Spatial Analysis with R: Statistics, Visualization, and Computational Methods

In the five years since the publication of the first edition of Spatial Statistics, Visualization, and Computational Methods , many new developments have taken shape regarding the implementation of new tools and methods for spatial analysis with R. The use and growth of artificial intelligence, machine learning and deep learning algorithms with a spatial perspective, and the interdisciplinary use of spatial analysis are all covered in this second edition along with traditional statistical methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis. Spatial Analysis with Statistics, Visualization, and Computational Methods, Second Edition , provides a balance between concepts and practicums of spatial statistics with a comprehensive coverage of the most important approaches to understand spatial data, analyze spatial relationships and patterns, and predict spatial processes.New in the Second Includes new practical exercises and worked out examples using RPresents a wide range of hands-on spatial analysis work tables and lab exercisesAll chapters are revised and include new illustrations of different concepts using data from environmental and social sciencesExpanded material on spatiotemporal methods, visual analytics methods, data science, and computational methodsExplains big data, data management, and data miningThis second edition of an established textbook, with new datasets, insights, excellent illustrations, and numerous examples with R, is perfect for senior undergraduate and first year graduate students in geography and the geosciences.