Introduction To Spatial Decision Support Systems

Timetable

The course starts on Monday, May 9, 2022 and ends on Monday, May 30, 2022. There will be 7 meetings in the course, 150 min each from 16:30 until 19:00. The meeting dates are: 9/5, 11/5, 16/5, 18/5, 23/5, 25/5, 30/5.

Module aim (aims)

The objective of this course is to introduce students to the fundamental concepts of Spatial Decision Support Systems (SDSS) and methods of Multi-Criteria Analysis applicable to solving spatial decision problems including site selection, resource allocation, and trade-off analysis of location decision alternatives such as, for example, business location selection, real estate choice, or evaluation of landfill site candidates.

Pre-requisites in terms of knowledge, skills and social competences (where relevant)

Students taking the course should be comfortable with basic data analytics and have a basic-level competence in algebra. Familiarity with Geographic Information Systems at an introductory level is a plus but it is not required.

Syllabus

This is a course in analytical methods useful in a variety of decision-making situations, in which location is a part of problem representation and solution. Examples of such situations include business or service site selection, route corridor selection, land use allocation, or prioritization of candidate sites for a specific service such as park, school, health clinic and others. Methods presented in the course belong to the field of Multiple Criteria Decision Analysis (MCDA). They extend common workflows and data analytics procedures used for solving site suitability and resource allocation problems. The course material covers the class of MCDA methods called multiple criteria evaluation. These methods are used by analysts and practitioners in problems requiring the prioritizing of already identified decision alternatives from best to worst. Rather than presenting purely a "cookbook" approach, students will be exposed to both theory and techniques behind the decision support methods prior to using software tools. Take-home problems will be used to ground the lecture material and help students place techniques in a decision problem context. This class should prove valuable to students interested in gaining practical skills useful for solving location selection/resources allocation problems applicable to private and public sectors. All reading materials for the course will be provided in the pdf format by the course instructor.

Student Learning Outcomes
Students in the course will:
1. Become familiar with models and methods of SDSS and spatial multi-criteria analysis.
2. Learn how to formulate and solve site selection problems.
3. Analyze and present the results of spatial multi-criteria evaluation.

Grading Standards
The final grade will be comprised of the following weighting factors:
Two take-home assignments: 50%
Course attendance and participation: 50%

List of Course Topics
1. Introduction to Spatial Decision Making Methods
2. Introduction to Multiple Criteria Decision Analysis
3. Evaluation Criteria
4. Decision Alternatives and Constraints
5. Criterion Weighting Technique
6. Decision Rules/Aggregation Function
7. Lab #1: Landfill Site Selection
8. Site selection with multiple criteria and Geographic Information Systems (GIS)
9. MCDM Technique with Implicit Preferences
10. Lab #2: Real Estate Evaluation

Reading list

Malczewski, J., Rinner, C. 2015. Multicriteria Decision Analysis in Geographic Information Science. Chapter 4, pp.81-119. Springer Verlag (pdf provided by the instructor).

Malczewski, J. (2000). On the use of weighted liner combination method in GIS: Common andbest practice approaches. Transactions in GIS, 4(1), 5–22, (pdf provided by the instructor).

Jankowski, P. 2017. Multicriteria decision-making. The International Encyclopedia of Geography: People, the Earth, Environment, and Technology. John Wiley & Sons. http://onlinelibrary.wiley.com/book/10.1002/9781118786352 (pdf provided by the instructor)

Lieske, S., Hamerlinck, G.. 2015. Integrating Planning Support Systems and Multicriteria Evaluation for Energy Facility Site Suitability Evaluation. URISA Journal 26(1):13-26 (pdf provided by the instructor).

Victor Fernandez Nascimento, Nazli Yesiller, Keith C Clarke, Jean Pierre
Henry Balbaud Ometto, Pedro R. Andrade & Anahi Chimini Sobral. 2017. Modeling the
environmental susceptibility of landfill sites in California, GIScience & Remote Sensing, 54:5,
657-677, DOI: 10.1080/15481603.2017.1309126