Catalog Description: A spatial analytic approach to digital mapping and GIS. Given that recording the geolocation of scientific, business and social data is now routine, the question of what we can learn from the spatial aspect of data arises. This class looks at challenges in analyzing spatial data, particularly scale and spatial dependence. Various methods are considered such as hotspot detection, interpolation, and map overlay. The emphasis throughout is hands on and practical rather than theoretical.
Prerequisites: Basic computer literacy, e.g., Excel or similar, some previous GIS or mapping useful, but not required
Fall and/or Spring: 15 weeks - 2 hours of lecture and 4 hours of laboratory per week
Grading Basis: Letter
Final Exam Status: Final exam required