Chris Brunsdon, Lex Comber

An Introduction to R for Spatial Analysis and Mapping (eBook, ePUB)

• Format: ePub

Produktbeschreibung

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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Produktdetails

• Verlag: SAGE Publications
• Seitenzahl: 336
• Erscheinungstermin: 31. Dezember 2018
• Englisch
• ISBN-13: 9781526454225
• Artikelnr.: 54825612

Autorenporträt

Chris Brunsdon is Professor of Geocomputation and Director of the National Centre for Geocomputation at the National University of Ireland, Maynooth, having worked previously in the Universities of Newcastle, Glamorgan, Leicester and Liverpool, variously in departments focusing on both geography and computing. He has interests that span both of these disciplines, including spatial statistics, geographical information science, and exploratory spatial data analysis, and in particular the application of these ideas to crime pattern analysis, the modelling of house prices, medical and health geography and the analysis of land use data. He was one of the originators of the technique of geographically weighted regression (GWR).

He has extensive experience of programming in R, going back to the late 1990s, and has developed a number of R packages which are currently available on CRAN, the Comprehensive R Archive Network. He is an advocate of free and open source software, and in particular the use of reproducible research methods, and has contributed to a large number of workshops on the use of R and of GWR in a number of countries, including the UK, Ireland, Japan, Canada, the USA, the Czech Republic and Australia.

When not involved in academic work he enjoys running, collecting clocks and watches, and cooking - the last of these probably cancelling out the benefits of the first.

Inhaltsangabe

Chapter 1: Introduction and Getting Started
Chapter 2: Data and Plots
Chapter 3: Spatial Data Handling in R
Chapter 4: Scripting and Writing Functions in R
Chapter 5: Using R as a GIS
Chapter 6: Point Pattern Analysis Using R
Chapter 7: Spatial Attribute Analysis With R: Point Based Data
Chapter 8: Spatial Attribute Analysis With R: Area Based Data
Chapter 9: Localised Spatial Analysis
Chapter 10: Working with Data from the Internet
Epilogue: Spatial Analysis and R - Review and Prospect