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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

Topography-related calculations with elevation data


Deriving topography-related variables from a DEM is a central task in terrain analysis. Many functions and algorithms have been developed for this purpose, and different GIS software packages include different sets of such tools. The raster package currently provides several basic terrain analysis functions (of which three examples will be shown in this section).

Note

A variety of terrain analysis (and other) algorithms are available in R through interfacing with open source GIS software, such as SAGA GIS (using the RSAGA package) and GRASS GIS (using the spgrass6 package). To use these, you will require to download and install the (freely available) respective software, but the subject is beyond the scope of the present book, which focuses on standalone R functionality.

Slope and aspect calculation

Calculation of topographic slope and aspect is among the most basic DEM analysis procedures. These two variables have many uses in their own right...

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