Abstract

The precise simulation of urban space evolution and grasping of the leading factors are the most important basis for urban space planning. However, the simulation ability of current models is lacking when it comes to complicated/unpredictable urban space changes, resulting in flawed government decision-making and wasting of urban resources. In this study, a macro–micro joint decision model was proposed to improve the ability of urban space evolution simulation. The simulation objects were unified into production, living and ecological space to realize “multiple planning in one”. For validation of the proposed model and method, remote sensing images, geographic information and socio-economic data of Xuzhou, China from 2000 to 2020 were collected and tested. The results showed that the simulation precision of the cellular automata (CA) model was about 87% (Kappa coefficient), which improved to 89% if using a CA and multi-agent system (MAS) joint model. The simulation precision could be better than 92% using the prosed model. The result of factor weight determination indicated that the micro factors affected the evolution of production and living space more than the macro factors, while the macro factors had more influence on the evolution of ecological space than the micro factors. Therefore, active policies should be formulated to strengthen the ideological guidance towards micro individuals (e.g., a resident, farmer, or entrepreneur), and avoid disordered development of living and production space. In addition, ecological space planning should closely link with the local environment and natural conditions, to improve urban ecological carrying capacity and realize urban sustainable development.

Highlights

  • Land use/cover change (LUCC) has been generally considered a main driving force of global ecosystem and climate change [1]

  • The results show that the simulation precision of cellular automata (CA) model was 87.14% (Kappa coefficient), with an increase to 89.63% when using CA + multi-agent system (MAS) model

  • The accurate simulation of urban space evolution and understanding of the leading factors are key issues to improve the sustainability of urban development

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Summary

Introduction

Land use/cover change (LUCC) has been generally considered a main driving force of global ecosystem and climate change [1]. On the one hand, the socio-economic level may be significantly improved; on the other hand, it leads to loss of farmland, fragmentation of habitats, and increases in the heat island effect [5,6,7]. These problems can be alleviated through reasonable urban space planning and efficient utilization of urban resources [8]. Urban space planning is considered an effective tool/means to improve urban sustainable development

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