Introduction to Reproducible Geospatial Analysis and Figures in R: A Tutorial Article

Philippe Maesen and Edouard Salingros ()
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Philippe Maesen: BEAGx, Faculty of Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
Edouard Salingros: BEAGx, Faculty of Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium

Data, 2024, vol. 9, issue 4, 1-21

Abstract: The present article is intended to serve an educational purpose for data scientists and students who already have experience with the R language and which to start using it for geospatial analysis and map creation. The basic concepts of raster data, vector data, CRS and datum are first presented along with a basic workflow to conduct reproducible geospatial research in R. Examples of important types of maps (scatter, bubble, choropleth, hexbin and faceted) created from open-source environmental data are illustrated and their practical implementation in R is discussed. Through these examples, essential manipulations on geospatial vector data are demonstrated (reading, transforming CRS, creating geometries from scratch, buffer zones around existing geometries and intersections between geometries).

Keywords: tutorial; R; geospatial data analysis; maps; reproducible research (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2024
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