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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
EUR 9,70 per la spedizione da Germania a Italia
Destinazione, tempi e costiDa: moluna, Greven, Germania
Kartoniert / Broschiert. Condizione: 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. Codice articolo 458627094
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: 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. Codice articolo 9783319868028
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Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: 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. Codice articolo 9783319868028
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Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. Codice articolo 26376468119
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Da: Revaluation Books, Exeter, Regno Unito
Paperback. Condizione: Brand New. reprint edition. 131 pages. 9.25x6.10x0.34 inches. In Stock. Codice articolo 3319868020
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Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. Print on Demand. Codice articolo 369610056
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Da: Biblios, Frankfurt am main, HESSE, Germania
Condizione: New. PRINT ON DEMAND. Codice articolo 18376468125
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Da: Mispah books, Redhill, SURRE, Regno Unito
Paperback. Condizione: New. New. book. Codice articolo ERICA80033198680206
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