This course enables students who have taken the introductory course (URP 520) to advance their skills in the use of Geographic Information Systems. Several advanced GIS techniques are presented to help students deepen their analytical capabilities using spatial data. Topics to be covered include network analysis (e.g., pipeline flows, waterways, travel routing and costs, facility service areas, and traffic lose; spatial data analysis (e.g., raster modeling, interpolating point data, density analysis, and neighborhood statistics); and an introduction to visualizing spatial data through 3D modeling. The course also introduces students to several statistical and computational approaches to quantifying spatial patterns and identifying clusters and outliers in spatial data. The course also further deepens skills in applying GIS as a tool for studying urban problems. Students work on case study projects drawn from local communities. The course will include practice in spatial workflow automation using Python
Meets
Mon 6:00-9:00pm Computer Lab Room 2109