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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

Chapter 6. Modifying Rasters and Analyzing Raster Time Series

In this chapter, we will continue with the material presented in Chapter 4, Working with Rasters, moving on to more advanced operations. These involve either the modification of the geometric properties of a raster or direction- and distance-related calculations on rasters; mostly using additional functions in the raster package. Examples related to the analysis of spatio-temporal remote sensing data will be presented in the last section of this chapter, to demonstrate how more complex, custom-made procedures of raster processing can be constructed.

In this chapter, we will use objects that we previously created in Chapter 3, Working with Tables, and Chapter 4, Working with Rasters.

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

  • Modifying the geometry of raster layers
  • Applying focal filters
  • Clumping patches of connected cells
  • Resampling and reprojection of rasters
  • Performing topography-related calculations on elevation...
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