Details of Award
NERC Reference : NE/X006727/1
A 3D agent-based model for simulating urban redevelopment at the building scale
Grant Award
- Principal Investigator:
- Dr AC Ford, Newcastle University, Sch of Engineering
- Grant held at:
- Newcastle University, Sch of Engineering
- Science Area:
- None
- Overall Classification:
- Unknown
- ENRIs:
- None
- Science Topics:
- Complexity Science
- Agent-Based Models
- Urban policy and regeneration
- Spatial Planning
- Artificial Intelligence
- Artificial Intelligence
- Neural Networks (AI)
- Geo-spatial methods
- Social Stats., Comp. & Methods
- Abstract:
- EPSRC : Richard Burke : EP/S023577/1 Toronto is currently one of the top three fastest growing central cities in North America. Between 2006-2016, Toronto's population grew by 9% and by 2030 the population is projected to grow by an additional 13%. This exponential growth is primarily attributed to high levels of immigration, with immigrants constituting just under 50% of Toronto's population. Toronto's population growth and limited land availability has caused a real estate bubble: a significant rise in property prices due to demand outpacing supply. To ensure it remains a liveable city, Toronto must focus on rebuilding, reurbanising and regenerating within an existing urban structure that is difficult to change. Redevelopment of the existing city should be prioritised to address this real estate crisis and ensure it remains a resilient city. The most appropriate way to explore Toronto's potential for redevelopment is to evaluate current city planning regulations, the real estate market and urban form in a simulation environment to evaluate their longevity and robustness. Agent-based models are ideal to evaluate Toronto's future urban redevelopment potential as they provide a suitable environment to replicate the urban redevelopment process. This modelling technique provides a conceptual and theoretical framework to simulate spatially dynamic processes through self-activities and interactions between various rule-based agents. Agent-based models are very dynamic and have been applied to a wide range of research topics, such as modelling pedestrian movements for simulating COVID-19 transmission and future urban expansion dynamics. The definition of agents in an agent-based models are unlimited and can represent key actors in the redevelopment process, such as government, resident, and developer stakeholders as well as spatial entities important in urban redevelopment such as land parcels, roads, and buildings. Agent-based models are very well suited to simulate urban redevelopment as they can capture the complex relationships between urban planning regulations, the real estate market and urban form which are important factors needed to accurately replicate the urban redevelopment process. Therefore, the aim of this project is to explore how Toronto's planning regulations, real estate market and urban form influence the feasibility of redevelopment within the city. The expected results will contribute to society and industry through the creation of 3D spatial decision support system as one of the key deliverables. This tool will help inform stakeholders of the viability of current urban regulation policies, provide insight into the most suitable locations for future urban redevelopment projects and help improve overall city management. In addition, the implementation of 3D visualisation is beneficial for urban planners to understand and interpret how vertical height limitations can impact the opportunity of redevelopment. Overall, the approach of this project will highlight how agent-based models are an invaluable tool to address the Canadian real estate crisis and can contribute to urban redevelopment initiatives to ensure a more functional city. This approach will provide a dynamic framework which can be readily applied to other Canadian cities experiencing similar real estate challenges and will ultimately improve Canada's capability to develop more sustainable urban planning strategies and regulations.
- NERC Reference:
- NE/X006727/1
- Grant Stage:
- Completed
- Scheme:
- NC&C NR1
- Grant Status:
- Closed
- Programme:
- Globalink Placement
This grant award has a total value of £12,333
FDAB - Financial Details (Award breakdown by headings)
| Exception - Other Costs |
|---|
| £12,332 |
If you need further help, please read the user guide.