Applied Spatial Data Analysis with R

  • Roger S. Bivand
  • Edzer Pebesma
  • Virgilio Gómez-Rubio
Part of the Use R! book series (USE R, volume 10)

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Roger S. Bivand, Edzer Pebesma, Virgilio Gómez-Rubio
    Pages 1-16
  3. Handling Spatial Data in R

    1. Front Matter
      Pages 17-20
    2. Roger S. Bivand, Edzer Pebesma, Virgilio Gómez-Rubio
      Pages 21-57
    3. Roger S. Bivand, Edzer Pebesma, Virgilio Gómez-Rubio
      Pages 59-82
    4. Roger S. Bivand, Edzer Pebesma, Virgilio Gómez-Rubio
      Pages 83-125
    5. Roger S. Bivand, Edzer Pebesma, Virgilio Gómez-Rubio
      Pages 127-150
    6. Roger S. Bivand, Edzer Pebesma, Virgilio Gómez-Rubio
      Pages 151-166
  4. Analysing Spatial Data

    1. Front Matter
      Pages 167-171
    2. Roger S. Bivand, Edzer Pebesma, Virgilio Gómez-Rubio
      Pages 173-211
    3. Roger S. Bivand, Edzer Pebesma, Virgilio Gómez-Rubio
      Pages 213-261
    4. Roger S. Bivand, Edzer Pebesma, Virgilio Gómez-Rubio
      Pages 263-318
    5. Roger S. Bivand, Edzer Pebesma, Virgilio Gómez-Rubio
      Pages 319-361
  5. Back Matter
    Pages 363-405

About this book

Introduction

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.

Keywords

R disease mapping geostatistics spatial data spatial objects spatio temporal data

Authors and affiliations

  • Roger S. Bivand
    • 1
  • Edzer Pebesma
    • 2
  • Virgilio Gómez-Rubio
    • 3
  1. 1.and Business AdministrationNorwegian School of EconomicsBergenNorway
  2. 2.Westfälische Wilhelms-UniversitätMuensterGermany
  3. 3.Department of MathematicsUniversidad de Castilla-La ManchaAlbaceteSpain

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-7618-4
  • Copyright Information Springer Science+Business Media New York 2013
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4614-7617-7
  • Online ISBN 978-1-4614-7618-4
  • About this book