Wednesday, May 19, 2021

A Semester of Spatial Simulation

While at Mason, it was a tradition of mine to make  a post of some of the models developed by students in my classes as part of their end of semester projects.  So while I am not at Mason anymore, I thought I would keep this tradition when teaching agent-based modeling classes. To that end, this semester at UB I taught a class entitled “Spatial Simulation” (and the course description is below for these who are interested). 
 
For many, this was their first exposure to agent-based and cellular automata (CA) modeling. As part of the class the students were expected to complete an end of semester project, in this case, develop an agent-based or CA model that explores some aspect of the course themes.   The movie below shows a selection of these projects which ranged from what a exploring what 15 minute city would look like, to that of land use change over years and several other  topics in-between. Many of the astute readers might notice these models where created using NetLogo which was used in class to teach the basics of spatial simulation but at the same time could leverage our book  "Agent-based Modelling and Geographical Information Systems: A Practical Prime" and associated resources on GitHub.

Coarse Description:

This graduate course will introduce students in the geographical and environmental sciences to the use of spatial simulation methods (e.g., cellular automata, agent-based modeling) to explore complex geographical phenomena from the bottom up. For example, how the micro-movement of pedestrians lead to the emergence of crowds or how individuals buying and selling houses lead to property markets forming. We will cover geographical applications in areas such as agriculture, biodiversity, interactions between human populations and nonhuman species and cities. Emphasis will be placed on the notion that geographical systems are constantly changing at various spatiotemporal scales and how through spatial simulation we can gain an understanding of the processes that lead to patterns that we can observe through data. The course will combine taught classes, literature reviews and discussions with hands-on spatial simulation modeling. The format of the class will consist of both lecture and discussion, with substantial emphasis on student participation.

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