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A Production–Living–Ecological Space Model for Land-Use Optimisation: A case study of the core Tumen River region in China
Ecological Modelling ( IF 3.1 ) Pub Date : 2020-12-01 , DOI: 10.1016/j.ecolmodel.2020.109310 Fenghao Tian , Mingyu Li , Xulong Han , Hui Liu , Boxian Mo
Ecological Modelling ( IF 3.1 ) Pub Date : 2020-12-01 , DOI: 10.1016/j.ecolmodel.2020.109310 Fenghao Tian , Mingyu Li , Xulong Han , Hui Liu , Boxian Mo
Abstract The study of production–living–ecological space (PLES) is essential for the sustainable use of land resources and regional socioeconomic development, and several studies have adopted PLES-based evaluation indices. However, few studies have investigated the effects of governmental regulation and human activity on the optimal allocation of land for different uses. Crucially, the non-optimal use of land by urban decision-makers leads to multiple problems including wasting potential land resources and trade-offs between economic development and environmental protection. Therefore, in this study, we developed a multi-spatial agent-based optimisation model (MSABOM) coupled with a multi-agent system (MAS) within a machine-learning framework. The MSABOM determines spatially optimised land-use solutions based on the small-scale land-use preferences of stakeholders, and addresses conflicts in the sub-optimal allocation of resources based on the behaviours of model agents and the decision-making environment. The Yanbian Korean Autonomous Prefecture in China was used as a case study to demonstrate the effectiveness of this approach. The results show that (1) the MSABOM can significantly improve the optimisation of PLES, improving the land utilisation rate by 1.22 times; (2) based on an understanding of existing practices, the optimal allocation plan obtained by the agent-based model is more suitable than that obtained by a non-agent-based model; (3) multi-functional land-use patterns can be optimally allocated in space and time, which is extremely useful for coordinating stakeholder participation and addressing conflicts of interest in land-use behaviours; and (4) an urban spatial development coefficient was successfully used to determine the dominant function and functional positioning of PLES, which helps ensure flexible development strategies for spatial planning.
更新日期：2020-12-01
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