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.
