In the Big Data era, space and place can help contextualize the Amazon of data. This
Spring, ’15 graduate course offers some useful tools, including GIS (Geographic information Systems) for data analysis, Open to seniors if they get permission from the instructor.
GEOG 526: Geospatial Data Analysis
Spring Quarter 2015
Monday 2:30 to 5:30
sln 14665
Course Overview
This course provides a conceptual and practical introduction to spatial data analysis and geographic information systems in geographic research. The goal is to provide a practical understanding of the application of spatial data analysis to geographic problem solving. Emphasis is placed on the appropriate selection of methods to analyze geographic data, procedures for research design, and interpretation of research findings. Students will gain practical experience through assignments that require the application of spatial data analysis to specific geographic research questions using statistical and GIS software. Topics include fundamental spatial data analysis such as buffers, overlay and distance operations, descriptive and inferential spatial statistics, spatial pattern analysis and spatial autocorrelation, global and local spatial measures, regression analysis and geographically weighted regression, kriging and interpolation, and agent-based models. No prior GIS experience required.
Open to seniors with permission of instructor.
Professor Suzanne Davies Withers
Department of Geography
Smith 012
Phone: 206-616-9064