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Learning R for Geospatial Analysis

You're reading from   Learning R for Geospatial Analysis Leverage the power of R to elegantly manage crucial geospatial analysis tasks

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Product type Paperback
Published in Dec 2014
Publisher Packt
ISBN-13 9781783984367
Length 364 pages
Edition 1st Edition
Languages
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Author (1):
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Michael Dorman Michael Dorman
Author Profile Icon Michael Dorman
Michael Dorman
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Table of Contents (13) Chapters Close

Preface 1. The R Environment FREE CHAPTER 2. Working with Vectors and Time Series 3. Working with Tables 4. Working with Rasters 5. Working with Points, Lines, and Polygons 6. Modifying Rasters and Analyzing Raster Time Series 7. Combining Vector and Raster Datasets 8. Spatial Interpolation of Point Data 9. Advanced Visualization of Spatial Data A. External Datasets Used in Examples
B. Cited References
Index

Summary

In this chapter, we covered the basics of using R. At this point, you should have R installed and you should be able to write and execute several basic commands from the command line or from the text editor of your preference. The concepts of classes and objects were also introduced, which are both important for the rest of the topics that you will learn in this book. We are now ready to proceed to more complex data structures and operations used in spatial data analysis.

The next chapter will be devoted to vectors, the basic data structures in R. Then, we will introduce more complex data structures to represent nonspatial data in Chapter 3, Working with Tables, and spatial data in Chapter 4, Working with Rasters, and Chapter 5, Working with Points, Lines, and Polygons.

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Learning R for Geospatial Analysis
Published in: Dec 2014
Publisher: Packt
ISBN-13: 9781783984367
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