Book Image

Learning R for Geospatial Analysis

By : Michael Dorman
Book Image

Learning R for Geospatial Analysis

By: Michael Dorman

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
External Datasets Used in Examples
Cited References
Index

Summary


In this chapter, we covered the basic operations involved in working with vector layers in R. First, we reviewed the classes used to represent spatial vector layers in R, and explored two ways to bring spatial vector data into R (geocoding and reading from a file). Second, we discussed how to examine and modify the attribute tables of vector layers, how to create subsets of layers according to their attribute tables, and how to join new data to an attribute table (either from a separate table or from another vector layer). Third, the major types of geometry-related operations with vector layers, including the calculation of geometrical properties, evaluation of relations between layers, and the creation of new layers based on the existing ones, were presented.

In the next chapter, we will delve into rasters in more detail, examining geometry-related modification of rasters (such as reprojection), utilizing elevation rasters (such as DEMs), and working with spatio-temporal raster data...