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Courses - Fall 2019
Geographical Sciences Department Site
Selected Topics in Geography; Models and Methods for Spatial Data Science
Credits: 3
Grad Meth: Reg, Aud
Introduces a spatial data science (SDS) framework for uncovering spatial patterns and understanding spatial processes, whether they are generated by humans, the physical environment, or a combination thereof.This course first covers some basic principles of popular computational toolsfor SDS and then surveys a variety of geographic conceptual models and quantitative methods from the traditions of spatial analysis and spatialstatistics. A strong emphasis is placed on the practical deployment of these models and methods and their interpretation. Students will developexpertise in common design decisions, analytical intuition, and limitations of SDS through real world examples and applied projects, as well as build their repertoire of Python programming skills for obtaining, processing, and analyzing spatial data.