This book combines geostatistics and global mapping systems to present
an up-to-the-minute study of environmental data. Featuring numerous
case studies, the reference covers model dependent (geostatistics)
and data driven (machine learning algorithms) analysis techniques
such as risk mapping, conditional stochastic simulations, descriptions
of spatial uncertainty and variability, artificial neural networks
(ANN) for spatial data, Bayesian maximum entropy (BME), and more.