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

The third edition explores the evolving landscape of spatial analysis, integrating cutting-edge developments in R, artificial intelligence, and machine learning with spatial perspectives. It addresses the growing importance of big data and location-based analytics across diverse applications from movement tracking to emergency response planning and GeoAI. In response to demands for accessible spatial data visualization and pattern discovery, the book emphasizes techniques for generating actionable spatial information to support decision-making. Each chapter now concludes with a practical 5-minute analytical workbook designed to enhance spatial thinking skills through hands-on examples. New in the Third Edition: Balances core spatial statistics principles with thoroughly updated practicums for comprehensive geographical data analysis. Covers analysis of point, areal, and geostatistical data and the chapter explaining big data, data management, and data mining is methodically updated. Uses R programming for practical exercises and worked out examples throughout the text. Illustrates concepts using real data from social and environmental sciences for applied learning. Offers new practical spatial analysis worktables, laboratory activities, interesting new datasets, incredible insights, and superb graphics for skills development. The third 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 earth sciences.