Overview
- Addresses the needs of researchers and students using R to analyze spatial data across a range of disciplines and professions
- Co-authored by a group involved in the Comprehensive R Archive Network
- Second edition includes color figures and is fully revised
- Includes supplementary material: sn.pub/extras
Part of the book series: Use R! (USE R, volume 10)
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Table of contents (10 chapters)
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Front Matter
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Handling Spatial Data in R
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Front Matter
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Analysing Spatial Data
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Front Matter
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Back Matter
Keywords
About this book
Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS and the handling of spatio-temporal data. The second part showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics, areal data analysis and disease mapping. The coverage of methods of spatial data analysis ranges from standard techniques to new developments, and the examples used are largely taken from the spatial statistics literature. All the examples can be run using R contributed packages available from the CRAN website, with code and additional data sets from the book's own website. Compared to the first edition, the second edition covers the more systematic approach towards handling spatial data in R, as well as a number of important and widely used CRAN packages that have appeared since the first edition.
This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data. It will also be of interest to spatial data analysts who do not use R, but who are interested in practical aspects of implementing software for spatial data analysis. It is a suitable companion book for introductory spatial statistics courses and for applied methods courses in a wide range of subjects using spatial data, including human and physical geography, geographical information science and geoinformatics, the environmental sciences, ecology, public health and disease control, economics, publicadministration and political science.
The book has a website where complete code examples, data sets, and other support material may be found: http://www.asdar-book.org.
The authors have taken part in writing and maintaining software for spatial data handling and analysis with R in concert since 2003.
Reviews
“The book’s tone and technical focus … suits well its intended audience: advanced or intermediate users of R wanting to improve their spatial analysis skills. … this book is the authoritative resource on R’s spatial capabilities. I heartily recommend ASDAR to all existing R users interested in spatial data and adventurous R beginners with a strong grounding in GIS.” (Robin Lovelace, Applied Spatial Analysis and Policy, Vol. 8, 2015)
Authors and Affiliations
About the authors
Roger Bivand is Professor of Geography in the Department of Economics at the Norwegian School of Economics, Bergen, Norway. Edzer Pebesma is Professor of Geoinformatics at Westfälische Wilhelms-Universität, Münster, Germany. Virgilio Gómez-Rubio is Associate Professor in the Department of Mathematics at Universidad de Castilla-La Mancha, Albacete, Spain
Bibliographic Information
Book Title: Applied Spatial Data Analysis with R
Authors: Roger S. Bivand, Edzer Pebesma, Virgilio Gómez-Rubio
Series Title: Use R!
DOI: https://doi.org/10.1007/978-1-4614-7618-4
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media New York 2013
Softcover ISBN: 978-1-4614-7617-7Published: 21 June 2013
eBook ISBN: 978-1-4614-7618-4Published: 21 June 2013
Series ISSN: 2197-5736
Series E-ISSN: 2197-5744
Edition Number: 2
Number of Pages: XVIII, 405
Number of Illustrations: 32 b/w illustrations, 89 illustrations in colour
Topics: Statistics for Life Sciences, Medicine, Health Sciences, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Statistics, general, Monitoring/Environmental Analysis, Geography, general