Abstract:

Urban expansion simulation and prediction are vital for supporting national spatial planning and promoting sustainable urbanization. Improving its scientific and practical applicability is essential to accurately capturing urban expansion trends and sustainable land resource utilization. Present cellular automata (CA) models focus on describing spatially driven urban expansion, while those using the agent-based model (ABM) approach provide theoretical benefits in simulating self-organized urban expansion. Moreover, existing coupling methods predominantly cascade these models based on simulation steps, presenting challenges in deeply integrating them to unleash their potential for simulating both natural and self-organized urban expansion. This study is grounded in the structural openness of CA and the theoretical strengths of ABM. It uses accessibility as an intermediary to define scope variations in local self-organized processes during urban expansion. Additionally, it devises rules for local self-organization to model stakeholder interactions using game theory principles. Then this study integrates the human-land interactions portrayed by ABM, guided by the defined scope and rules, into the CA neighborhood construction. This approach leads to the creation of a CA-ABM-coupled urban expansion simulation and prediction model with a fine depiction of local self-organization processes (CA-ABM-LSO). This model revolves around finely defined localized self-organization and achieves a deep integration of CA and ABM within the foundational structure, which enables a coupled simulation of natural and self-organizational urban expansion processes. Using Wuhan as a case study, the results show that the CA-ABM-LSO effectively leverages its capabilities to depict both natural and self-organized urban expansion. This enhancement significantly improves urban expansion simulation accuracy and refines the landscape patterns of simulated urban patches. Rules based on game theory that govern local self-organization can effectively guide the behaviors of micro-agents through macro-economic policies, which can strengthen the scientific robustness and planning viability of urban expansion simulations. Expected by 2035, the key areas for urban expansion in Wuhan are predicted to concentrate near high-tech zones and transportation hubs, which aligns with the planning of the “Wu-E-Huang-Huang” metropolis and would provide valuable foundational insights for its land resource management.

Key words: urban expansion, cellular automata, agent, self-organization