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

Using the matrix and array classes


A raster is essentially a matrix with spatial reference information. Similarly, a multiband raster is essentially a three-dimensional array with spatial reference information. Therefore, before proceeding with spatial rasters, we will cover some prerequisite material on working with these (simpler) objects in this section—matrices and arrays. Moreover, as we shall see later, matrices and arrays are common data structures with many uses in R.

Representing two-dimensional data with a matrix

A matrix object is a two-dimensional collection of elements, all of the same type (as opposed to a data.frame object; see the previous chapter), where the number of elements in all rows (and, naturally, all columns) is identical. Matrix objects have many uses in R. For example, certain functions take matrices as their arguments (such as the focal function to filter rasters) or return matrices (such as the extract function to extract raster values; we will meet both these...