Ebook: Applied Spatial Data Analysis with R
- Tags: Statistics for Life Sciences Medicine Health Sciences, Statistics for Engineering Physics Computer Science Chemistry and Earth Sciences, Statistics general, Environmental Monitoring/Analysis, Quantitative Geography
- Series: Use R! 10
- Year: 2013
- Publisher: Springer-Verlag New York
- Edition: 2
- Language: English
- pdf
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.
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.
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.
Content:
Front Matter....Pages i-xviii
Front Matter....Pages 17-20
Classes for Spatial Data in R ....Pages 21-57
Visualising Spatial Data....Pages 59-82
Spatial Data Import and Export....Pages 83-125
Further Methods for Handling Spatial Data....Pages 127-150
Spatio-Temporal Data....Pages 151-166
Front Matter....Pages 167-171
Spatial Point Pattern Analysis....Pages 173-211
Interpolation and Geostatistics....Pages 213-261
Modelling Areal Data....Pages 263-318
Disease Mapping....Pages 319-361
Hello World: Introducing Spatial Data....Pages 1-16
Back Matter....Pages 363-405
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.
Content:
Front Matter....Pages i-xviii
Front Matter....Pages 17-20
Classes for Spatial Data in R ....Pages 21-57
Visualising Spatial Data....Pages 59-82
Spatial Data Import and Export....Pages 83-125
Further Methods for Handling Spatial Data....Pages 127-150
Spatio-Temporal Data....Pages 151-166
Front Matter....Pages 167-171
Spatial Point Pattern Analysis....Pages 173-211
Interpolation and Geostatistics....Pages 213-261
Modelling Areal Data....Pages 263-318
Disease Mapping....Pages 319-361
Hello World: Introducing Spatial Data....Pages 1-16
Back Matter....Pages 363-405
....