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Study of Mineral Mapping Techniques using Airborne Hyperspectral Data: Exploring the potential of AVIRIS-NG for Mineral Identification - Softcover

 
9786137344262: Study of Mineral Mapping Techniques using Airborne Hyperspectral Data: Exploring the potential of AVIRIS-NG for Mineral Identification

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Geology is a science deal with the minerals and rocks majorly. Hyperspectral data is used in the geology domain for mineral identification and mapping. Because of its high spatial as well as high spectral resolution. The main objective is to identify the different minerals on the earth crust using different mineral mapping algorithms such as Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF) and Mixture Tuned Matched Filtering (MTMF) using AVIRIS-NG data and conclude the better algorithm for mineral mapping. For identification of a different kind of minerals, spectral analysis is performed. Imagery pixel spectrum is matched with predefined or unique (pure) spectra for the mineral detection. SAM algorithm mainly computes the angle between the pixel spectra and reference spectra. The SFF compares the continuum removed spectrum of the image with the continuum removed reference spectrum and operated the least square fitting. MTMF is a combination of two different algorithms and works on the MNF transformed data for estimation of abundance of minerals along with the identification of the false positive. MTMF perform well and gives better results for mineral mapping.

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Ronak Jain
ISBN 10: 6137344266 ISBN 13: 9786137344262
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Geology is a science deal with the minerals and rocks majorly. Hyperspectral data is used in the geology domain for mineral identification and mapping. Because of its high spatial as well as high spectral resolution. The main objective is to identify the different minerals on the earth crust using different mineral mapping algorithms such as Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF) and Mixture Tuned Matched Filtering (MTMF) using AVIRIS-NG data and conclude the better algorithm for mineral mapping. For identification of a different kind of minerals, spectral analysis is performed. Imagery pixel spectrum is matched with predefined or unique (pure) spectra for the mineral detection. SAM algorithm mainly computes the angle between the pixel spectra and reference spectra. The SFF compares the continuum removed spectrum of the image with the continuum removed reference spectrum and operated the least square fitting. MTMF is a combination of two different algorithms and works on the MNF transformed data for estimation of abundance of minerals along with the identification of the false positive. MTMF perform well and gives better results for mineral mapping. 72 pp. Englisch. Bestandsnummer des Verkäufers 9786137344262

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ISBN 10: 6137344266 ISBN 13: 9786137344262
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Jain RonakRonak Jain is presently pursuing PhD from Mohanlal Sukhadia University, Rajasthan. He received his M.Sc.(2015) & M.Sc. Tech.(2016) in Geology from MLSU and Post-Graduate Diploma in Geoinformatics (2017) from Indian Institut. Bestandsnummer des Verkäufers 385845198

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Jain, Ronak/ U Sharma, Richa/ KUMAR, ANIL
ISBN 10: 6137344266 ISBN 13: 9786137344262
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Paperback. Zustand: Brand New. 72 pages. 8.66x5.91x0.17 inches. In Stock. Bestandsnummer des Verkäufers zk6137344266

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Taschenbuch. Zustand: Neu. Neuware -Geology is a science deal with the minerals and rocks majorly. Hyperspectral data is used in the geology domain for mineral identification and mapping. Because of its high spatial as well as high spectral resolution. The main objective is to identify the different minerals on the earth crust using different mineral mapping algorithms such as Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF) and Mixture Tuned Matched Filtering (MTMF) using AVIRIS-NG data and conclude the better algorithm for mineral mapping. For identification of a different kind of minerals, spectral analysis is performed. Imagery pixel spectrum is matched with predefined or unique (pure) spectra for the mineral detection. SAM algorithm mainly computes the angle between the pixel spectra and reference spectra. The SFF compares the continuum removed spectrum of the image with the continuum removed reference spectrum and operated the least square fitting. MTMF is a combination of two different algorithms and works on the MNF transformed data for estimation of abundance of minerals along with the identification of the false positive. MTMF perform well and gives better results for mineral mapping.Books on Demand GmbH, Überseering 33, 22297 Hamburg 72 pp. Englisch. Bestandsnummer des Verkäufers 9786137344262

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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Geology is a science deal with the minerals and rocks majorly. Hyperspectral data is used in the geology domain for mineral identification and mapping. Because of its high spatial as well as high spectral resolution. The main objective is to identify the different minerals on the earth crust using different mineral mapping algorithms such as Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF) and Mixture Tuned Matched Filtering (MTMF) using AVIRIS-NG data and conclude the better algorithm for mineral mapping. For identification of a different kind of minerals, spectral analysis is performed. Imagery pixel spectrum is matched with predefined or unique (pure) spectra for the mineral detection. SAM algorithm mainly computes the angle between the pixel spectra and reference spectra. The SFF compares the continuum removed spectrum of the image with the continuum removed reference spectrum and operated the least square fitting. MTMF is a combination of two different algorithms and works on the MNF transformed data for estimation of abundance of minerals along with the identification of the false positive. MTMF perform well and gives better results for mineral mapping. Bestandsnummer des Verkäufers 9786137344262

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