englisch. Seller Inventory # 9783659250323
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SPECTRAL IMAGING ANALYSIS MODELS
Published by
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659250325
ISBN 13: 9783659250323
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Spectral imaging analysis models
Published by
LAP LAMBERT Academic Publishing Okt 2012, 2012
ISBN 10: 3659250325
ISBN 13: 9783659250323
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Taschenbuch
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Taschenbuch. Condition: Neu. Neuware -Hyperspectral Imagery combines imaging and spectroscopy in single systems which often include large data sets and require new processing methods. The spatial resolution of most space borne Hyperspectral (HSI) sensors is much coarser than the size of the objects being observed. Therefore the measured spectral signature is a mixture of the signatures of the objects in the field of view (FOV) of the sensor. One of the tedious and time consuming tasks related to hyperspectral data analysis is the identification of library candidates. The high spectral resolution can be effectively used to decompose measured spectra into its constituents by way of spectral unmixing. Spectral Unmixing is the process by which the measured spectrum is decomposed into a collection of constituent spectra (or endmembers), and a set of corresponding fractions (or abundances). Thus spectral unmixing allows us to detect and classify sub-pixel target objects by their contribution to the measured spectral signature. The application area includes Agriculture, Forestry, Geology, Hydrology, Sea ice and Water, Environment, Land cover, Mapping, Ocean and Coastal, Military Operations, Geo-explorations, and Bio-sciences.Books on Demand GmbH, Überseering 33, 22297 Hamburg 264 pp. Englisch. Seller Inventory # 9783659250323
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Spectral imaging analysis models : Remote Sensing Satellites Imagery Data Processing Techniques for Mineral Exploration: A Geo-science Perspective
Published by
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659250325
ISBN 13: 9783659250323
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Hyperspectral Imagery combines imaging and spectroscopy in single systems which often include large data sets and require new processing methods. The spatial resolution of most space borne Hyperspectral (HSI) sensors is much coarser than the size of the objects being observed. Therefore the measured spectral signature is a mixture of the signatures of the objects in the field of view (FOV) of the sensor. One of the tedious and time consuming tasks related to hyperspectral data analysis is the identification of library candidates. The high spectral resolution can be effectively used to decompose measured spectra into its constituents by way of spectral unmixing. Spectral Unmixing is the process by which the measured spectrum is decomposed into a collection of constituent spectra (or endmembers), and a set of corresponding fractions (or abundances). Thus spectral unmixing allows us to detect and classify sub-pixel target objects by their contribution to the measured spectral signature. The application area includes Agriculture, Forestry, Geology, Hydrology, Sea ice and Water, Environment, Land cover, Mapping, Ocean and Coastal, Military Operations, Geo-explorations, and Bio-sciences. Seller Inventory # 9783659250323
Quantity: 1 available
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SPECTRAL IMAGING ANALYSIS MODELS: Remote Sensing Satellites Imagery Data Processing Techniques for Mineral Exploration: A Geo-science Perspective
Published by
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659250325
ISBN 13: 9783659250323
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Paperback. Condition: Brand New. 264 pages. 8.66x5.91x0.60 inches. In Stock. Seller Inventory # 3659250325
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