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Simulating Urban Shrinkage in Detroit via Agent-Based Modeling

While we are witnessing a growth in the world-wide urban population, not all cities are growing equally and some are actually shrinking (e.g., Leipzig in Germany; Urumqi in China; and Detroit in the United States). Such shrinking cities pose a significant challenge to urban sustainability from the urban planning, development and management point of view due to declining populations and changes in land use. To explore such a phenomena from the bottom up,Na (Richard) Jiang, Wenjing Wang, Yichun Xie

and myself have a new paper entitled “Simulating Urban Shrinkage in Detroit via Agent-Based Modeling” published in Sustainability. 

This paper builds on our initial efforts in this area which was presented in a previous post. In that post we showed how a stylized model could not only simulate housing transactions but the aggregate market conditions relating to urban shrinkage (i.e., the contraction of housing markets). In this new paper, we significantly extend our previous work by: 1) enlarging the study area; 2) introducing another type of agent, specially, a bank type agent; 3) enhancing the trade functions by incorporating agents preferences when it comes to buying a house; 4) adding additional household dynamics, such as employment status change. These changes will are discussed extensively in the methodology section of the paper.

If this is of interest to you, below we provide the abstract of the paper along with some figures of the study area, graphical user interface, model logic and results. At the bottom of the post you can see the full reference to the paper along with a link to it. The model itself was created in NetLogo and a similar to our other works, we have a more detailed description of the
model following the Overview, Design concepts, and Details (ODD)
protocol along with the source code and data needed to run the model at:


While the world’s total urban population continues to grow, not all cities are witnessing such growth, some are actually shrinking. This shrinkage causes several problems to emerge, including population loss, economic depression, vacant properties and the contraction of housing markets. Such issues challenge efforts to make cities sustainable. While there is a growing body of work on studying shrinking cities, few explore such a phenomenon from the bottom-up using dynamic computational models. To fill this gap, this paper presents a spatially explicit agent-based model stylized on the Detroit Tri-County area, an area witnessing shrinkage. Specifically, the model demonstrates how the buying and selling of houses can lead to urban shrinkage through a bottom-up approach. The results of the model indicate that along with the lower level housing transactions being captured, the aggregated level market conditions relating to urban shrinkage are also denoted (i.e., the contraction of housing markets). As such, the paper demonstrates the potential of simulation to explore urban shrinkage and potentially offers a means to test policies to achieve urban sustainability.

Keywords: Agent-based modeling; housing markets; Urban Shrinkage; cities; Detroit; GIS

Study Area.  
Model graphical user interface, including input parameters, monitors (left) and the study area (middle) and charts recording key model properties.

Unified modeling language (UML) Diagram of the Model.

Household Decision-Making Process for Stay or Leave Current Location.

Heat Maps of Median (A) and Average (B) House Prices at the End of the Simulation where Demand equals Supply.

Full Reference: 

Jiang, N., Crooks, A.T., Wang, W. and Xie, Y. (2021), Simulating Urban Shrinkage in Detroit via Agent-Based Modeling, Sustainability, 13, 2283. Available at https://doi.org/10.3390/su13042283. (pdf)


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