This book builds on the previous book by the same authors, An Introduction to R for Spatial Analysis and Mapping, to consider Spatial Data (ie the location attached to data), issues of inference, linking Big Data, Geography / GIS / Mapping and Spatial Analytics. A 'learning by doing' text book, it covers important theoretical issues and helps to develop practical skills in the reader for addressing these.

The critical algorithms used in GIS are notoriously difficult to both teach and understand. This book address the problem by combining rigorous formal language with example case studies and student exercises.