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  • Book Overview & Buying Learning R for Geospatial Analysis
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Learning R for Geospatial Analysis

Learning R for Geospatial Analysis

By : Michael Dorman
3.9 (7)
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Learning R for Geospatial Analysis

Learning R for Geospatial Analysis

3.9 (7)
By: Michael Dorman

Overview of this book

This book is intended for anyone who wants to learn how to efficiently analyze geospatial data with R, including GIS analysts, researchers, educators, and students who work with spatial data and who are interested in expanding their capabilities through programming. The book assumes familiarity with the basic geographic information concepts (such as spatial coordinates), but no prior experience with R and/or programming is required. By focusing on R exclusively, you will not need to depend on any external software—a working installation of R is all that is necessary to begin.
Table of Contents (13 chapters)
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10
A. External Datasets Used in Examples
11
B. Cited References
12
Index

Chapter 5. Working with Points, Lines, and Polygons

In this chapter, we will cover the basic usage of the second major type of spatial data—vector layers (points, lines, and polygons). In GIS terminology, these data are sometimes referred to as vectors, but we will use the term vector layers to distinguish them from vectors in R (see Chapter 2, Working with Vectors and Time Series). We will review the architecture of the vector layer classes defined in the sp package. Examples of the most common operations involving vector layers will then be presented using the sp, rgdal, and rgeos packages.

In this chapter, we'll cover the following topics:

  • Classes for spatial vector layers (points, lines, and polygons) in the sp package
  • Creating point layers by geocoding
  • Reading and writing vector layer files
  • Exploring the properties of vector layers
  • Accessing and modifying attribute tables
  • Reprojecting vector layers
  • Calculating derived geometrical properties (for example, polygon area...
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Tech Concepts
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Programming languages
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Learning R for Geospatial Analysis
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