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1. Understanding post-disaster population recovery patterns

   https://doi.org/10.1098/rsif.2019.0532  

   Yabe, Takahiro; Tsubouchi, Kota; Fujiwara, Naoya; Sekimoto, Yoshihide; Ukkusuri, Satish V. (February 2020, Journal of The Royal Society Interface)

   null (Ed.)

   Despite the rising importance of enhancing community resilience to disasters, our understandings on when, how and why communities are able to recover from such extreme events are limited. Here, we study the macroscopic population recovery patterns in disaster affected regions, by observing human mobility trajectories of over 1.9 million mobile phone users across three countries before, during and after five major disasters. We find that, despite the diversity in socio-economic characteristics among the affected regions and the types of hazards, population recovery trends after significant displacement resemble similar patterns after all five disasters. Moreover, the heterogeneity in initial and long-term displacement rates across communities in the three countries were explained by a set of key common factors, including the community’s median income level, population, housing damage rates and the connectedness to other cities. Such insights discovered from large-scale empirical data could assist policymaking in various disciplines for developing community resilience to disasters. 

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2. NSF Belmont Forum Collaborative Research: Advancing Resilience in Low-Income Housing Using Climate-Change Science and Big Data Analytics

   https://doi.org/10.17603/ds2-1kpb-dv70  

   Obonyo, Esther; Mutunga, James; Mirhosseini, Homeira (January 2025, Designsafe-CI)

   Project Overview: This NSF-funded project (Award #2019754) is part of the Belmont Forum’s Disaster Risk, Reduction, and Resilience (DR3) initiative, a global effort to assess and mitigate disaster risks through transdisciplinary collaboration. The study investigates strategies to enhance the resilience of low-income communities living in flood-prone and climate-vulnerable regions, with a geographic focus on Brazil, East Africa, and the southeastern United States. The U.S. component centers on coastal and urban communities in Florida, particularly those at risk from flooding and extreme weather events. Research Objectives: Through a transdisciplinary approach, the project integrates machine learning, geospatial analytics, and socio-economic data to: - Assess community-level vulnerabilities to flooding and extreme heat, -Identify barriers to adopting disaster-resilient housing, - Co-design affordable, climate-resilient housing prototypes using sustainable, locally sourced materials. The research aims to support community-informed design strategies and policy recommendations that are adaptable across different socio-economic and geographic contexts. Dataset Description: The dataset contains responses from approximately 500 residents aged 18+ living in low-income, flood-prone neighborhoods in Florida. The survey captures detailed information on: - Housing conditions and infrastructure, - Disaster preparedness and flood risk perception, - Access to services during and after disasters, - Health and economic impacts of extreme weather events, - Community cohesion and recovery strategies. This dataset serves as a resource for researchers, urban planners, emergency response agencies, and policymakers seeking data-driven insights to inform resilient housing design, climate adaptation, and disaster recovery planning. Data Collection and Anonymity: Survey distribution and data collection were conducted in partnership with Centiment, a third-party research company that recruits demographically targeted panels for academic and applied research. For this study, Centiment distributed the survey to residents of low-income, flood-prone communities in Florida, based on geographic and socio-economic criteria specified by the research team. All personally identifiable information (PII), such as IP addresses, email addresses, and precise geolocation data, was removed prior to uploading the dataset to DesignSafe. The dataset has been reviewed to ensure participant anonymity in accordance with DesignSafe data protection policies and applicable ethical standards. 

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3. Disaster reconnaissance framework for sustainable post-disaster materials management

   https://doi.org/10.1016/j.wasman.2023.07.010  

   Yeşiller, Nazli; Hanson, James L.; Wartman, Joseph; Turner, Benjamin; Gardiner, Andrea; Manheim, Derek C.; Choi, Juyeong (September 2023, Waste Management)

   A first foundational assessment is provided for disaster debris reconnaissance that includes identifying tools and techniques for reconnaissance activities, identifying challenges in field reconnaissance, and identifying and developing preliminary guidelines and standards based on advancements from a workshop held in 2022. In this workshop, reconnaissance activities were analyzed in twofold: in relation to post-disaster debris and waste materials and in relation to waste management infrastructure. A four-phase timeline was included to capture the full lifecycle of management activities ranging from collection to temporary storage to final management route: pre-disaster or pre-reconnaissance, post-disaster response (days/weeks), short-term recovery (weeks/months), and long-term recovery (months/years). For successful reconnaissance, objectives of field activities and data collection needs; data types and metrics; and measurement and determination methods need to be identified. A reconnaissance framework, represented using a 3x2x2x4 matrix, is proposed to incorporate data attributes (tools, challenges, guides), reconnaissance attributes (debris, infrastructure; factors, actions), and time attributes (pre-event, response, short-term, long-term). This framework supports field reconnaissance missions and protocols that are longitudinally based and focused on post-disaster waste material and infrastructure metrics that advance sustainable materials management practices. To properly frame and develop effective reconnaissance activities, actions for all data attributes (tools, challenges, guides) are proposed to integrate sustainability and resilience considerations. While existing metrics, tools, methods, standards, and protocols can be adapted for sustainable post-disaster materials management reconnaissance, development of new approaches are needed for addressing unique aspects of disaster debris management. 

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4. Persons Experiencing Homelessness during Extreme Temperatures: Lessons for Promoting Socially Inclusive Adaptive Capacity

   https://doi.org/10.3390/ijerph21080984  

   Cronley, Courtney; Fackler, Amanda; First, Jennifer M; Lee, Sangwon; Tsouris, Iris (August 2024, International Journal of Environmental Research and Public Health)

   Climate change and increasing extreme temperatures present unique challenges to persons experiencing homelessness (PEH), including heightened physical and psychological harm. While green and urban infrastructure has emerged as one possible mitigation strategy, homeless populations are rarely included in municipal disaster planning or infrastructure research. This study used in-depth interviews with PEH (N = 42) during the summers of 2022 and 2023. Questions were designed around phenomenological methods to explore the individuals’ firsthand descriptions of the lived experience of coping during extreme temperatures within a mid-size city in the Southeastern United States. Our findings highlight how social exclusion within the built environment reduces PEH’s adaptive capacity and increases the physical and psychological risks of extreme temperatures, namely through limiting and policing scarce resources and restricting the mobility of PEH. In contrast, public transit provided relief from extreme temperatures. Implications from our findings include the need for attention on inclusive green urban infrastructure, including increased placement and access to shade, public water, mixed-use daytime sheltering models, and the installation of lockers to increase capacity to maintain supplies and gear necessary for enduring extreme temperatures. Findings also highlight the challenges of designing inclusive green infrastructure and the importance of de-stigmatizing homelessness and building more housing and income support to increase adaptive capacity for an entire community in the context of a rapidly warming climate. 

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5. Multiple Dimensions of Resilience: How NEON Supports Ecology and the Research Community in the Face of Compounding Disasters

   https://doi.org/10.3389/fenvs.2022.653666  

   Robinson, Natalie; Barnett, David T.; Jones, Katherine D.; Stanish, Lee F.; Parker, Stephanie M. (March 2022, Frontiers in Environmental Science)

   Quantifying the resilience of ecological communities to increasingly frequent and severe environmental disturbance, such as natural disasters, requires long-term and continuous observations and a research community that is itself resilient. Investigators must have reliable access to data, a variety of resources to facilitate response to perturbation, and mechanisms for rapid and efficient return to function and/or adaptation to post-disaster conditions. There are always challenges to meeting these requirements, which may be compounded by multiple, co-occurring incidents. For example, travel restrictions resulting from the COVID-19 pandemic hindered preparations for, and responses to, environmental disasters that are the hallmarks of resilient research communities. During its initial years of data collection, a diversity of disturbances—earthquakes, wildfires, droughts, hurricanes and floods—have impacted sites at which the National Ecological Observatory Network (NEON) intends to measure organisms and environment for at least 30 years. These events strain both the natural and human communities associated with the Observatory, and additional stressors like public health crises only add to the burden. Here, we provide a case-study of how NEON has demonstrated not only internal resilience in the face of the public health crisis of COVID-19, but has also enhanced the resilience of ecological research communities associated with the network and provided crucial information for quantifying the impacts of and responses to disturbance events on natural systems—their ecological resilience. The key components discussed are: 1) NEON’s infrastructure and resources to support its core internal community, to adapt to rapidly changing situations, and to quickly resume operations following disruption, thus enabling the recovery of information flow crucial for data continuity; 2) how NEON data, tools, and materials are foundational in supporting the continuation of research programs in the face of challenges like those of COVID-19, thus enhancing the resilience of the greater ecological research community; and 3) the importance of diverse and consistent data for defining baseline and post-disaster conditions that are required to quantify the effects of natural disasters on ecosystem patterns and processes. 

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