Overview
Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The R programming language is a great platform for exploring these data and integrating them into your research.
Geospatial Data in R, part I:Getting started with spatial data objects
Part one of this multi-part workshop series will introduce basic methods and packages for working with geospatial data in R. Participants will learn how to import and export spatial data and store them as spatial objects. We will explore and compare several methods for mapping the data including the base plot function and the ggmap and tmap libraries. We will review coordinate reference systems and methods for reading, defining and transforming these. Note, this workshop focuses on vector spatial data.
Geospatial Data in R, part 2: Geoprocessing and analysis
Part two of this multi-part workshop series will dive deeper into data driven mapping in R, using color palettes and data classification to communicate information with maps. We will also introduce basic methods for processing spatial data, which are the building blocks of common spatial analysis workflows. Note, this workshop focuses on vector spatial data.
Geospatial Data in R, part 3: Working with raster data
Part three of this multi-part workshop series will introduce tools and approaches for working with raster data. Raster data are used to represent geographic phenomena that are present and measurable anywhere in a study area, like elevation, temperature, rainfall, land cover, soil type, etc. These data are a valuable resource for social scientists, planners, and engineers, as well as natural scientists. This workshop will introduce basic raster concepts and methods for working with raster data in R. Participants will learn how to import and store raster data as spatial objects. We will explore methods for plotting rasters and manipulating raster data values. Basic methods of raster and raster-vector spatial data analysis will also be introduced. Additionally, the workshop will review coordinate reference systems and methods for reading, defining and transforming these with raster data.
Knowledge Requirements: D-Lab’s R Fundamentals series or equivalent knowledge. Basic knowledge of geospatial data is expected. Knowledge of ggplot helpful.
NOTE: D-Lab workshops normally start 10 minutes after the scheduled start time (“Berkeley Time”). We recommend you log on at the start time to join the waiting room where hosts will message you further information.
