Build Equitable Community Resilience in a Changing Climate by Integrating Multi-hazard Risk and Social Vulnerability Throughout Local Networks of Plans (Gulf Research Program Early-Career Research Fellowship)

Duration: 2023–2026

Funding Agency: National Academies’ Gulf Research Program

Funding Amount: $76,000

PI: Siyu Yu

Co PIs: n/a

Postdoc: n/a

Graduate Research Assistants: n/a

Undergraduate Research Assistants: n/a

Abstract:

Siyu Yu is an assistant professor in the Department of Landscape Architecture and Urban Planning and a core faculty member with the Hazard Reduction and Recovery Center at Texas A&M University. Her experience spans land use, plan integration, and resilience issues in the United States, principally in the Gulf Coast region, as well as internationally in the Netherlands and Japan. She aims to increase multihazard resilience and social equity in an era of climate change by investigating relationships among community networks of land use and development plans and policies related to social and physical vulnerability to natural hazards.

Climate-LEAD: Climate Effects on Localized Environmental Health Disparities in Overburdened Texas Communities Along Gulf Coast

Duration: 2023–2026

Funding Agency: National Academies’ Gulf Research Program

Funding Amount: $1,499,990

PI: Lei Zou

Co PIs: Wendy Jepson, Heng Cai, Qingsheng Wang, Shankar Chellam, Qi Ying, Natalie Johnson, Michelle Meyer, Siyu Yu, Itza Mendoza-Sanchez

Postdoc: n/a

Graduate Research Assistants: n/a

Undergraduate Research Assistants: n/a

Abstract:

This project will develop fine-scaled databases, models, and tools to predict near-, mid-, and long-term impacts of climate change-intensified air pollution and water insecurity on health disparities in overburdened Texas communities along the Gulf Coast. Southeast Texas communities have long borne the brunt of poor localized air and water quality, partially due to emissions from petrochemical facilities and frequent coastal hazards. Ongoing climate change will cause more extreme events, exacerbating environmental hazards and health crises in these already overburdened communities. This necessitates an urgent effort to quantify future environmental health disparities under climate change in these communities to inform mitigation strategies. The databases, models, webGIS, and strategies produced through this project will guide stakeholders to strengthen health resilience to environmental hazards under climate change. 

FIRE-PLAN: Stakeholder-driven Challenges and Opportunities for Wildfire Mitigation and Preparedness

Duration: 2023–2025

Funding Agency: National Science Foundation (#2341679)

Funding Amount: $199,812

PI: Siyu Yu

Co PIs: James Tate, Jason Moats, Carlee Purdum, Tara Goddard, Matt Malecha

Postdoc: n/a

Graduate Research Assistants: n/a

Undergraduate Research Assistants: Tyler Eutsler (2023)

Abstract:

Wildland fire events have particularly significant impacts on communities and ecosystems in rural areas. Many residents in these areas lack the financial resources to cope with and mitigate the impacts of wildland fire events. This context is particularly the case in much of the Southern United States where social and cultural contexts present unique challenges for disaster response and mitigation. This project develops plans to investigate the impacts of wildland fire in the growing wildland-urban interface (WUI) in the Southern United States and contributes to the understanding of the unique dynamics in this critical zone. This research provides both scientific and practical insight to advance the discourse on wildland fire events as a mechanism to enhance community resilience. The project uses a stakeholder driven approach to collate data and resources as a foundation for continued scientific investigation of increasingly prominent yet still insufficiently understood issues surrounding wildfire hazards and human settlement.

This project involves convening and moderating conversations among a range of researchers, practitioners, and other stakeholders to discuss wildland fire risk and explore key issues for successfully mitigating, managing, and living with wildland fire hazards in the Southern U.S. The research team gathers information on current wildfire plans, regulations, and administrative and communications structures in the region to better understand governance as related to wildland fire risk and investigate potential risks of wildfire to the built environment, response systems, and the health of responders and local communities. The research objectives are to: (1) identify key challenges to wildland fire mitigation in the South through practitioner and academic discussions; (2) assess the integration of wildland fire risk management in plans and regulations in the Southern United States; and (3) understand community resilience through preparedness and response planning and coordination of public-private stakeholders to enhance healthcare access before, during and after a wildfire. The geographic focus on the U.S. South reflects the researcher team’s broader intent to augment wildfire-related knowledge and capabilities of understudied and potentially underprepared regions as climate change amplifies risk and uncertainty.

Collaborative Research: FW-HTF-P: Assistive Artificial Intelligence for Diversifying and Reskilling the Disaster Management Workforce of the Future

Duration: 2022–2024

Funding Agency: National Science Foundation (#2222091)

Funding Amount: $100,000

PI: Amir Behzadan

Co PIs: Theodora Chaspari, Michelle Meyer

Postdoc: n/a

Graduate Research Assistants: n/a

Undergraduate Research Assistants: n/a

Abstract:

Disaster impacts, which have become more frequent and severe due to climate change, disproportionately hurt vulnerable populations, including women, communities of color, people with disabilities, income-challenged communities, and more generally those who are not able to advocate for themselves. People from these populations are also poorly represented in the disaster-management profession. This fact raises risks that disaster-management practices do not align with the needs of the broader community, and that biases in hiring and resource allocation will reinforce these vulnerabilities. The goal of this project is to increase disaster-management job opportunities for people from these vulnerable groups. Through connecting residents, community leaders, and state and local authorities, this project will result in new knowledge about how human-centered artificial intelligence (AI) can transform the disaster-management profession by contributing to the diversification and reskilling of the workforce, ultimately augmenting human capabilities, and leading to culturally sensitive teams and equitable disaster-management practices.

The technical aims of the project center around a series of interconnected planning activities that foster a convergent research roadmap, develop fundamental research concepts, and stimulate research capacity that address technological, human, societal, and economic dimensions of the field of disaster management. The project team will study, formalize, and demonstrate the potential of AI to promote diversity and inclusion in disaster-management workforce and practices. Through active participation of stakeholders who will form an advisory board, the project team will engage residents and leaders from disaster-prone communities, state and local disaster-management agencies, and domain experts and researchers to develop a comprehensive roadmap that will guide the design, testing, and dissemination of assistive AI technologies for the disaster-management profession. Planning activities will include a workshop on diversity and inclusion in disaster management, a stakeholder meeting and demonstrations, and research working groups and collaboration meetings. Together, these activities will help meet three research objectives: (1) Facilitate multidisciplinary research and stakeholder partnerships that employ the joint perspectives, methods, and knowledge of disaster management, learning sciences, computer science, engineering, workforce training, and the social sciences; (2) Impart deeper understanding of human-AI partnership in disaster management that can augment (not replace) human workers, including consideration of workforce diversity and how to impart skills needed to interact with AI; and (3) Understand, anticipate, and explore ways of mitigating potential technological and societal risks resulting from AI integration into disaster-management workforce training and reskilling.

Heat-Related Health Risk Assessment and Mitigation for Aging Populations in Public Housing: A Community-Individual Environment-Health Nexus

Duration: 2022–2027

Funding Agency: DHHS-NIH-National Institute of Minority Health and Health Disparities

Funding Amount: $2,668,886

PI: Dongying Li

Co PIs: Robert Brown, Chanam Lee, Jason Maddock, Huiyan Sang

Postdoc: n/a

Graduate Research Assistants: Yue Zhang, Xiaoyu Li

Undergraduate Research Assistants: n/a

Abstract:

Although older adults in public housing face serious threats to their heat-related health, current assessment and mitigation frameworks neglect physiological conditions and place-based infrastructural and social inequalities. Our long-term goal is to develop quantifiable measures and dose-response relationships between the density and characteristics of urban green infrastructure (GI) and heat-related health outcomes for older adults, which can inform community planning and resilience policies that support aging in place during current and future climate conditions. Our objectives are to: 1) assess heat-related health risks for older adults in public housing neighborhoods; 2) determine the effects of green infrastructure on micrometeorological conditions and heat stress; and 3) evaluate the extent to which neighborhood GI mitigates heat-related health risks via emotional, cognitive, and social pathways. Our central hypothesis is that neighborhood GI characteristics are associated with a reduced risk of heat-related illness for older adults in public housing. To achieve Aim 1, we will perform heat-related health risk assessments using the population vulnerability framework, which integrates exposure, sensitivity, and adaptive capacity. Biometeorological exposure will be evaluated based on a novel human heat stress model that accounts for the physiology of older adults; sensitivity and adaptivity will be assessed using social and infrastructural stressors. To achieve Aim 2, we will develop 3-dimensional measures of GI characteristics using remote sensing data and street-level imagery and video classifications and identify inter- and intra-neighborhood GI attributes that relate to micrometeorological parameters and heat stress in older adults. To achieve Aim 3, we will conduct a 2-wave panel survey with multi-stage sampling of older adults in public housing neighborhoods in Houston and Chicago. By comparing baseline measures collected in the spring wave with those during heat conditions in the summer wave, we will assess the sociopsychological pathways through which neighborhood GI is associated with heat-related health/behavioral outcomes and subjective well-being. The research proposed in this application is innovative because it develops heat-related health risk assessments that integrate a novel age-specific human heat-stress model. It also focuses on GI as a modifiable risk factor and adopts a socioecological perspective to elucidate the extent to which individuals’ interaction with their neighborhood’s green infrastructure can moderate heat-related health risks via emotional, cognitive, and social pathways. The proposed research is significant because it is expected to provide strong scientific justification for heat assessment and mitigation frameworks that clarifies the complex transactions between the community-level socioenvironmental infrastructure and an individual’s health. Ultimately, such knowledge has the potential to offer new public health and environmental planning policies that enhance community resilience and promote climate equity.

Southeast Texas Urban IFL: Equitable solutions for communities caught between floods and air pollution

Duration: 2022–2027

Funding Agency: Department of Energy

Funding Amount: $17,000,000

PI: Michelle Meyer

Co PIs: Dongying Li, Nathanael Rosenheim, Galen Newman, Siyu Yu, Jaimie Masterson, John T. Cooper Jr, Jeewasmi Thapa

Postdoc: n/a

Graduate Research Assistants: Farzana Ahmed, Jenna Beyer, Lidia Mezei, Hyewon Yoon, Heather Wade

Undergraduate Research Assistants: n/a

Abstract:

This Urban Integrated Field Laboratory (IFL) is in Southeast Texas (SETx). The long-term goals for the SETx-UIFL are to provide quantitative understanding of projected climate change impacts in a way that is generalizable to other regions, and to improve the practice of resilience science and community resilience through new and generalizable theories of change validated in SETx-UIFL. To achieve these goals, the SETx-UIFL coordinates numerous disciplines, scholars, and community stakeholders toward the short-term goals of 1) integrating new data, methods, and models about the interactions among natural, human-built, and social systems; 2) increasing our understanding of interdependencies, mutual benefits, and trade-offs of different wellbeing outcomes for humans and the environment; 3) co-producing knowledge with stakeholders; and 4) centering concepts of social equity in urbanized regions across spatial and temporal scales.

Building Small Town and Rural Resilience Through Equity-Informed Land-Use Planning and Policy

Duration: 2022–2024

Funding Agency: National Academies’ Gulf Research Program

Funding Amount: $298,982

PI: Michelle Meyer (Formally Andrew Rumbach)

Co PIs: Jaimie Hicks Masterson, Matthew Malecha, Siyu Yu, Noel M. Estwick, Joseph DeAngelis

Postdoc: n/a

Graduate Research Assistants: Erika Koeniger

Undergraduate Research Assistants: n/a

Abstract:

This project focuses on increasing the disaster and climate change planning capacity of small towns and rural communities in the Gulf Coast, and strengthening the capacity of the planning Community of Practice to address hazards and climate change in ways that also increase equity for communities of color and low-income communities in these places. This project will develop four disaster and climate change planning tool “packages,” covering Risk Analysis, Housing Vulnerability, Plan Integration for Resilience Scorecard for Small Towns, and Integrating Hazards into Comprehensive Plans.

EAGER: SAI: Synchronizing Decision-Support via Human- and Social-Centered Digital Twin Infrastructures for Coastal Communities

Duration: 2021–2024

Funding Agency: National Science Foundation (#2122054)

Funding Amount: $298,982

PI: Xinyue Ye

Co PIs: Lei Zou, Galen Newman, Youngjib Ham, David Retchless

Postdoc: Dr. Cuiling Liu

Graduate Research Assistants: n/a

Undergraduate Research Assistants: n/a

Abstract:

Strengthening American Infrastructure (SAI) is an NSF Program seeking to stimulate human-centered fundamental and potentially transformative research that strengthens America?s infrastructure. Effective infrastructure provides a strong foundation for socioeconomic vitality and broad quality of life improvement. Strong, reliable, and effective infrastructure spurs private-sector innovation, grows the economy, creates jobs, makes public-sector service provision more efficient, strengthens communities, promotes equal opportunity, protects the natural environment, enhances national security, and fuels American leadership. To achieve these goals requires expertise from across the science and engineering disciplines. SAI focuses on how knowledge of human reasoning and decision making, governance, and social and cultural processes enables the building and maintenance of effective infrastructure that improves lives and society and builds on advances in technology and engineering.

 

Coastal flooding and storms present a growing global challenge. This SAI project focuses on strategies, technologies, mechanisms, and policies for increasing coastal community resilience. The project centers on the use of digital twins ? virtual copies of physical objects and systems that update in real time to match real-world conditions. Digital twins can provide the insights needed to inform resilient decision making in coastal communities. An initial case study is developed through the construction of a digital twin of Galveston Island and portions of other coastal Texan communities. The research adopts a holistic and integrated approach for evaluating, modeling, and testing resilience scenarios. It brings together multiple disciplines including geography, urban planning, landscape architecture, computer science, construction science, and marine science. A participatory and community engagement platform is used to collect ground truth data and gain further in-depth understanding of coastal infrastructure mechanisms at multiple scales. Residents and stakeholders will gain insights into: (1) comparing the pros and cons of different planning efforts; (2) the joint impacts that existing and future planning efforts may have on stakeholders? individual goals and objectives; and 3) the assets and capacities involved with current dynamic sensors used in digital twin-based information modeling. Decision-makers can leverage the capabilities of this platform to test incremental and place-based planning approaches with real-time priorities, policies, and suggested infrastructure changes. Through software and hardware integration, this digital twin serves as a platform for pursuing solutions to coastal infrastructure challenges. The potential reward is high, as more informed decisions and better affordances for inter-agency coordination may lower the costs of maintaining or replacing the coastal resilience protective system. The digital twin-based decision-support framework serves as a catalyst for further research in data-driven decision making by connecting different datasets and by providing training and collaborative research opportunities for local project participants as well as graduate and undergraduate students.

 

This SAI project supports the resilient design, planning, and development of sustainable infrastructure in coastal communities. It integrates physical, cyber, and social infrastructure data into an analytics platform for real-time, dynamic scenario testing for decision support. This digital twin-based decision support system allows (1) collection, compiling and sharing data on physical, cyber, and social infrastructure; (2) engagement of communities to disseminate information and facilitate citizen science; and (3) promoting a human- and social-centered approach for infrastructure planning and integrated social-environment system dynamics modeling in the context of short-term disasters and long-term climate change. The digital, data-driven decision-making framework integrates a variety of data sources, digital modeling and analytics platforms, and participatory-enhanced infrastructure management considerations. It creates a visualized common operating procedure within a digital twin of local circumstances that local residents and decision-makers can use to better reason about the relationships among different planning efforts, including disaster management, new construction, repair, rehabilitation and retrofitting activities, regular maintenance, system performance, and infrastructure additions. The digital platform collects and simulates highly dynamic and massive volumes of independently-acting, reacting, and interacting agents (such as people, vehicles, structures/infrastructure, and institutions) under different policy or hazard response scenarios. Coupled with immersive technologies, the platform allows people to better understand built and natural environment changes by visualizing how planning and infrastructure alteration and addition can alter resilience levels (positively or negatively). Local knowledge is combined with expert evaluation across multiple flood scenario types and infrastructure change scenarios to test different resilience levels to urban change. By revealing fundamental design and planning principles with implications for action, the research improves U.S. infrastructure for disaster resilience, in support of science-based measures for accessible, affordable, and universal geospatial design interventions.

CAREER: Estimating and Addressing Disaster Survivors’ Unmet Needs: A Social Vulnerability and Social Infrastructure Approach

Duration: 2020–2025

Funding Agency: National Science Foundation (#1944329)

Funding Amount: $534,985 plus $16,000 Research Experience for Undergraduate Supplement and $50,000 INTERN Supplement

PI: Michelle Meyer

Co PIs: n/a

Postdoc: Carlee Purdum

Graduate Research Assistants: Mason Alexander-Hawk, Joy Semien, Haley Yelle

Undergraduate Research Assistants: Jordan Vick (2021), Asad Abbas (2021), Saul Romero (2021), Adrian Rodriguez (2021), Haley Yelle (2020–2021), Tyler Easter (2022-2023), Shanelle Trujilio (2023)

Abstract:

This Faculty Early Career Development (CAREER) grant will further the understanding of how communities can effectively leverage philanthropic resources to meet housing-recovery needs after disasters. As disaster costs and disaster displacement increase, governmental assistance to individuals and private insurance often are inadequate to ensure full recovery for all affected people. Philanthropic resources can address unmet needs of disaster survivors if used effectively and efficiently. Locally led nonprofit “long-term recovery groups” are often charged with distributing these resources, but little is known about these organizations’ efforts or what makes their operations more or less effective in promoting community recovery and resilience. This project will assess how philanthropic housing-recovery practices affect individual unmet needs, post-disaster equity, and the overarching philanthropic ecosystem of affected communities. This project will use the research results to inform and test a training program for locally based nonprofits, government officials, and foundations that will improve their effectiveness in managing philanthropic resources for disaster recovery. Educational outcomes also include undergraduate research experiences to foster under-represented student engagement in STEM and graduate student internships coordinated with disaster recovery nonprofits to further their data management skills.

This project builds on past research into nonprofit operations and housing recovery, introducing a new approach that integrates both. Recent research indicates that governmental aid processes correlate with increased economic and racial inequality after disasters. At the same time, social “infrastructure”, like local nonprofits and especially long-term recovery groups, provide recovery support to socially vulnerable populations who often have difficulty accessing governmental disaster aid. Yet, philanthropic response to disaster is understudied. This is the first attempt to quantify long-term recovery groups’ effectiveness and to identify the factors that increase their effectiveness in supporting housing recovery across the United States. The project work will include the development and analysis of a new dataset of nonprofit disaster recovery operations using secondary and primary data from recent disasters. While focused on long-term recovery groups, the findings from this work will have implications for non-disaster situations. The project will increase understanding of how practices undertaken in disaster situations can be institutionalized into organizations, thus addressing how sudden change in mission and capacity affects organizational operations. The research findings will also point to how disaster resilience can be integrated into daily operations of all types of nonprofits and how resilience affects their overarching operation and mission. Further, this work will evaluate the effects of philanthropic response to disasters on a community’s broader philanthropic safety net.

Center for Risk-Based Community Resilience Planning: A NIST-Funded Center of Excellence

Duration: 2015–2025

Funding Agency: National Institute of Standards and Technology (NIST)

Funding Amount: $20,000,000

PI: John van der Lindt (Colorado State University)

Co PIs: Includes 90 researchers across 12 universities. The HRRC team is Walter Gillis Peacock, Shannon Van Zandt, Nathanael Rosenheim, Maria Koliu, Maria Watson, Michelle Meyer

Post-Doc: Dr. Xu Han

Graduate Students: Kijin Seong (2015-2020), Donghwan Gu (2015-2020), Mohammad Aghababaei (2017-2021)Heather Wade (2018-2022), Wayne Day (Current), Michelle Stanley (Current)

Abstract:

Working with NIST researchers and partners from 12 universities led by Colorado State University, the Community Resilience Center of Excellence, awarded in February 2015, will accelerate the development of system-level models and associated databases to support community resilience decision making. The center’s multi-disciplinary team includes experts in engineering, economics, data and computing, and social sciences. Research will support development of metrics and tools that will help local governments decide how to best invest resources intended to lessen the impact of hazards on buildings and infrastructure systems and how to recover rapidly and minimize community disruption.

The centerpiece of the center’s effort is IN-CORE — the Interdependent Networked-Community Resilience Modeling Environment. Built on an open-source platform, the computer model and associated software and databases will incorporate a risk-based approach to decision-making that will enable quantitative comparisons of alternative resilience strategies.

IN-CORE will provide the scientific basis for developing resilience metrics and decision tools to support community resilience of the built environment. The research will include evaluating cascading effects among interconnected infrastructure. In addition, models and tools will integrate social systems vital to the functioning and recovery of communities — health care delivery, education, social services, financial institutions and others.

The center’s multi-disciplinary team includes experts in engineering, economics, data and computing, and social sciences from Colorado State University, University of Illinois at Champaign Urbana, University of Oklahoma, Rice University, Oregon State University, Texas A&M University, University of South Alabama, University of Colorado Boulder, California Polytechnic at Pomona, University of Washington, University of Kansas and Iowa State University.