02306nam 2200445Ia 450 991087703630332120200520144314.09780470611463 (e-book)9781848210608 (hbk.)(MiAaPQ)EBC477673(CKB)2550000000005885(EXLCZ)99255000000000588520080408d2008 uy 0engur|n|nnn|||||txtrdacontentcrdamediacrrdacarrierAdvanced mapping of environmental data geostatistics, machine learning, and Bayesian maximum entropy /edited by Mikhail KanevskiLondon ISTE, Ltd. ;Hoboken, NJ J. Wileyc20081 online resource (xiii, 313 p.) illISTE ;v.62Includes bibliographical references and index.Chapter 1. Advanced Mapping of Environmental Data: Introduction -- Chapter 2. Environmental Monitoring Network Characterization and Clustering -- Chapter 3. Geostatistics: Spatial Predictions and Simulations -- Chapter 4. Spatial Data Analysis and Mapping Using Machine Learning Algorithms -- Chapter 5. Advanced Mapping of Environmental Spatial Data: Case Studies -- Chapter 6. Bayesian Maximum Entropy – BME -- Index.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.ISTE.GeologyStatistical methodsMachine learningBayesian statistical decision theoryGeologyStatistical methods.Machine learning.Bayesian statistical decision theory.550.1/519542Kanevski Mikhail1763841MiAaPQMiAaPQMiAaPQ9910877036303321Advanced mapping of environmental data4204475UNINA