Book description
Leverage the power of R to elegantly manage crucial geospatial analysis tasks
In Detail
R is a simple, effective, and comprehensive programming language and environment that is gaining everincreasing popularity among data analysts.
This book provides you with the necessary skills to successfully carry out complete geospatial data analyses, from data import to presentation of results.
Learning R for Geospatial Analysis is composed of stepbystep tutorials, starting with the language basics before proceeding to cover the main GIS operations and data types. Visualization of spatial data is vital either during the various analysis steps and/or as the final product, and this book shows you how to get the most out of R's visualization capabilities. The book culminates with examples of cuttingedge applications utilizing R's strengths as a statistical and graphical tool.
What You Will Learn
 Make inferences from tables by joining, reshaping, and aggregating
 Familiarize yourself with the R geospatial data analysis ecosystem
 Prepare reproducible, publicationquality plots and maps
 Efficiently process numeric data, characters, and dates
 Reshape tabular data into the necessary form for the specific task at hand
 Write R scripts to automate the handling of raster and vector spatial layers
 Process elevation rasters and time series visualizations of satellite images
 Perform GIS operations such as overlays and spatial queries between layers
 Spatially interpolate meteorological data to produce climate maps
Table of contents

Learning R for Geospatial Analysis
 Table of Contents
 Learning R for Geospatial Analysis
 Credits
 About the Author
 About the Reviewers
 www.PacktPub.com
 Preface
 1. The R Environment
 2. Working with Vectors and Time Series
 3. Working with Tables
 4. Working with Rasters
 5. Working with Points, Lines, and Polygons
 6. Modifying Rasters and Analyzing Raster Time Series
 7. Combining Vector and Raster Datasets
 8. Spatial Interpolation of Point Data
 9. Advanced Visualization of Spatial Data
 A. External Datasets Used in Examples
 B. Cited References
 Index
Product information
 Title: Learning R for Geospatial Analysis
 Author(s):
 Release date: December 2014
 Publisher(s): Packt Publishing
 ISBN: 9781783984367
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