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Geog591

GEOG 591 Urban GIS Applications

Prerequisite: GEO370, or similar course, or experiences with GIS software. Students will use ArcGIS Pro or ArcGIS Desktop software to complete most labs.

Course Descriptions:
This course introduces the theories and applications of Geographic Information Systems (GIS) and teaches hands-on skills using GIS technology, with emphasis on problems in urban/economic geography. Major topics will cover from topological data structure, data collection to spatial analysis, and various urban GIS applications. Another important goal of the course is to expose students to various approaches of integrating spatial models with GIS.

Major urban/economic theories/models covered in this course include: Urban mapping, rank mobility index, urban expansion, population density, central place theory, markov chains, gravity model, etc.

GIS concepts/skills covered in this course: spatial data queries, mapping, geo-referencing, buffering, relational database operations, spatial statistical tools, geo-coding, address matching, network analysis, etc.

Text:

Richard P. Greene, James B. Pick, 2011, Exploring The Urban Community – A GIS Approach,
Pearson Prentice Hall Press, ISBN – 0321751591

Course Components:

This course is an elective course for the GISci Graduate Certificate Program. Besides traditional midterm and final exam, Geog591 also has the following major components:

  • Lecture and ICAs – we will discuss major urban spatial models and GIS analytical methods every week, coupled with various in class activities, such as Urban GIS Mapping, Urban GIS Visualization, service area delineation, Rank Mobility Index GIS exercise, short quizzes, etc.
  • GIS Labs – There will be 8 labs throughout the semester. Students will complete labs with GIS and other related software. This will be vital for students to get hands-on experiences with GIS software.
  • Term project – every student will develop a project proposal (see description below).

Term Project

Term project proposal
Note – Each student needs to submit a proposal by himself/herself, even if he/she works in a group.
Proposals will be graded individually, not by group.
(1) Your proposal should include the following components – problem statement, literature review, data sources, data availability, time expected to collect your data, and methodology (may include urban model specifications, flowcharts of data analysis).

(2) If you choose to work with other students in a group setting (maximum 3 students in a group), you still need to submit your own proposal (you may have similar materials with other group members though, such as methodology, data source, etc.)

(3) Limit of words – 2-3 pages, double space.