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Spatial Big Data Science

Classification Techniques for Earth Observation Imagery

Language EnglishEnglish
Book Paperback
Book Spatial Big Data Science Zhe Jiang
Libristo code: 20094411
Publishers Springer International Publishing AG, August 2018
Emerging Spatial Big Data (SBD) has transformative potential in solving many grand societal challeng... Full description
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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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About the book

Full name Spatial Big Data Science
Language English
Binding Book - Paperback
Date of issue 2018
Number of pages 131
EAN 9783319868028
Libristo code 20094411
Weight 238
Dimensions 156 x 237 x 9
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