Investigating accessibility resilience of emergency and lifesaving facilities under natural hazards

Chih-Hao Wang (), Na Chen () and Craig Olwert ()
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Chih-Hao Wang: California State University, Fresno
Na Chen: Sun Yat-sen University
Craig Olwert: California State University, Northridge

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2024, vol. 120, issue 2, No 30, 1785-1807

Abstract: Abstract Although accessibility has been widely studied from a variety of perspectives, it is rare to analyze accessibility resilience under the long-term threat of different natural hazards which emerge more frequently in recent years. Most existing transportation resilience studies focus on the transportation infrastructure’s ability to function mainly in terms of connectivity during or after a disaster, neglecting the facility allocation which also affects transportation accessibility. We develop an analytical research framework to investigate the resilience of accessibility to emergency and lifesaving (E&L) facilities (including parks, schools, hospitals, roads, and fire stations) considering the impacts of the seismic and wildfire hazards in the San Fernando Valley, CA. Using the cumulative-opportunity approach, pre-accessibility to E&L facilities without the impact of a hazard is calculated by counting the number or area/length of each type of E&L facilities via driving within a specified travel threshold for each census tract in the study region. With the same approach, post-accessibility to E&L facilities is calculated for each hazard under certain simulations and then statistically compared to identify hotspots which are most likely to receive statistically significant damage. The hotspots are further analyzed by a normalized difference accessibility index (NDAI) to suggest whether decision makers should invest in facilities or the transportation network to improve accessibility resilience. This analytic framework will allow planners and decision makers to efficiently identify their most vulnerable locations and identify needed mitigation measures.

Keywords: Natural hazards; Accessibility; Resilience; Statistical analysis; Hotspot analysis (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11069-023-06272-8

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