Resilience-Based Planning for Urban Infrastructure in Post-Disaster Recovery

Abstract

Urban infrastructure systems are more susceptible to disasters, which requires resilience-centred recovery planning models that incorporate measurement measures, prioritisation measures, governance frameworks, and equity measures. However, the available research base is still disjointed in terms of defining resilience concepts in the context of infrastructure recovery following the occurrence of a disaster. This scoping review aims to outline resilience-based planning frameworks to support recovery of urban infrastructure following a disaster, and in particular, focus on resilience indicators, decision support frameworks, governance issues, and equity concerns. A methodological scoping review was performed based on the traditional methodological frameworks and the PRISMA-ScR guidelines. The peer-reviewed articles related to post-disaster infrastructure recovery and decision frameworks related to resilience were determined and analysed through thematic analysis. The findings show that recovery time, functionality curves, and resilience index are the most common ways of measuring resilience. The recovery prioritisation is often done using network optimisation, multi-criteria decision analysis, simulation modelling, and artificial intelligence methods. Integration of equity aspects and modelling of cross-sector interdependencies are, however, limited. The issues of governance and data are common in the press. As much as resilience-based recovery planning has gone a long way in computing sophistication, a deeper combination of equity, interdependency modelling, standardised metrics, and governance systems is necessary to have holistic and viable urban infrastructure resilience. Furthermore, governance mechanisms should be better aligned with computational models to ensure that theoretical approaches are effectively translated into practice. The study also highlights the need for validation through real-world disaster case studies rather than relying solely on simulated data. Finally, fostering cross-sector collaboration among engineers, planners, policymakers, and data scientists is essential for developing comprehensive and practical resilience strategies.