AI in Spatial Data Science

Catalog description

This course focuses on the scientific and technical challenges that lie at the intersection of spatial data science and artificial intelligence (AI). Geospatial data and geographic visualizations are not readily supported by contemporary AI approaches, but development in this area of GeoAI is rapidly advancing. Spatial reasoning, spatial analysis, and cartographic design are all potentially aided via the use of AI in the near future. Students will engage with key theories, methods, and systems to develop new workflows that enable geospatial problem solving with the support of AI. Students will engage with emerging literature to contextualize and critique ongoing scientific progress towards achieving GeoAI goals, including engagement with ethical considerations related to geospatial extensions of AI. They will also develop customized solutions for AI-supported spatial data science tasks through lab exercises. These labs will allow students the opportunity to create and evaluate AI-supported spatial data science workflows with an emphasis on reproducibility and ethical responsibility. A culminating project in the class will allow students to create a new AI-supported spatial data science solution for a real-world application.