9781526428493-1526428490-An Introduction to R for Spatial Analysis and Mapping (Spatial Analytics and GIS)

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

ISBN-13: 9781526428493
ISBN-10: 1526428490
Edition: Second
Author: Lex Comber, Chris Brunsdon
Publication date: 2019
Publisher: SAGE Publications Ltd
Format: Hardcover 336 pages
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Book details

ISBN-13: 9781526428493
ISBN-10: 1526428490
Edition: Second
Author: Lex Comber, Chris Brunsdon
Publication date: 2019
Publisher: SAGE Publications Ltd
Format: Hardcover 336 pages

Summary

An Introduction to R for Spatial Analysis and Mapping (Spatial Analytics and GIS) (ISBN-13: 9781526428493 and ISBN-10: 1526428490), written by authors Lex Comber, Chris Brunsdon, was published by SAGE Publications Ltd in 2019. With an overall rating of 3.8 stars, it's a notable title among other Geography (Earth Sciences) books. You can easily purchase or rent An Introduction to R for Spatial Analysis and Mapping (Spatial Analytics and GIS) (Hardcover) from BooksRun, along with many other new and used Geography books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.62.

Description

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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