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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

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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Learning R for Geospatial Analysis
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