Modelling and simulating 'informal urbanization': An integrated agent-based and cellular automata model of urban residential growth in Ghana
Modelling and simulating 'informal urbanization': An integrated agent-based and cellular automata model of urban residential growth in Ghana
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DOI：
10.1177/23998083211068843
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发表时间：
2022-01-12
影响因子：
3.5
通讯作者：
Fox, Sean
中科院分区：
文献类型：
--
作者：
Agyemang, Felix S. K.;Silva, Elisabete;Fox, Sean
未来30年，全球城市人口预计将增长25亿，其中90%将发生在非洲和亚洲国家。这些地区的城市扩张通常以“非正式城市化”为特征，即在产权不明确、不安全或有争议的情况下，家庭在没有规划许可的情况下自行建设。尽管非正式城市化的规模很大，但它几乎没有受到城市分析和城市科学领域的学者的关注。为了解决这一差距，我们引入了TI-City，这是一个城市增长模型，旨在预测非洲城市未来住宅开发的位置、法律地位和社会经济地位。在自下而上的方法中，我们使用基于代理的和元胞自动机建模技术来预测主要城市发展参与者的地理空间行为，包括家庭、房地产开发商和政府。我们将模型应用于加纳阿克拉的城市地区，利用当地收集的数据，包括家庭调查，来对模型进行参数化。使用多空间尺度验证技术，我们将TI-City模拟历史观察到的建筑模式的能力与广受欢迎的城市增长模型SLEUTH进行了比较。结果表明，TI-City在每个尺度上的表现都好于Sleuth，这表明该模型可以在类似的城市背景下提供一个有价值的决策支持工具。
The global urban population is expected to grow by 2.5 billion over the next three decades, and 90% of this growth will occur in African and Asian countries. Urban expansion in these regions is often characterised by 'informal urbanization' whereby households self-build without planning permission in contexts of ambiguous, insecure or disputed property rights. Despite the scale of informal urbanization, it has received little attention from scholars working in the domains of urban analytics and city science. Towards addressing this gap, we introduce TI-City, an urban growth model designed to predict the locations, legal status and socio-economic status of future residential developments in an African city. In a bottom-up approach, we use agent-based and cellular automata modelling techniques to predict the geospatial behaviour of key urban development actors, including households, real estate developers and government. We apply the model to the city-region of Accra, Ghana, drawing on local data collection, including a household survey, to parameterise the model. Using a multi-spatial-scale validation technique, we compare TI-City's ability to simulate historically observed built-up patterns with SLEUTH, a highly popular urban growth model. Results show that TI-City outperforms SLEUTH at each scale, suggesting the model could offer a valuable decision support tool in similar city contexts.