Lin, Xuhui; Lu, Qiuchen; Gunn, Neil; Sølvsten, Simon; (2023) Developing a context-based bounded centrality approach of street patterns in flooding: a case study of London. In: Proceedings of 30th EG-ICE:International Conference on Intelligent Computing in Engineering. (pp. pp. 1-10). UCL: London, UK.

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Abstract

Floods affect an average of 21 million people worldwide each year, and their frequency is expected to increase due to climate warming, population growth, and rapid urbanisation. Previous research on the robustness of transport networks during floods has mainly used percolation theory. However, giant component size of disrupted networks cannot capture the entire network’s information and, more importantly, does not reflect the local reality. To address this issue, this study introduces a novel approach to bounded context-based centrality to extract the local impact of disruption. In particular, we propose embedding travel behaviour into the road network to calculate bounded centrality and develop new measures characterising the size of connected components during flooding. Our analysis can identify critical road segments during floods by comparing the decreasing trend and dispersibility of component sizes on road networks. To demonstrate the feasibility of these approaches, a case study of London's transport infrastructure that integrates road networks with relevant urban contexts was developed. This approach is beneficial for practical risk management, helping decision-makers allocate resources efficiently in space and time.

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