10.1 Geocomputation with R
Robin Lovelace, Jakub Nowosad, Jannes Muenchow
This is the online home of Geocomputation with R, a book on geographic data analysis, visualization and modeling.
10.2 Spatial Data Science
Edzer Pebesma, Roger Bivand
This book introduces and explains the concepts underlying spatial data: points, lines, polygons, rasters, coverages, geometry attributes, data cubes, reference systems, as well as higher-level concepts including how attributes relate to geometries and how this affects analysis.
10.3 Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny
This book describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R. After a detailed introduction of geospatial data, the book shows how to develop Bayesian hierarchical models for disease mapping and apply computational approaches such as the integrated nested Laplace approximation (INLA) and the stochastic partial differential equation (SPDE) to analyze areal and geostatistical data.