Introduction to R for Geospatial Data

By Anne Fouilloux, butterflyskip, Chris Prener, Claudia Engel, David Mawdsley, Erin Becker, François Michonneau, Ido Bar, Jeffrey Oliver, Juan Fung, Katrin Leinweber, Kevin Weitemier, Kok Ben Toh, Lachlan Deer, Marieke Frassl, Matt Clark, Miles McBain, Naupaka Zimmerman, Paula Andrea Martinez, Preethy Nair, Raniere Silva, Rayna Harris, Richard McCosh, Vicken Hillis.
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Abstract

The goal of this lesson is to provide an introduction to R for learners working with geospatial data. It is intended as a pre-requisite for the R for Raster and Vector Data lesson for learners who have no prior experience using R. This lesson can be taught in approximately 4 hours and covers the following topics: Working with R in the RStudio GUI Project management and file organization Importing data into R Introduction to R’s core data types and data structures Manipulation of data frames (tabular data) in R Introduction to visualization Writing data to a file The the R for Raster and Vector Data lesson provides a more in-depth introduction to visualization (focusing on geospatial data), and working with data structures unique to geospatial data.

Link to resource: https://datacarpentry.org/r-intro-geospatial/

Type of resources: Module

Education level(s): Graduate / Professional

Primary user(s): student, teacher

Subject area(s): Computer Science, Information Science, Measurement and Data

Language(s): English