Introduction to R for Spatial Analysis and Mapping

Introduction to R for Spatial Analysis and Mapping

Introduction to R for Spatial Analysis and Mapping

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.
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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.
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