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Applied Spatial Data Analysis with R (Use R!), by Roger S. Bivand, Edzer Pebesma, Virgilio Gómez-Rubio
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This book first presents R packages, functions, classes and methods for handling spatial data. It then showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics and disease mapping.
- Sales Rank: #308678 in Books
- Published on: 2013-06-21
- Released on: 2013-06-21
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x 1.00" w x 6.10" l, 1.30 pounds
- Binding: Paperback
- 405 pages
Review
“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)
From the Back Cover
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, public administration 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.
About the Author
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
Most helpful customer reviews
23 of 23 people found the following review helpful.
Lots of information, clearly presented.
By E. Eff
This is not a book for a beginner, but is an excellent book for two groups of readers: those who have some background with R and wish to learn about its capabilities for spatial statistics; and those with some background in spatial statistics who wish to learn how to use R. The authors have been the main developers of the spatial statistics packages on R, and therefore know the packages intimately. But the authors also have a deep knowledge of the spatial statistics literature, and I found myself learning something new about these methods in every chapter. Everyone serious about spatial statistics should see what R has to offer. This book is the easiest way to do that.
16 of 17 people found the following review helpful.
The best practial introduction to R spatial
By GeoVizer
The R spatial packages are the leading edge for spatial analysis and spatial statistics. This book, by the primary developers of the R Spatial packages, is the best introduction to the subject that I have seen.
Now, if you are comfortable with it, you can dive an and download R and R spatial and go to town. But if you need some help, this is a good place to start. This would also make a good textbook for a class on spatial analysis.
5 of 5 people found the following review helpful.
Just what is needed
By D. Lamb
This book fills a gap in the Spatial Statistics literature. Most of the treatises are heavy on the math, and I find it difficult to bridge the gap between the formulas and applying them. The modules for R take care of this for you and leave you to interpret the result. This book covers most of these modules and demonstrates how to use them. Really worth getting. There is also the ESRI Guide to GIS Analysis Vol 2, but it is more of an introductory text.
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