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A 3D agent-based model for simulating urban densification in Toronto, Canada

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  • Richard Burke
  • Raja Sengupta
  • Alistair Ford

Abstract

The use of land parcel data, 3D visualisation and urban theories offers a significant opportunity for advancing simulations of urban densification. This paper presents a 3D agent-based model (ABM) to explore future urban densification dynamics in Toronto based on stakeholder behaviour and interactions, the impact of zoning regulations, and profit expectations. The ABM establishes residents, developers, landowners, and the local zoning authority as primary actors involved in urban densification. This model replicates the Toronto urban development process through a structured framework of submodels which represent different stages of this process, based on the literature and gentrification theories. Three different scenarios are developed which show the city is projected to experience between 46 and 98 new developments by the year 2040. Average building height could increase by 17% to 56%, and the city could have 10,238 to 25,070 new units to meet future population demand. These simulations characterise Toronto’s future capacity for urban densification, realise the levels of densification required to meet Toronto’s growing population, and ultimately provide a more comprehensive understanding of the city’s future transformation.

Suggested Citation

  • Richard Burke & Raja Sengupta & Alistair Ford, 2025. "A 3D agent-based model for simulating urban densification in Toronto, Canada," Environment and Planning B, , vol. 52(3), pages 527-544, March.
  • Handle: RePEc:sae:envirb:v:52:y:2025:i:3:p:527-544
    DOI: 10.1177/23998083241261762
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    References listed on IDEAS

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    1. Liu, Dongya & Zheng, Xinqi & Wang, Hongbin, 2020. "Land-use Simulation and Decision-Support system (LandSDS): Seamlessly integrating system dynamics, agent-based model, and cellular automata," Ecological Modelling, Elsevier, vol. 417(C).
    2. Damian Pitt, 2013. "Evaluating the greenhouse gas reduction benefits of compact housing development," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 56(4), pages 588-606, May.
    3. Wenwu Tang & Jianxin Yang, 2020. "Agent-Based Land Change Modeling of a Large Watershed: Space-Time Locations of Critical Threshold," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 23(1), pages 1-15.
    4. Jörg Blasius & Jürgen Friedrichs & Heiko Rühl, 2016. "Pioneers and gentrifiers in the process of gentrification," European Journal of Housing Policy, Taylor and Francis Journals, vol. 16(1), pages 50-69, January.
    5. Bernard Nzau & Claudia Trillo, 2019. "Harnessing the Real Estate Market for Equitable Affordable Housing Provision through Land Value Capture: Insights from San Francisco City, California," Sustainability, MDPI, vol. 11(13), pages 1-21, July.
    6. Jörg Blasius & Jürgen Friedrichs & Heiko Rühl, 2016. "Pioneers and gentrifiers in the process of gentrification," International Journal of Housing Policy, Taylor & Francis Journals, vol. 16(1), pages 50-69, January.
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