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Cellular Automata for Urban Growth Modelling

机译:元胞自动机用于城市增长建模

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Urban growth modelling has attracted considerable attention over the past two decades. This article reviews the driving factors that have been identified and studied in cellular automata (CA); one of the popular methods in urban growth modelling. Over a hundred articles published between 1993 and 2012 were selected and reviewed. We extracted the driving factors from CA transition rules and arranged them in a list. The list contributes to early spatial research for the selection of factors in CA models. Our analyses show that studies between 1993 and 2000 mainly focused on using earth’s physical factors in predicting urban growths, while recent studies combined them with socioeconomic factors, resulting with models with a greater number of inputs. Nevertheless, the human-behaviour factors impacting urban growth were generally under-represented. Geographically, more applications of the CA urban growth models have been seen in the developed countries compared with those in the developing countries, suggesting substantial work is needed to address issues in understanding and modelling rapid urban growth processes in developing countries.
机译:在过去的二十年中,城市增长模型吸引了相当多的关注。本文回顾了已经在细胞自动机(CA)中确定和研究的驱动因素;城市增长建模中流行的方法之一。选择并审查了1993年至2012年之间发表的一百多篇文章。我们从CA转换规则中提取了驱动因素,并将它们排列在列表中。该列表有助于在CA模型中选择因子的早期空间研究。我们的分析表明,1993年至2000年之间的研究主要集中于利用地球的物理因素来预测城市的增长,而最近的研究则将它们与社会经济因素相结合,从而产生了具有大量输入的模型。然而,影响城市增长的人为因素普遍未被充分体现。从地理上讲,与发展中国家相比,在发达国家中,CA城市增长模型的应用更多,这表明需要大量工作来解决对发展中国家快速城市增长过程的理解和建模问题。

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