Seller: SpringBooks, Berlin, Germany
First Edition
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Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
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Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Seller: Books Puddle, New York, NY, U.S.A.
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Seller: Revaluation Books, Exeter, United Kingdom
Paperback. Condition: Brand New. reprint edition. 131 pages. 9.25x6.10x0.34 inches. In Stock.
Published by Springer International Publishing AG, CH, 2017
ISBN 10: 3319601946 ISBN 13: 9783319601946
Language: English
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Hardback. Condition: New. 1st ed. 2017. Emerging Spatial Big Data (SBD) has transformative potential in solving many grand societal challenges such as water resource management, food security, disaster response, and transportation. However, significant computational challenges exist in analyzing SBD due to the unique spatial characteristics including spatial autocorrelation, anisotropy, heterogeneity, multiple scales and resolutions which is illustrated in this book.This book also discusses current techniques for, spatial big data science with a particular focus on classification techniques for earth observation imagery big data. Specifically, the authors introduce several recent spatial classification techniques, such as spatial decision trees and spatial ensemble learning. Several potential future research directions are also discussed. This book targets an interdisciplinary audience including computer scientists, practitioners and researchers working in the field of data mining, big data, as well as domain scientists working in earth science (e.g., hydrology, disaster), public safety and public health. Advanced level students in computer science will also find this book useful as a reference.
Published by Springer-Verlag New York Inc, 2017
ISBN 10: 3319601946 ISBN 13: 9783319601946
Language: English
Seller: Revaluation Books, Exeter, United Kingdom
Hardcover. Condition: Brand New. 131 pages. 9.25x6.25x0.50 inches. In Stock.
Published by Springer, Berlin, Springer International Publishing, Springer, 2017
ISBN 10: 3319601946 ISBN 13: 9783319601946
Language: English
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Emerging Spatial Big Data (SBD) has transformative potential in solving many grand societal challenges such as water resource management, food security, disaster response, and transportation. However, significant computational challenges exist in analyzing SBD due to the unique spatial characteristics including spatial autocorrelation, anisotropy, heterogeneity, multiple scales and resolutions which is illustrated in this book.This book also discusses current techniques for, spatial big data science with a particular focus on classification techniques for earth observation imagery big data. Specifically, the authors introduce several recent spatial classification techniques, such as spatial decision trees and spatial ensemble learning. Several potential future research directions are also discussed. This book targets an interdisciplinary audience including computer scientists, practitioners and researchers working in the field of data mining, big data, as well as domain scientists working in earth science (e.g., hydrology, disaster), public safety and public health. Advanced level students in computer science will also find this book useful as a reference.
Seller: Books Puddle, New York, NY, U.S.A.
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Seller: Mispah books, Redhill, SURRE, United Kingdom
Paperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Published by Springer International Publishing AG, CH, 2017
ISBN 10: 3319601946 ISBN 13: 9783319601946
Language: English
Seller: Rarewaves.com UK, London, United Kingdom
US$ 208.89
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Add to basketHardback. Condition: New. 1st ed. 2017. Emerging Spatial Big Data (SBD) has transformative potential in solving many grand societal challenges such as water resource management, food security, disaster response, and transportation. However, significant computational challenges exist in analyzing SBD due to the unique spatial characteristics including spatial autocorrelation, anisotropy, heterogeneity, multiple scales and resolutions which is illustrated in this book.This book also discusses current techniques for, spatial big data science with a particular focus on classification techniques for earth observation imagery big data. Specifically, the authors introduce several recent spatial classification techniques, such as spatial decision trees and spatial ensemble learning. Several potential future research directions are also discussed. This book targets an interdisciplinary audience including computer scientists, practitioners and researchers working in the field of data mining, big data, as well as domain scientists working in earth science (e.g., hydrology, disaster), public safety and public health. Advanced level students in computer science will also find this book useful as a reference.
Published by Springer, Berlin, Springer International Publishing, Springer Aug 2018, 2018
ISBN 10: 3319868020 ISBN 13: 9783319868028
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Emerging Spatial Big Data (SBD) has transformative potential in solving many grand societal challenges such as water resource management, food security, disaster response, and transportation. However, significant computational challenges exist in analyzing SBD due to the unique spatial characteristics including spatial autocorrelation, anisotropy, heterogeneity, multiple scales and resolutions which is illustrated in this book.This book also discusses current techniques for, spatial big data science with a particular focus on classification techniques for earth observation imagery big data. Specifically, the authors introduce several recent spatial classification techniques, such as spatial decision trees and spatial ensemble learning. Several potential future research directions are also discussed. This book targets an interdisciplinary audience including computer scientists, practitioners and researchers working in the field of data mining, big data, as well as domain scientists working in earth science (e.g., hydrology, disaster), public safety and public health. Advanced level students in computer science will also find this book useful as a reference. 131 pp. Englisch.
Published by Springer, Berlin, Springer International Publishing, Springer Jul 2017, 2017
ISBN 10: 3319601946 ISBN 13: 9783319601946
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Emerging Spatial Big Data (SBD) has transformative potential in solving many grand societal challenges such as water resource management, food security, disaster response, and transportation. However, significant computational challenges exist in analyzing SBD due to the unique spatial characteristics including spatial autocorrelation, anisotropy, heterogeneity, multiple scales and resolutions which is illustrated in this book.This book also discusses current techniques for, spatial big data science with a particular focus on classification techniques for earth observation imagery big data. Specifically, the authors introduce several recent spatial classification techniques, such as spatial decision trees and spatial ensemble learning. Several potential future research directions are also discussed. This book targets an interdisciplinary audience including computer scientists, practitioners and researchers working in the field of data mining, big data, as well as domain scientists working in earth science (e.g., hydrology, disaster), public safety and public health. Advanced level students in computer science will also find this book useful as a reference. 131 pp. Englisch.
Published by Springer International Publishing, 2018
ISBN 10: 3319868020 ISBN 13: 9783319868028
Language: English
Seller: moluna, Greven, Germany
Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Introduces four unique properties related to the nature of spatial data that must be accounted for in any data analysisCovers Spatial AutocorrelationDiscusses Spatial Dependency in Multiple Spatial ScalesEmerging Spatial Big Data.
Published by Springer International Publishing, 2017
ISBN 10: 3319601946 ISBN 13: 9783319601946
Language: English
Seller: moluna, Greven, Germany
Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Introduces four unique properties related to the nature of spatial data that must be accounted for in any data analysisCovers Spatial AutocorrelationDiscusses Spatial Dependency in Multiple Spatial ScalesEmerging Spatial Big Data.
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Seller: Biblios, Frankfurt am main, HESSE, Germany
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Seller: Majestic Books, Hounslow, United Kingdom
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Seller: Biblios, Frankfurt am main, HESSE, Germany
Condition: New. PRINT ON DEMAND.