Course: GEOG 508/L. GeoAI and Lab (2/1)
Prerequisites: GEOG 306/L or GEOG 690J. Recommended Preparatory: GEOG 408E/L; GEOG 460 or GEOG 690B. Students will learn fundamental concepts and widely used methodologies for GeoAI. The integration of geography, GIS, and artificial intelligence within GeoAI (a subfield of spatial data science) provides novel approaches for addressing a variety of geospatial problems in the natural environment and our human society. All labs will be hands-on using real-world geospatial data to address such GeoAI topics as object detection and extraction using both oblique and orthorectified imagery, point cloud classification for lidar, extraction of location information for geocoding from unstructured text, and object tracking. Students will benefit from assignments exploring a variety of datasets as well as utilizing the department’s local supercomputers for analysis tasks. Students will work predominately with ArcGIS Pro for Deep Learning and ArcGIS API for Python. This course will integrate perspectives from the physical and social sciences to identify and describe what GeoAI is, what kind of questions we can answer using these tools, and how we can apply them to real world data.