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Land Use Optimization for a Rapidly Urbanizing City with Regard to Local Climate Change: Shenzhen as a Case Study

机译:考虑局部气候变化的快速城市化城市土地利用优化:以深圳为例

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Land use and land use change have been proven to be leading causes of local climate change. In cities that undergo rapid urbanization, the urban heat island (UHI) can generate serious problems for the urban living environment. An appropriate overall land use plan can mitigate the detrimental effects of an UHI because it can reduce its development. However, land use decisions are driven by social and economic factors that cannot be made on the basis of moderating an UHI alone. To make a sound land use plan for Shenzhen in 2020, a rapidly urbanizing city in China suffering from UHI due to its fast land development, a genetic algorithm-based multiobjective optimization (MOO) approach was develped that addresses the objectives for future land use. The MOO provides a set of Pareto solutions and then the decision maker or planner can choose from the set of solutions. Recognizing the definite development of certain nonurban land for the local economy, three objectives were considered: (1) minimizing the increase of surface temperature, (2) minimizing the incompatibility between land uses, and (3) minimizing the cost of land use changes from the status quo. To quantify the effects of land use patterns on the UHI in Shenzhen, a self-organizing maps (SOM) method and linear regression model were used to establish the interactive relation. The relation thus obtained was then used in the MOO to help evaluate the effects of alternative land use patterns on the development of the UHI. Four scenarios were examined. The first scenario took all three objectives into account, and one optimal plan was selected randomly from the Pareto set as the first scenario, whereas the other three scenarios considered one objective each. Results showed that MOO can make tradeoffs among the conflicting objectives, indicating that the optimized land use plans can minimize the increasing UHI effects and at the same time attempt to achieve other objectives in the process of land development.
机译:事实证明,土地利用和土地利用变化是当地气候变化的主要原因。在经历快速城市化的城市中,城市热岛(UHI)可能给城市生活环境带来严重问题。适当的土地总体规划可以减轻UHI的不利影响,因为它可以减少UHI的发展。但是,土地使用决策是由社会和经济因素驱动的,而这些因素不能仅基于调节UHI来做出。为了制定一个合理的土地利用计划,以实现2020年深圳的土地利用快速发展的目标,该城市由于土地开发速度快而遭受着城市重工业的困扰,因此中国城市发展迅速,因此开发了一种基于遗传算法的多目标优化(MOO)方法,以解决未来土地利用的目标。 MOO提供了一组Pareto解决方案,然后决策者或计划者可以从一组解决方案中进行选择。认识到一定的非城市土地对于当地经济的明确发展,考虑了以下三个目标:(1)最小化地表温度的升高;(2)最小化土地利用之间的不相容性;(3)最小化土地利用变化的成本现状。为了量化土地利用方式对深圳城市轨道交通的影响,采用了一种自组织图(SOM)法和线性回归模型来建立互动关系。这样获得的关系随后在MOO中使用,以帮助评估替代土地利用模式对UHI发展的影响。检查了四个方案。第一个方案考虑了所有三个目标,并且从帕累托集中随机选择了一个最佳计划作为第一个方案,而其他三个方案则各自考虑一个目标。结果表明,MOO可以在相互矛盾的目标之间进行权衡,这表明优化的土地利用计划可以最大程度地减少UHI的影响,同时尝试在土地开发过程中实现其他目标。

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