生态阻力面模型的构建及其在城市扩展模拟中的应用（英文）

发布时间：2017-09-26 03:39

  本文关键词：生态阻力面模型的构建及其在城市扩展模拟中的应用（英文）

  更多相关文章： urban expansion simulation ecological resistance surface model

【摘要】：Urban expansion models are useful tools to understand urbanization process and have been given much attention.However,urban expansion is a complicated socio-economic phenomenon that is affected by complex and volatile factors involving in great uncertainties.Therefore,the accurate simulation of the urban expansion process remains challenging.In this paper,we make an attempt to solve such uncertainty through a reversal process and view urban expansion as a process wherein the urban landscape overcomes resistance from other landscapes.We developed an innovative approach derived from the minimum cumulative resistance(MCR) model that involved the introduction of a relative resistance factor for different source levels and the consideration of rigid constraints on urban expansion caused by ecological barriers.Using this approach,the urban expansion ecological resistance(UEER)model was created to describe ecological resistance surfaces suitable for simulating urban expansion and used to simulate urban expansion in Guangzhou.The study results demonstrate that the ecological resistance surface generated by the UEER model comprehensively reflects ecological resistance to urban expansion and indicates the spatial trends in urban expansion.The simulation results from the UEER-based model were more realistic and more accurately reflected ecological protection requirements than the conventional MCR-based model.These findings can enhance urban expansion simulation methods.
【作者单位】： Guangzhou
【关键词】： urban expansion simulation ecological resistance surface model
【基金】：National Natural Science Foundation of China,No.41001385 12th Five-year National Science Supported Planning Project,No.2012BAJ15B02
【分类号】：F299.2;F224
【正文快照】： 1 IntroductionIntense urbanization processes are ongoing worldwide,especially in developing countries.According to the United Nations predicts,the population of urban areas is expected to ex?ceed 60%by 2030,with 90%of the increase occurring in low income

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