Spring 2021 - GEOG 352 D100

Spatial Analysis (4)

Class Number: 2786

Delivery Method: Remote


  • Course Times + Location:

    Tu 2:30 PM – 4:20 PM

  • Exam Times + Location:

    Apr 22, 2021
    8:30 AM – 11:30 AM

  • Instructor:

    Suzana Dragicevic
    1 778 782-4621
    Office: RCB 6233
    Office Hours: TBD
  • Prerequisites:

    GEOG 251 or one of STAT 201, 203 (formerly 103), 205, or 270.



Advanced quantitative techniques for spatial analysis of geographic data and patterns. Topics include geostatistics, spatial interpolation, autocorrelation, kriging, and their use in geographic problem solving with spatial analysis software. Quantitative.


In many decisions and observations in the real world, spatial analysis plays an important role. For example: expensive land is concentrated in the core of the city; we explore the map data to find the best route to get to the restaurant; we know about clusters of forest insect infestations close to our communities; and we are concerned about the distribution of point-source industrial pollutants in our environment. In each of these, we mentally process observations in space and time to arrive at an understanding. But this mental processing is inadequate for large volumes of data. We need to depend on spatial data analysis methods and GIS tools to support our planning and decision-making.

The course will be an integration of lectures and computer labs on various spatial analysis methods such as point pattern analysis, cluster analysis, spatial autocorrelation, as well as spatial interpolation, among others. GIS software and geospatial data will be used for laboratory assignments to complement and reinforce theoretical concepts from the lectures.

Remote delivery: the lectures and labs will be a mixture of synchronous and asynchronous, but primarily asynchronous. Quizzes and the final exam will be synchronous. The course begins in the first week of the term.

The content of the course is subject to minor changes depending on the number of students and available resources.


On successful completion of the course, students should be able to:

  • Demonstrate knowledge of spatial analysis methods
  • Use GIS software for spatial data analysis and management
  • Apply spatial analysis methods to solve problems in geography and related disciplines
  • Pursue further advanced study in spatial analysis and modeling


  • laboratory assignments 50%
  • quizzes (synchronous) 15%
  • final exam (synchronous) 35%


All marks in the course are absolute and not scaled or assigned based on a curve



Requirements for Remote Learning:
Recent Windows or Mac computer, video camera, microphone, keyboard, mouse, reliable internet connection.
The GIS software and some reading materials will be made available for your use during the course.


McGrew, J.C., Lembo, A.J. and Monroe, C.B. (2014). An Introduction to Statistical Problem Solving in Geography. Waveland Press, Inc. (available for purchase on VitalSource)

Registrar Notes:


SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html


Teaching at SFU in spring 2021 will be conducted primarily through remote methods. There will be in-person course components in a few exceptional cases where this is fundamental to the educational goals of the course. Such course components will be clearly identified at registration, as will course components that will be “live” (synchronous) vs. at your own pace (asynchronous). Enrollment acknowledges that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes. To ensure you can access all course materials, we recommend you have access to a computer with a microphone and camera, and the internet. In some cases your instructor may use Zoom or other means requiring a camera and microphone to invigilate exams. If proctoring software will be used, this will be confirmed in the first week of class.

Students with hidden or visible disabilities who believe they may need class or exam accommodations, including in the current context of remote learning, are encouraged to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 778-782-3112).