„It gives a good overview, is clearly written, is concise, and includes many references to papers published in the different areas.“ (Zentralblatt MATH, 2011)
Advanced Mapping of Environmental Data
herausgegeben von Mikhail KanevskiThis 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.
