A CA-ABM-coupled simulation and prediction model for finely depicting the local self-organization process of urban expansion
Urban expansion simulation and prediction are vital for supporting national spatial planning and promoting sustain-able 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 ex-pansion,while those using the agent-based model(ABM)approach provide theoretical benefits in simulating self-organized ur-ban expansion.Moreover,existing coupling methods predominantly cascade these models based on simulation steps,presen-ting challenges in deeply integrating them to unleash their potential for simulating both natural and self-organized urban expan-sion.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 hu-man-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 effec-tively leverages its capabilities to depict both natural and self-organized urban expansion.This enhancement significantly im-proves 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 re-source management.