Road network vulnerability and city-level characteristics: A nationwide comparative analysis of Japanese cities. (June 2021)

• Record Type: Journal Article
• Authors: Santos, Johan Rose; Safitri, Nur Diana; Safira, Maya; Varghese, Varun; Chikaraishi, Makoto
• Is Part Of: Environment & planning. Volume 48:Number 5(2021)
• Page Start: 1091
• Page End: 1107
• Publication Date: 2021-06
• Subjects: Vulnerability -- efficiency -- robustness -- transport network -- Japan; City planning -- Periodicals; Urban ecology (Sociology) -- Periodicals; 307.11605
• DOI: 10.1177/2399808321999318
• Languages: English
• ISSNs: 2399-8083

Abstract

Climate change is making our cities more vulnerable, increasing the needs for further policy actions to make them more resilient. In particular, the transport network is critical in the first phase of disaster response. This study presents the epirical findings of a large scale, nationwide analysis of the road network vulnerability in 69 Japanese cities. We (1) identify the level of network efficiency using topological elements in its undisturbed normal state; (2) evaluate the level of network robustness under different random and targeted attack scenarios; and (3) analyze the relationship of the identified network efficiency and robustness indicators with city-level characteristics. The main findings include: (1) cities with a higher population and a higher infrastructure investment tend to be more robust under random attacks; (2) larger cities tend to be less robust to targeted attacks, presumably due to their high agglomeration of urban functions; (3) car dependency tends to make cities more vulnerable toward random attacks and less vulnerable toward targeted attacks as it indicates a weaker concentration in urban functions; and (4) a high modal share for trains tends to make cities less vulnerable toward random events as it indicates a high agglomeration of urban functions. These findings will help policymakers to prioritize their budget allocations to improve nationwide disaster resilience.