Abstract

Recovery after disasters is becoming a more prominent focal area of research as the geography literature on disaster management embraces a resilience approach. The damaging impacts of natural disasters on individuals are often compounded by problems and failures in managing recovery after the event. Such problems and failures in recovery take on specific dimensions when disaster events damage the well-established and well-functioning but costly infrastructure and built environments of affluent urban societies. In these circumstances, the extent and nature of property damage combines with the specific pattern of economic and institutional resources available and the disaster recovery management applied to shape the long-term recovery process. As such events become more common and costly, it is important to develop systematic knowledge of how to have a successful and organized recovery process, and, curiously, especially in the case of developed countries. There is a need for a better understanding of what constitutes a successful recovery process, what happens with this process, what long-term recovery is, and how to use the process to mitigate future disasters. The purpose of this research is therefore to compare and contrast long-term recovery planning and management following major disasters in order to identify common lessons, challenges, and ways to mitigate future losses and damages. Although recovery is not everywhere managed the same, there are important lessons that can be learned from the experiences of others. In particular, it is worth identifying the effects of local institutions on recovery and the learning processes that occur. This research seeks to understand and assess disaster recovery in urban communities by examining the relationship between disaster resilience, housing and insurance. This dissertation addresses five research questions, which are addressed in separate chapters, each of which will be published separately: (1) How to assess urban resilience policies supporting disaster risk reduction approaches? The 100 Resilient Cities (100RC) was launched by the Rockefeller Foundation to build worldwide resilience. An evaluation of each member city Resilient Strategies plan took place using directed and summative content analysis to determine whether or not vulnerability and risk narratives were applied in its disaster risk reduction approaches. The results reveal the differences produced among member cities due to the role of actors and power expressed in the policy design and implementation. The overall findings suggest that the 100RC program has not fundamentally addresses issues related to the Sendai Framework for Disaster Risk Reduction goals to reduce disaster risk and vulnerabilities. While many members identified many disaster risks and challenges among shocks and stresses, most were overlooked when designing and implementing key policies for urban resilience. This research was published as a journal article in a special publication focused on reviewing the five-year progress of the Sendai Framework for Disaster Risk Reduction implementation for insight into lessons and planning (Hofmann Zavareh, 2021). (2) How do urban-rural linkages in sustainability transitions impact disaster recovery management and recovery? Analysis of urban-rural linkages in recovery from the earthquake events in Christchurch, New Zealand reveal how desired transformations were entangled in rural, national and international linkages. Three key findings are found; (1) the elements in urban-rural linkages framework are interconnected; (2) the relationalities assumed in the framework do not always hold, and (3) emphasis on urban-rural linkages may obscure other geographies of recovery. This reveals the complexity of the task to map spatial flows, linkages and partnerships among urban, peri-urban and rural areas managing transition pathways for sustainable development. This research was published as part of a special peer-reviewed book publication focused on Rural-Urban Linkages for Sustainable Development edited by Armin Kratzer and Jutta Kister with Routledge (Winder & Hofmann Zavareh, 2020). (3) How to analyze natural disaster damage for specific localized regions to obtain calculations of losses for communities managing recovery using economic models? Micro-level assessments of regional and local disaster impacts in tourist destinations provide the opportunity for economic geographers to assist in calculating precise damage assessments at small regional scales that in turn support the tourism sector and other inter-dependent economies facing reconstruction challenges after disasters. To calculate precise damage assessments, a micro-level assessment model is developed. The island of Dominica is chosen as an example for the model using statistical data from the tourism sector to outline and detail the consequences of a disaster specifically for communities. The results highlight the importance of damage assessments on a small-scale level needed for communities to better understand impacts for residents and the local tourism sector. Only after identifying regional impacts, it is then possible to apply adequate disaster recovery financing needed for residents and the tourism sector recovery. This research was published in the Tourism Geographies journal as part of the Tourism in Changing Natural Environments special publication (Schmude et al., 2018). (4) How to measure long-term community housing recovery using dynamic economic resilience? The research assesses long-term housing recovery and community resilience in the case of Broadmoor, a community located in New Orleans. The community long-term housing measurement is calculated using housing recovery scenarios (dynamic economic resilience). The dynamic economic resilience scenario results provide an indication as to how significant implementation of new disaster recovery policies and procedures can be centered on a more efficient handling of applications for building permits, as well as financial claims for rebuilding or buy-outs, and a more effective management of constrained reconstruction resources for community resilience rebuilding. These results also support recent Munich Re disaster risk modeling studies to improve flood protection in New Orleans. This case demonstrates the role of measuring long-term housing is necessary to better understand the housing recovery processes in different market types. The Broadmoor case also highlights that the speed of recovery was greatly influenced by adopting a community-based approach to managing local and regional resources. This research has been accepted for publication as a journal article in Environmental Hazards (Zavareh & Winder, 2021). (5) What is the role of insurance in managing overall community recovery and housing resilience? The role of insurance, and government buy-outs in recovery are explored in two case study communities (Broadmoor, New Orleans and Avonside, Christchurch). Analysis of case studies using a framework based on “Build Back Better” demonstrating the role of insurance embedded in the scale of long-term housing recovery processes in different market types. Regardless of how the financing or insurance scheme was employed, the most significant factor appears to be the rate (time compression) at which households were able to successfully access and implement financial resources. These two aspects of time compression are interconnected for the success of financing recovery schemes. Successive events or extreme events as seen in both cases, placed considerable burdens on complex institutional systems (local, state, national) that are often disruptive in a nonlinear recovery process. The cases highlight the speed of recovery as the main influencer of long-term housing recovery, given that personal liability is rather manageable if able to access funding for rebuilding efforts. This suggests that a reconceptualization of what exactly community housing resilience is, is needed as it relates to the field of disaster recovery. Here resilience is the opposite of simply rebuilding, contesting the current housing recovery paradigm in “Build Back Better” and disasters research. This research is currently under review for publication. There is still much to be learned about disaster resilience, sustainability transitions, measuring disaster damages and losses, as well as housing recovery for long-term community resilience. Future research should aim to provide more robust modeling and attempt to bridge the gaps in literature and knowledge in collaboration with community stakeholders of post-disaster recovery.