An introduction to fundamental techniques for geospatial data science and geoscience using a modern GIS toolkit that includes ArcGIS Online and the programming language R. This site is for Chris Prener’s sections only.
This class introduces both the theoretical and technical skills that constitute the nascent field of geospatial data science. Techniques introduced include map production and cartography, spatial data cleaning and management, and the manipulation of both tabular and spatial data. The course incorporates a wide variety of social, economic, health, urban, meteorological, and environmental data. These data are mapped at a variety of extents, from the City of St. Louis to the St. Louis Metropolian region, Missouri, and the entire United States.
To map these data, we balance an introduction to the industry-standard proprietary ecosystem, ArcGIS, with cutting-edge techniques for working with spatial data in the programming language R
. Data science tools, including Markdown, Git, and GitHub are also introduced.
This course has five intertwined objectives. After completing the course, students will be able to:
R
.R
and ArcGIS Online.R
, Markdown, and other tools.slides, notes, assignment submission
policies, schedule
slots available Wednesdays, 9am to 10am
course repositories
related articles, news, and media
data science in R