9781526428509-1526428504-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)

3.5
ISBN-13: 9781526428509
ISBN-10: 1526428504
Edition: Second
Author: Chris, Brunsdon, Comber, Lex
Publication date: 2019
Publisher: SAGE Publications Ltd
Format: Paperback 336 pages
Category: Geography
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Book details

ISBN-13: 9781526428509
ISBN-10: 1526428504
Edition: Second
Author: Chris, Brunsdon, Comber, Lex
Publication date: 2019
Publisher: SAGE Publications Ltd
Format: Paperback 336 pages
Category: Geography

Summary

Acknowledged authors Chris , Brunsdon , Comber , Lex wrote An Introduction to R for Spatial Analysis and Mapping (Spatial Analytics and GIS) comprising 336 pages back in 2019. Textbook and eTextbook are published under ISBN 1526428504 and 9781526428509. Since then An Introduction to R for Spatial Analysis and Mapping (Spatial Analytics and GIS) textbook received total rating of 3.5 stars and was available to sell back to BooksRun online for the top buyback price of $ 18.03 or rent at the marketplace.

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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