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首页> 外文期刊>Journal of Urban Planning and Development >Ecological Conservation- and Economic Development-Based Multiobjective Land-Use Optimization: Case Study of a Rapidly Developing City in Central China
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Ecological Conservation- and Economic Development-Based Multiobjective Land-Use Optimization: Case Study of a Rapidly Developing City in Central China

机译：基于生态保护和经济发展的多目标土地利用优化：以中部快速发展的城市为例

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摘要

Ecological conservation has long been a hot topic in land-use planning. However, ecological conservation conflicts with economic development in the process of urbanization, which has been noted in a great many studies. In existing studies of land-use planning, a sum-weighted method (SWM) has usually been used to combine several objectives into one objective, and only one solution generated. However, with the SWM, the trade-offs between conflicting objectives are ignored. In this paper, faced with the shortcomings of the existing approaches, a genetic algorithm-based multiobjective optimization (MOO) approach is proposed to search for the Pareto solutions of the land-use structure, followed by a cellular automaton model to represent the spatial land-use distribution. A rapidly developing city in central China, Wuhan, was selected as the case study area. Maximizing the gross domestic product (GDP) value generated by the land use and maximizing the ecosystem service value (ESV) were taken as the multiple objectives for land-use planning in Wuhan. The Pareto solutions are compared with the solutions of three different single objectives: one, maximizing ESV; another, maximizing the sum of GDP and ESV; and the last one, maximizing GDP. It is concluded that the Pareto solutions can reflect the potential possible values of GDP and ESV. Moreover, the Pareto solutions can represent a trade-off between economic development and ecological conservation.
机译：长期以来，生态保护一直是土地利用规划中的热门话题。然而，在许多城市研究中已经注意到，生态保护与城市化过程中的经济发展相冲突。在现有的土地利用规划研究中，通常采用总和加权法（SWM）将多个目标组合为一个目标，并且仅生成一个解决方案。但是，使用SWM时，将忽略目标冲突之间的权衡。面对现有方法的不足，提出了一种基于遗传算法的多目标优化（MOO）方法来寻找土地利用结构的帕累托解，然后采用元胞自动机模型来表示空间土地使用分配。选择了中国中部一个快速发展的城市武汉作为案例研究区域。最大化土地利用产生的国内生产总值（GDP）和最大化生态系统服务价值（ESV）被视为武汉市土地利用规划的多个目标。将帕累托解决方案与三个不同目标的解决方案进行了比较：另一个是最大化GDP和ESV的总和；最后一个是最大化GDP。结论是，帕累托解决方案可以反映GDP和ESV的潜在可能值。此外，帕累托解决方案可以代表经济发展与生态保护之间的权衡。

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