Semester Offering: InterSem

This course will focus on introducing students to the use of geographic information system (GIS) and remotely sensed data for urban and environmental analysis. Students will learn to work with urban spatial databases including data sets pertaining to land use/land cover, parcel records, census demographics, environmental issues, disaster and climate change impacts, etc. Technical topics and practical applications to be covered include finding and understanding sources of information for metropolitan spatial databases, integration of data from a variety of sources, database structure and design issues, spatial analysis capabilities, data quality and data documentation. While learning GIS and Remote Sensing analytical skills, students will complete a mapping/analysis project of their choosing.


By the end of the course, students should be able to:
1.        Identify, locate, and acquire spatial data pertinent to projects in their field of interest.
2.        Explain the data creation process and create simple data sets and/or add to existing data.
3.        Perform basic spatial analyses as well as link these methods together in a more complex analytical model to answer their research questions.




I.        Introduction and Course Overview
1.      Concepts and functionality of spatial analysis
2.      Basics and History of geographic information systems (GIS) and Remote Sensing (RS)
3.      GIS and RS application examples

II.       Finding, Assessing and Using Existing Spatial Data
1.      Data sources and structures
2.      Working with attributes
3.      Using plugins
4.      Visualization of spatial data

III.     Working with Urban Spatial and Statistical Data in GIS
1.      Importing geospatial data from outside sources
2.      Coordinate systems and projections
3.      Density analysis
4.      Proximity and network analysis

IV.     Georeferencing and Geocoding
1.    Creating new GIS data and editing
2.    Mapping addresses through geocoding

V.        Raster Basics and Analysis in RS
1.    Image acquisition and processing
2.    Image classification
3.    Change detection
4.    Accuracy assessment
5.    Raster GIS applications

VI.       Spatial Analysis for Urban and Environmental Management
1.    Land use change analysis
2.    Agriculture and forestry mapping
3.    Disaster assessment and impacts


No designated textbook, but class notes and reading materials will be provided.


1.     Applied Spatial Analysis and Policy, Springer

Others: QGIS Training Manual


For each lecture session, students are expected to spend at least 3 hours on self-study (reading and working through the provided materials). Additional 5-10 hours of out-of-class student work is required for completing each assignment.


The course will follow a lecture and in-class hands-on exercises format. There will also be an assignment at the end of each session to be completed outside of class. Students may work together to help one another and discuss the materials that constitute the exercise. However, each student is required to prepare and submit summaries (including any computer work) on their own.


The final grade will be computed from the following constituent parts:

-      Assignments 30%
-      Mid-term exam (closed books) 30%
-      Final exam (individual project on data collection and analysis) 30%
-      Class attendance 10%

In the exams, an “A” would be awarded if a student can contextualize the knowledge learned in class by including their own their own insight and analysis. A “B” would be awarded if a student shows an overall understanding of all topics, a “C” would be awarded if a student meets below average expectation in terms of analysis, and a “D” would be awarded if a student does not meet basic expectations in analyzing.