Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Remote sensing
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Spatial Big Data Science - Classification Techniques for Earth Observation Imagery (Hardcover, 1st ed. 2017)
Loot Price: R3,848
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Spatial Big Data Science - Classification Techniques for Earth Observation Imagery (Hardcover, 1st ed. 2017)
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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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