An Introduction to R for Spatial Analysis and Mapping (Spatial Analytics and GIS)

This is a new edition of the accessible and student-friendly ′how to′ for anyone using R for the first time, for use in spatial statistical analysis, geocomputation and digital mapping. The authors, once again, take readers from ‘zero to hero’, updating the now standard text to further enable practical R applications in GIS, spatial analyses, spatial statistics, web-scraping and more.

Revised and updated, each chapter includes:

• example data and commands to explore hands-on;
• scripts and coding to exemplify specific functionality;
• self-contained exercises for students to work through;
• embedded code within the descriptive text.

The new edition includes detailed discussion of new and emerging packages within R like sf, ggplot, tmap, making it the go to introduction for all researchers collecting and using data with location attached. This is the introduction to the use of R for spatial statistical analysis, geocomputation, and GIS for all researchers - regardless of discipline - collecting and using data with location attached.

• R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
• Geocomputation with R (Chapman & Hall/CRC The R Series)
• Applied Spatial Data Analysis with R (Use R!)
• An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
• Practical Statistics for Data Scientists: 50 Essential Concepts
• Spatial Statistics and Geostatistics: Theory and Applications for Geographic Information Science and Technology (SAGE Advances in Geographic Information Science and Technology Series)
• Urban Analytics (Spatial Analytics and GIS)
• Epidemics: Models and Data using R (Use R!)
• ggplot2: Elegant Graphics for Data Analysis (Use R!)
• Spatial Point Patterns: Methodology and Applications with R (Chapman & Hall/CRC Interdisciplinary Statistics)