In this chapter, you learned some of the most useful methods for advanced visualization of spatial data in R, using the packages ggplot2
, ggmap
, and lattice
. It was shown how these tools can be used to conclude a spatial analysis procedure and create publishable maps and plots of the results, all within the R environment. In this context, it has been noted that not everything can be accomplished in R, and at times we need to migrate to traditional GIS software or graphic editors for interactive customization of the graphic output. Nevertheless, visualization in R is extremely flexible, while at the same time bringing all of the benefits of programming. Once you become more familiar with the techniques presented in this chapter, it is almost inevitable that R will become the primary tool of choice for data visualization. I sincerely hope that after completing this book you feel the same way about geospatial data analysis in R.
Learning R for Geospatial Analysis
By :
Learning R for Geospatial Analysis
By:
Overview of this book
Table of Contents (18 chapters)
Learning R for Geospatial Analysis
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
The R Environment
Working with Vectors and Time Series
Working with Tables
Working with Rasters
Working with Points, Lines, and Polygons
Modifying Rasters and Analyzing Raster Time Series
Combining Vector and Raster Datasets
Spatial Interpolation of Point Data
Advanced Visualization of Spatial Data
External Datasets Used in Examples
Cited References
Index
Customer Reviews