Using EL-CA Model to Predict Multi-Scenario Land Sustainable Use Simulation and Urban Development

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Abstract

The ecological civilisation has become a consensus on society development in China, and is an inevitable requirement for building a community with a shared future for mankind. Exploring the changes in land use in mountainous counties is practically required to achieve a sustainable economy and society and build a beautiful China. Aiming at the contradiction between the expansion of urban construction land and the ecological environment, the research takes a typical mountainous city, Qianshan city, as an example. Under the three scenarios guided by the two development concepts: protect cultivated land priority and protect ecological priority, the research applies the SD model to predict the demand for land use, the EL-CA model to simulate the spatial evolution of land use, and the gravity centre model to analyse the city’s future development. Results show that: (1) In the scenario of protect cultivated land priority, ecological land is severely fragmented, and part of it is converted into cultivated land; in the scenario of protect ecological land priority, the ecological land nearby built-up area is largely encroached, and the others may be spottily encroached by construction land; (2) In different development scenarios, cities will mainly expand to the south in the future, and the northern part of the city will generally undertake the protection of ecological and cultivated land. The research simulates the evolution process of future land use in mountainous cities; it provides a theoretical reference for spatial planning for national land and the implementation of green development and technical guidance for urban expansion and ecological coordination.

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APA

Li, J., Cao, Y., Li, Y., Chu, J., Wang, Y., & Ma, M. (2023). Using EL-CA Model to Predict Multi-Scenario Land Sustainable Use Simulation and Urban Development. Journal of Experimental Nanoscience. Taylor and Francis Ltd. https://doi.org/10.1080/17458080.2023.2170352

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