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

Chapter 7. Combining Vector and Raster Datasets

Generating new insight by overlaying several layers of spatial information, one on top of the other, constitutes one of the main concepts of spatial data analysis, as we have already seen in the previous chapters. So far, however, we have only used operations involving either rasters alone or vector layers alone, but not a combination of both. Although the two types of spatial layers have their characteristic uses (such as rasters for DEMs and vector layers for administrative borders), combining them in a single analysis is often desired. As we shall see, this is a less straightforward task, characterized by specific procedures and decisions.

In this chapter, we are going to explore the interplay between vector and raster layers, and the way it is implemented in the raster package. The way rasters and vector layers can be interchanged and queried, one according to the other, will be demonstrated through examples.

Note

In this chapter, we are going...