From election results over housing prices to air pollution measurements, most data can be located on a map and can thus be considered geodata. This course covers the basics of geospatial analysis and its application in real-world data science problems with a focus on public policy-related topics. We will start with the basics of geospatial data, such as the fundamental data models vector and raster, typical data formats, and (open) data sources. R is introduced as a tool to edit, analyze, and visualize geodata and we will delve into spatial data operations as well as different techniques for spatial statistics that will provide the tools to accomplish geodata-based use cases. In summary, this course will enable the students to use tools for handling geodata, extract insights through suitable operations and spatial statistics methods, and create powerful visualizations with maps.
