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Scenario-based simulation of land use in Yingtan (Jiangxi Province, China) using an integrated genetic algorithm-cellular automata-Markov model

机译:基于情景的鹰潭(江西省)用综合遗传算法 - Markov模型模拟

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摘要

Yingtan is a rapidly urbanizing city in Jiangxi Province, South China. During rapid urbanization, construction land is expanded at the expense of cropland and forest. Although economic benefits are gained, ecological and environmental damage is irreversible. In this study, a methodological framework for land use simulation using an integrated genetic algorithm-cellular automata-Markov model is proposed to assess the relationship between economic development and cropland protection in Yingtan. This framework considers both the economic and ecological benefits of different land use types. Three land use scenarios are evaluated to seek recommendations for land use practice. The results show that the areas with high suitability for cropland and construction are mainly concentrated in urban fringes. Under the green development scenario, the area of new construction land can meet the land demand for population growth and economic development proposed for 2025 based on population forecasting and government interviews. The expansion for construction land is decreased by ~ 35 km(2)while the cropland area is increased by ~ 20 km(2)compared with those under natural and controlled development scenarios. Additionally, ecological losses are lowest under the green development scenario. In conclusion, the green development scenario is conducive to both cropland and ecological protection, which is of relevance for future spatial planning in Yingtan.
机译:鹰潭是江西省南方迅速城市化的城市。在快速城市化期间,建设土地以牺牲农田和森林为代价而扩大。虽然获得了经济效益,但生态和环境损害是不可逆转的。在本研究中,提出了一种使用综合遗传算法 - 蜂窝自动机 - 马尔可夫模型的土地利用模拟方法框架,以评估鹰潭经济发展与农田保护之间的关系。该框架考虑了不同土地使用类型的经济和生态效益。评估三种土地使用方案以寻求土地利用实践的建议。结果表明,为农田和施工适用性高的地区主要集中在城市边缘。在绿色发展情景下,新建筑地区可以满足2025年人口预测和政府访谈所提出的人口增长和经济发展的土地需求。建筑用地的扩展减少〜35公里(2)(2)厘米下降,而农田面积增加约20公里(2)(2),与自然和控制发展情景下的人相比。此外,在绿色发展场景下,生态损失最低。总之,绿色发展方案有利于农田和生态保护,这与鹰潭未来空间规划有关。

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