Spatial Big Data Science

Lieferzeit: Lieferbar innerhalb 14 Tagen

139,09 

Classification Techniques for Earth Observation Imagery

ISBN: 3319601946
ISBN 13: 9783319601946
Autor: Jiang, Zhe/Shekhar, Shashi
Verlag: Springer Verlag GmbH
Umfang: xv, 131 S., 10 s/w Illustr., 27 farbige Illustr., 131 p. 37 illus., 27 illus. in color.
Erscheinungsdatum: 21.07.2017
Auflage: 1/2017
Produktform: Gebunden/Hardback
Einband: Gebunden

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 ScalesIncludes supplementary material: sn.pub/extras

Artikelnummer: 2354277 Kategorie:

Beschreibung

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.

Herstellerkennzeichnung:


Springer Verlag GmbH
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E-Mail: juergen.hartmann@springer.com

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