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

Exploring vector layer properties and subsetting


This section is going to be devoted to the examination of spatial vector layer properties, and to subsetting them based on their attribute tables. Some of the presented procedures will be analogous to those presented for rasters in the previous chapter (for example, plotting and querying CRS information), while others are generally relevant only to vector layers (for example, calculating areas and creating subsets according to the attribute table). As will quickly become apparent, many operations involving attribute tables of vector layers are conveniently analogous to operations on data.frame objects.

Examining vector layer properties

The summary function produces a useful textual summary of the properties of a vector layer, including its class, bounding box coordinates, CRS, and attribute table column types. For example, using summary on airports produces the following textual output:

> summary(airports)
Object of class SpatialPointsDataFrame...