Research on Risk and Resilience Evaluation of Urban Underground Public Space

• Published in: International journal of environmental research and public health Vol. 19; no. 23; p. 15897
• Main Authors: Li, Xiaojuan, Li, Lulu, Lin, Mingchao, Jim, Chi Yung
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 29.11.2022; MDPI
• Subjects: Casualties; Disaster Planning; Disasters; Emergency exits; Emergency preparedness; Environment; Humans; Indicators; Infrastructure; Mass casualty incidents; Multivariate statistical analysis; Population density; Population growth; Prevention; Public spaces; Resilience; Risk analysis; Risk factors; Risk Management; Subways; Systems stability; Traffic congestion; Urban areas; Urban development; Urban Renewal; underground public space; risk assessment; resilience improvement; safety science; resilience evaluation
• ISSN: 1660-4601; 1661-7827; 1660-4601
• DOI: 10.3390/ijerph192315897

High urban density, land scarcity, rapid population growth, and traffic congestion have restricted urban development. In response, selected multiple functions have increasingly been integrated into the underground public space (UPS) to maximize the 3D utilization of precious urban space. The accelerated intensity of UPS use has alerted safety concerns. UPS with enclosed and confined natures, complex building structures, locations usually in cramped areas, and limited emergency exits are potentially more prone to heavy casualties and losses in natural or human-made disasters. As research on UPS safety is limited and focused on single risks, we attempted to fill the knowledge gap by developing an integrated risk analysis of UPS to understand risk resilience and improve risk management. From the perspective of the UPS system, four latent factors were identified: natural environment, economic environment, facilities and equipment, and physical structure. Seventeen resilience indicators subsumed under the factors were selected based on resilience concepts. A questionnaire was designed to gather opinions on the relative importance rating of the resilience indicators. SPSS and AMOS software were enlisted to build a structural equation model (SEM), validate the data and model, and calculate the path coefficients and index weights to test four hypotheses. The SEM model results were employed to develop a holistic resilience enhancement strategy under a four-phase framework: before, during, after, and long-term, and under four latent factors. The resilience enhancements can optimize UPS disaster prevention, rescue and evacuation, mitigation, and response management.