[zevross] BigDataFr recommends: #datascientist Map and analyze raster data in R

BigDataFr recommends: Map and analyze raster data in R

« The amount of spatial analysis functionality in R has increased dramatically since the first release of R. In a previous post, for example, we showed that the number of spatial-related packages has increased to 131 since the first R release. This means, of course, that more and more of your spatial-related workflow can be conducted without leaving R.

In this post we show some simple (and not-so-simple) examples of how to work with raster data in R with a focus on the raster package. This post also makes extensive use of the “new” R workflow with the packages dplyr, magrittr, tidyr and ggplot2.

1. Load the libraries

We will load the key libraries. If you’re unfamiliar with dplyr and tidyr, which we use for data processing, you can check out our previous post on the topic. Be sure to load tidyr before raster, otherwise the extract tool from the raster library will be masked. »
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Author: hkitson@zevross.com
Source: zevross.com

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