Geographical Data Science and Spatial Data Analysis
An Introduction in R
- Lex Comber - University of Leeds, UK
- Chris Brunsdon - National University of Ireland, Maynooth, Ireland
Spatial Analytics and GIS
Whilst other books describe different flavours of Data Analytics in R and other programming languages, there are none that consider Spatial Data (i.e. the location attached to data), or that consider issues of inference, linking Big Data, Geography, GIS, Mapping and Spatial Analytics.
This is a ‘learning by doing’ textbook, building on the previous book by the same authors, An Introduction to R for Spatial Analysis and Mapping. It details the theoretical issues in analyses of Big Spatial Data and developing practical skills in the reader for addressing these with confidence.
The online resources include:
· Code Library of up-to-date R scripts from each chapter to help you feel confident using R.
· Data Library with datasets to practice your skills on real-world data.
· Journal Articles on important topics, such as critical spatial data science, to deepen your understanding.
This book is a must-read for anyone wishing to use R to analyse large spatial datasets. It is suitable for teachers and learners at all levels, building knowledge from the ground-up using relevant, real-world examples and easy to follow instructions.
Written by two renowned international experts, this is an excellent introductory book for students, teachers and researchers alike who have experience of using R and who want to further develop their skills in big data spatial science.