Geospatial data are an important component of social science and humanities data visualization and analysis. The R programming language is a great platform for exploring these data and integrating them into a research project.
Geospatial Data in R Part 2: Geoprocessing and Analysis
Part two of this two part workshop series will introduce methods for processing and tranforming spatial data stored as sp spatial objects. Students will learn about coordinate reference systems and map projects and how these impact spatial analysis. We will explore different geoprocessing operations and spatial queries that are the building blocks of spatial analysis.
Knowledge Requirements: R experience equivalent to the D-Lab R Fundamentals workshop series is required to follow along with the tutorial. Part I of this series is a prerequisite for following along with the material.
Technology Requirements: Bring a laptop with R, RStudio and the following R packages installed: sp, rgdal, rgeos, ggplot2, ggmap, leafletR, RColorBrewer, classInt, and tmap. Knownledge of geospatial data is helpful but not required.
