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Urban ecological security assessment and forecasting using integrated DEMATEL-ANP and CA-Markov models: A case study on Kolkata Metropolitan Area, India
Sustainable Cities and Society ( IF 10.5 ) Pub Date : 2021-02-12 , DOI: 10.1016/j.scs.2021.102773
Subrata Ghosh , Nilanjana Das Chatterjee , Santanu Dinda

Due to rapid urbanization, Indian cities have faced serious environmental problems, including pollution, loss of urban green space, increasing heat island phenomena, and destruction of the urban ecosystem, over the past few decades. Urban ecological security (UES) measures the degree of urbanization pressure and level of ecological sensitivity. Currently, urban ecological security assessment (UESA) is an important aspect of sustainable urban development. Accurate assessment of ecological security status has become a real problem because of differential evaluation methods produced variable results. The present study aims to address these shortcomings using integrated DEMATEL-ANP model to select the influencing factors and assess ecological security of Kolkata Metropolitan Area (KMA). Moreover, a combined cellular automata and Markov chain model was applied to simulate land-use/land-cover change and predict the future state of UES in KMA. The result shows that land use land cover change rate, built-up density, green area change intensity index and landscape connectivity index are the most influencing factors in UES. The present study can enrich the methods in the field of UESA and the findings of this study can provide valuable and scientific guidance to optimize land-use planning and potentially improving the ecological security of an urban area.



中文翻译:

基于DEMATEL-ANP和CA-Markov集成模型的城市生态安全评估与预测:以印度加尔各答大都会区为例

由于快速的城市化,印度城市在过去的几十年中面临着严重的环境问题,包括污染,城市绿地的丧失,热岛现象的加剧以及城市生态系统的破坏。城市生态安全(UES)衡量城市化压力的程度和生态敏感性水平。当前,城市生态安全评估(UESA)是城市可持续发展的重要方面。由于不同的评估方法产生了可变的结果,因此准确评估生态安全状况已成为一个现实问题。本研究旨在利用集成的DEMATEL-ANP模型来解决这些缺点,以选择影响因素并评估加尔各答都市区(KMA)的生态安全。而且,结合细胞自动机和马尔可夫链模型来模拟土地利用/土地覆盖的变化,并预测UES在KMA中的未来状态。结果表明,土地利用变化率,建筑密度,绿地变化强度指数和景观连通性指数是影响UES的最大因素。本研究可以丰富UESA领域的方法,并且本研究的结果可以为优化土地利用规划并潜在改善城市生态安全提供有价值的科学指导。

更新日期:2021-02-24
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