Can I read Advanced mapping of environmental data : geostatistics, machine learning, and Bayesian maximum entropy on EtoBox?

Advanced mapping of environmental data : geostatistics, machine learning, and Bayesian maximum entropy by Kanevski, Mikhail (editor) is a nonfiction available to read on EtoBox.

What is Advanced mapping of environmental data : geostatistics, machine learning, and Bayesian maximum entropy about?

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.Content: Chapter 1 Advanced Mapping of Environmental Data: Introduction (pages 1–17): M. Kanevski Chapter 2 Environmental Monitoring Network Characterization and Clustering (pages 19–46): D. Tuia and M. Kanevski Chapter 3 Geostatistics: Spatial Predictions and Simulations (pages 47–94): E. Savelieva, V. Demyanov and M. Maignan Chapter 4 Spatial Data Analysis and Mapping Using Machine Learning Algorithms (pages 95–148): F. Ratle, A. Pozdnoukhov, V. Demyanov, V. Timonin and E. Savelieva Chapter 5 Advanced Mapping of Environmental Spatial Data: Case Studies (pages 149–246): L. Foresti, A. Pozdnoukhov, M. Kanevski, V. Timonin, E. Savelieva, C. Kaiser, R. Tapia and R. Purves Chapter 6 Bayesian Maximum Entropy — BME (page

Who reads Advanced mapping of environmental data : geostatistics, machine learning, and Bayesian maximum entropy?

Author

Kanevski, Mikhail (editor)

Publisher

Wiley-ISTE

Published

2008

Language

EN

ISBN

9781118623268

Category

nonfiction

Subjects

Science, Mathematics, Social_sciences

Updated

2026-03-24