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Study of Mineral Mapping Techniques using Airborne Hyperspectral Data: Exploring the potential of AVIRIS-NG for Mineral Identification - Softcover
Synopsis
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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About the Author
Ronak 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 Institute of Remote Sensing, ISRO and Faculty of Geo-Information Science & Earth Observation (ITC), University of Twente, Netherlands.
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- PublisherLAP LAMBERT Academic Publishing
- Publication date2018
- ISBN 10 6137344266
- ISBN 13 9786137344262
- BindingPaperback
- LanguageEnglish
- Number of pages72
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Study of Mineral Mapping Techniques using Airborne Hyperspectral Data: Exploring the potential of AVIRIS-NG for Mineral Identification
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LAP LAMBERT Academic Publishing, 2018
ISBN 10: 6137344266
ISBN 13: 9786137344262
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Softcover
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Study of Mineral Mapping Techniques using Airborne Hyperspectral Data
Published by
LAP LAMBERT Academic Publishing Feb 2018, 2018
ISBN 10: 6137344266
ISBN 13: 9786137344262
New
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Taschenbuch. Condition: 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. Seller Inventory # 9786137344262
Quantity: 2 available
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Study of Mineral Mapping Techniques using Airborne Hyperspectral Data: Exploring the potential of AVIRIS-NG for Mineral Identification
Published by
LAP LAMBERT Academic Publishing, 2018
ISBN 10: 6137344266
ISBN 13: 9786137344262
New
Softcover
Seller: Majestic Books, Hounslow, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. Print on Demand. Seller Inventory # 401681534
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Study of Mineral Mapping Techniques using Airborne Hyperspectral Data : Exploring the potential of AVIRIS-NG for Mineral Identification
Published by
LAP LAMBERT Academic Publishing, 2018
ISBN 10: 6137344266
ISBN 13: 9786137344262
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: 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. Seller Inventory # 9786137344262
Quantity: 1 available
Stock Image
Study of Mineral Mapping Techniques using Airborne Hyperspectral Data: Exploring the potential of AVIRIS-NG for Mineral Identification
Published by
LAP LAMBERT Academic Publishing, 2018
ISBN 10: 6137344266
ISBN 13: 9786137344262
New
Softcover
Seller: Biblios, Frankfurt am main, HESSE, Germany
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Condition: New. PRINT ON DEMAND. Seller Inventory # 18394695595
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Study of Mineral Mapping Techniques using Airborne Hyperspectral Data
Published by
LAP LAMBERT Academic Publishing, 2018
ISBN 10: 6137344266
ISBN 13: 9786137344262
New
Softcover
Seller: moluna, Greven, Germany
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Condition: 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. Seller Inventory # 385845198
Quantity: Over 20 available