An Introduction to R for Spatial Analysis and Mapping (Third Edition) - Brunsdon, Chris

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Résumé :
The accessible and student-friendly 'how to' for anyone using R for the first time to analyse location-based data....

Biographie:
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....

Sommaire:
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
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