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Spatial Big Data Science: Classification Techniques for Earth Observation Imagery - Couverture souple
Synopsis
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
ISBN 10 : 3319868020
ISBN 13 : 9783319868028
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : 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. N° de réf. du vendeur 9783319868028
Quantité disponible : 2 disponible(s)
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Spatial Big Data Science
Edité par
Springer International Publishing, 2018
ISBN 10 : 3319868020
ISBN 13 : 9783319868028
Neuf
Kartoniert / Broschiert
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Kartoniert / Broschiert. Etat : 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. N° de réf. du vendeur 458627094
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Spatial Big Data Science: Classification Techniques for Earth Observation Imagery
Vendeur : Books Puddle, New York, NY, Etats-Unis
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Etat : New. N° de réf. du vendeur 26376468119
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Spatial Big Data Science: Classification Techniques for Earth Observation Imagery
impression à la demandeVendeur : Majestic Books, Hounslow, Royaume-Uni
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Etat : New. Print on Demand. N° de réf. du vendeur 369610056
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Spatial Big Data Science: Classification Techniques for Earth Observation Imagery
impression à la demandeVendeur : Biblios, Frankfurt am main, HESSE, Allemagne
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Etat : New. PRINT ON DEMAND. N° de réf. du vendeur 18376468125
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Spatial Big Data Science: Classification Techniques for Earth Observation Imagery
Vendeur : Revaluation Books, Exeter, Royaume-Uni
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Paperback. Etat : Brand New. reprint edition. 131 pages. 9.25x6.10x0.34 inches. In Stock. N° de réf. du vendeur 3319868020
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Spatial Big Data Science : Classification Techniques for Earth Observation Imagery
Edité par
Springer, Berlin, Springer International Publishing, Springer, 2018
ISBN 10 : 3319868020
ISBN 13 : 9783319868028
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : 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. N° de réf. du vendeur 9783319868028
Quantité disponible : 2 disponible(s)
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Spatial Big Data Science: Classification Techniques for Earth Observation Imagery
Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
Évaluation du vendeur 4 sur 5 étoiles
Paperback. Etat : New. New. book. N° de réf. du vendeur ERICA80033198680206
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