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Spatial Big Data Science : Classification Techniques for Earth Observation Imagery
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Spatial Big Data Science: Classification Techniques for Earth Observation Imagery
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Spatial Big Data Science : Classification Techniques for Earth Observation Imagery
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Spatial Big Data Science : Classification Techniques for Earth Observation Imagery
Published by Springer, Berlin, Springer International Publishing, Springer, 2018
ISBN 10: 3319868020 ISBN 13: 9783319868028
Language: English
£ 124.70
Convert currency£ 11.95 shipping from Germany to United KingdomQuantity: 2 available
Add to basketTaschenbuch. 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.
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Spatial Big Data Science : Classification Techniques for Earth Observation Imagery
Published by Springer, Berlin, Springer International Publishing, Springer, 2017
ISBN 10: 3319601946 ISBN 13: 9783319601946
Language: English
£ 124.70
Convert currency£ 11.95 shipping from Germany to United KingdomQuantity: 2 available
Add to basketBuch. 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.
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£ 131.97
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£ 143.87
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Paperback. Condition: Brand New. reprint edition. 131 pages. 9.25x6.10x0.34 inches. In Stock.
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£ 110.70
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Spatial Big Data Science: Classification Techniques for Earth Observation Imagery
Published by Springer-Verlag New York Inc, 2017
ISBN 10: 3319601946 ISBN 13: 9783319601946
Language: English
Hardcover. Condition: Brand New. 131 pages. 9.25x6.25x0.50 inches. In Stock.
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Paperback. Condition: New. New. book.
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Spatial Big Data Science
Published by Springer International Publishing, 2018
ISBN 10: 3319868020 ISBN 13: 9783319868028
Language: English
£ 105.20
Convert currency£ 21.35 shipping from Germany to United KingdomQuantity: Over 20 available
Add to basketKartoniert / 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.
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Spatial Big Data Science
Published by Springer International Publishing, 2017
ISBN 10: 3319601946 ISBN 13: 9783319601946
Language: English
£ 105.20
Convert currency£ 21.35 shipping from Germany to United KingdomQuantity: Over 20 available
Add to basketGebunden. 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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Spatial Big Data Science
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
Seller rating 5 out of 5 stars
£ 122.38
Convert currency£ 9.40 shipping from Germany to United KingdomQuantity: 2 available
Add to basketTaschenbuch. 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.
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Spatial Big Data Science
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
Seller rating 5 out of 5 stars
£ 122.38
Convert currency£ 9.40 shipping from Germany to United KingdomQuantity: 2 available
Add to basketBuch. 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.
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Condition: New. Print on Demand.
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£ 162.86
Convert currency£ 6.79 shipping from Germany to United KingdomQuantity: 4 available
Add to basketCondition: New. PRINT ON DEMAND.
