Search NASA⌕ Search

SEARCH · Search NASA

Results for “Social vulnerability”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Method for Measuring Coupled Individual and Social Vulnerability to Environmental Hazards

Although models of social vulnerability to environmental hazards are commonly developed to support policy interventions in emergencies and disasters, their utility is hindered by a lack of contextual information on individuals exposed to and affected by hazards. We develop a novel approach to model social vulnerability that couples individuals and their varying forms of protective capacity with the social fabric of the communities in which they reside. The backbone of our model is the Public-Use Microdata Sample (PUMS), a product of the U.S. Census Bureau that preserves a representative sample of completed responses to the American Community Survey (ACS). The PUMS enables us to understand the full range of individual protective capacities against a hazard in an exposed area, which we term individual vulnerability profiles (IVPs). In this case, we examine IVPs in the Coney Island-Brighton Beach section of New York City, which suffered severe impacts during Hurricane Sandy in 2012. To manage the large number of unique IVPs in Coney Island-Brighton Beach, we perform a segmentation analysis to generalize them into thematic cohort vulnerability profiles (CVPs) representing a typology of vulnerable people in Coney Island-Brighton Beach during Sandy. From synthetic populations of CVPs, we then estimate how individuals in varying housing types were coexposed to Sandy at the census tract level by classifying these areas into community social vulnerability profiles (SVPs). Our results provide a topology of social vulnerability that simultaneously links individual, community, and population-wide concerns, enabling a more holistic understanding of resources and interventions beneficial to human security during events like Sandy than is attainable with area-level metrics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

An Interpretable Index of Social Vulnerability to Environmental Hazards

Index-based measures of social vulnerability to environmental hazards are commonly modeled from composites of population-level risk factors. These models overlook individual context in communities' experiences of environmental hazards, producing metrics that may hinder spatial decision support for mitigating and responding to hazards. This paper introduces an interpretable, high-resolution model for generating an individual-oriented social vulnerability index (IOSVI) for the United States built on synthetic populations that couples individual and social determinants of vulnerability. The IOSVI combines an individual vulnerability index (IVI) that ranks individuals in an area’s synthetic population based on intersecting risk factors, with a social vulnerability index (SVI) based on the population’s cumulative distribution of IVI scores. Interpretability of the IOSVI procedure is demonstrated through examples of national, metropolitan, and neighborhood (census tract) level spatial variation in index scores and IVI themes, as well as an exploratory analysis examining risk factors affecting a specific sub-population (military veterans) in areas of high social and environmental vulnerability.

Tuccillo, Joe↗
NASA NTRS2021

Spatiotemporal Associations Between Social Vulnerability, Environmental Measurements, and COVID-19 in the Conterminous United States

This study summarizes the results from fitting a Bayesian hierarchical spatiotemporal model to coronavirus disease 2019 (COVID-19) cases and deaths at the county level in the United States for the year 2020. Two models were created, one for cases and one for deaths, utilizing a scaled Besag, York, Mollié model with Type I spatial-temporal interaction. Each model accounts for 16 social vulnerability and 7 environmental variables as fixed effects. The spatial pattern between COVID-19 cases and deaths is significantly different in many ways. The spatiotemporal trend of the pandemic in the United States illustrates a shift out of many of the major metropolitan areas into the United States Southeast and Southwest during the summer months and into the upper Midwest beginning in autumn. Analysis of the major social vulnerability predictors of COVID-19 infection and death found that counties with higher percentages of those not having a high school diploma, having non-White status and being Age 65 and over to be significant. Among the environmental variables, above ground level temperature had the strongest effect on relative risk to both cases and deaths. Hot and cold spots, areas of statistically significant high and low COVID-19 cases and deaths respectively, derived from the convolutional spatial effect show that areas with a high probability of above average relative risk have significantly higher Social Vulnerability Index composite scores. The same analysis utilizing the spatiotemporal interaction term exemplifies a more complex relationship between social vulnerability, environmental measurements, COVID-19 cases, and COVID-19 deaths.

spatial epidemiology↗
DOE OSTI2024

Historical Power Outages of the United States and the Social Vulnerability Index

Several works have been documented in the literature to study the societal effect of power outages and to analyze their correlation with the Social Vulnerability Index (SVI). Because the SVI is calculated based on the summed rank of multiple vulnerability factors for environmental hazards, it can include factors irrelevant to power outages caused by extreme events. This work performs a detailed correlation analysis for social vulnerability and power outages by considering different SVI themes (e.g., socioeconomic status, household composition, racial and ethnic minority status, and housing and transportation) and power outages with and without a threshold for extreme weather events. Although there is some relation between specific themes and aspects of power outages and the SVI in the results, there is no strong distinction between power outage durations and low vs. high SVI values. These results point to the need for further research that grounds the specific factors and methods used to develop SVI and related indices to energy services and power systems disruptions.

Bhusal, Narayan↗
DOE OSTI2023

Social Vulnerability and Beacon Hill Resilience Hub Network [Slides]

Improving community resilience to climate change impacts is a core goal of the Beacon Hill stakeholder task force. Developing a network of resilience hubs in the community is a strategy the task force is pursuing to build this resilience. This technical assistance aims to assist the task force in their resilience hub network planning by: identifying hazards that the resilience hubs may address; providing background information on social vulnerability and climate impacts; identifying populations in Beacon Hill who are at risk to disproportionate climate impacts due to social isolation and physical vulnerability characteristics (e.g., lack of transportation or internet); and identifying the potential role of resilience hubs that align with best practices for reducing social vulnerability to climate impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Incorporating Social Vulnerability Variables in Measures to Quantify Access to Opportunities

Herein this study quantifies access to travel opportunities to understand what societal factors are linked with local access and to identify communities with reduced access. We introduce a method to compare accessibility across all census tracts in the United States that can be used across geographically diverse communities ranging from sparsely to densely populated areas. This study considers six key opportunities which we consider essential for all communities (grocery stores, public schools, daycares, primary care doctors, pharmacies, and parks), and six additional destinations which can be viewed as a social safety net (homeless shelters, women’s shelters, food pantries, libraries, vocational schools, and banks). We quantify accessibility to these opportunities within a 15 min walk, transit trip, bicycle ride, and automobile drive for every census tract in the United States, and observe a decrease in vehicle miles traveled and vehicle ownership in tracts with increased walkability. Through analysis at the census tract level, this study incorporates variables of social vulnerability with these cumulative opportunity metrics to better understand diminished accessibility as attributed to social and racial inequities. As example findings, we find decreased access to financial services in communities with high minority and limited English speaking populations, no apparent change in access for childcare in communities with high percentages of single-parent families, and potentially increased or decreased access to women’s healthcare resources for Black women depending on the travel mode.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Social vulnerability and power loss mitigation: A case study of Puerto Rico

The increasing occurrence of extreme weather events urges us to reevaluate the resiliency and vulnerability aspects of our most critical infrastructures — such as power grids — as their failures result in both economic loss and severe human hardship. Seen through the lens of alleviating human suffering, it is crucial to be able to identify critical system components of the infrastructure for targeted hardening given resource constraints. This effort is of particular importance in islanded areas such as Puerto Rico where hurricanes are frequent and resources are limited, and where the spatially diverse effects of power loss on human suffering are all the more severe. Recent studies on evaluating infrastructure networks during extreme weather events have taken a simulation based approach that incorporates a variety of component models, such as weather realizations, topological network models, fragility models, and power flow models to estimate expected loss of service. Here, in this work, we expand such a Component Based Event Simulation (CBES) methodology proposed in the literature and integrate it with a social vulnerability modeling component. This paradigm-advancing approach of synthesizing the cutting edge capability of power network modeling and the social impacts of the power transmission network failure is demonstrated for the island of Puerto Rico. Our work exemplifies the efficacy of this integrated modeling framework in developing a decision metric for targeted transmission line hardening.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Geospatial Capabilities to Couple Hazard and Social Vulnerability Data in Water Distribution Criticality Analysis

A resilience analysis of a water distribution system is greatly enhanced by the integration of up-to-date geospatial data describing the water system, hazards, and surrounding community. The Water Network Tool for Resilience (WNTR), an open-source Python package designed to simulate and analyze the resilience of water distribution systems, was recently updated to incorporate geographic information system (GIS) data into the resilience analysis. This paper describes the GIS capabilities and includes a case study using the drinking water distribution system model for a large city in Pennsylvania. The case study focuses on potential pipe damage from landslides and on pipes that are particularly difficult to repair. The analysis couples data on hazards, social vulnerability, and the location of emergency services to identify and prioritize high-impact critical infrastructure for mitigation. Results demonstrate that pipes can be prioritized for mitigation based on water shortage and vulnerable populations that are affected. In conclusion, the methods can be adopted for general use and are available as part of the WNTR software.

GIS, landslide↗
NASA NTRS2023

Improving Tornado Casualty Predictions in the US With Population Exposure Data and A Modified Social Vulnerability Index

Tornadoes are frequent and widespread events that often account for hundreds of injuries and fatalities, and millions of dollars in damages. Multiple studies have analyzed tornado climatology and associated exposure; however, fewer have focused on predicting fatalities and injuries by coupling geospatial data on tornado characteristics and underlying social and economic vulnerability. In this study, we test the ability of negative binomial regression models to predict tornado-induced injuries and fatalities by coupling data on physical characteristics of tornadoes, exposure of populations, and underlying social vulnerability. We also present a modified spatially weighted social vulnerability index SVI* wt . We used 10-year (2005-2014) tornado data over the continental United States for this analysis. The results of this study indicate that the tornado length, magnitude and nocturnality seem to be the major hazard-related indicators of fatalities (McFadden’s Pseudo- R 2 ranged from 0.01-0.12). Population exposure and SVI* wt are positive and statistically significant in predicting tornado related fatalities and injuries (Pseudo R 2 of 0.11-0.18). Although combining SVI* wt with hazard variables does not substantially improve model fit when compared to adding population exposure, combining SVI* wt , hazard and exposure results in better predictions of both injuries and fatalities (Pseudo R 2 of 0.17) and is also an improvement on previous similar studies.

disaster↗
NASA NTRS2024

Cali Urban Development II: Investigating the Impacts of Land Use Change on Urban Heat and Social Vulnerability in Cali, Colombia

The surface urban heat island (SUHI) effect is an environmental phenomenon resulting in cities with higher temperatures than rural areas due to increased pavement and decreased cooling from vegetation. The city of Santiago de Cali in Colombia faces SUHI challenges exacerbated by land use change. The Cali municipal government agency, Departamento Administrativo de Gestión del Medio Ambiente, and the community organization Fundacion Dinamizadores Ambientales partnered with NASA DEVELOP to evaluate communities in Cali most vulnerable to urban heat. This project illustrated the utility of using NASA Earth observations to evaluate the relationship between land use, temperature, and social factors in Cali, Colombia between 2013 and 2023. The team used Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), and Landsat 9 OLI-2/TIRS-2 to generate land surface temperature (LST) maps in Google Earth Engine through NASA DEVELOP’s Urban Heat Exposure Assessment Tempe 2.0 tool. Cloud cover limited the project feasibility, but it improved with Landsat 9 data. In ArcGIS Pro, the team found that LST was significantly higher in urban areas than in wetlands or forests. Using R Studio, the team ran a principal component analysis and found that health care and green space access were negatively correlated, and Afro-Colombian ethnicity was positively correlated with LST. With knowledge of the most impacted and vulnerable regions, the partner organizations can prioritize establishing healthcare facilities and green spaces in those areas to reduce the impacts of urban heat.

vegetation loss↗
NASA NTRS2023

San Joaquin Valley Health & Air Quality: Evaluating the Overlap of Social Vulnerabilities and Air Quality in the San Joaquin Valley Air Pollution Control District

Little Manila Rising (LMR) is a nonprofit in Stockton, California that has been increasingly concerned by the air pollution in their city and the neighboring San Joaquin Valley (SJV). Geographical factors, climate conditions, and anthropogenic activities, such as agriculture burning and vehicle emissions, contribute to the high levels of air pollution in this region. To visualize the distribution of air pollution and social disparities across the SJV, LMR partnered with NASA DEVELOP. The DEVELOP team used Terra and Aqua MODIS, Sentinel-5P TROPOMI, and CALIPSO CALIOP to observe Aerosol Optical Depth (AOD), Nitrogen Dioxide (NO 2 ), and the vertical distribution of pollutants at varying pollution levels, respectively. Additionally, Suomi-NPP VIIRS provided active fire data. By leveraging NASA Earth observations along with sociodemographic and public health data, the DEVELOP team created maps identifying the areas experiencing the highest vulnerabilities and disparities in pollution exposure. The team found that AOD was slightly higher in agricultural regions, while NO 2 was consistently higher along transportation corridors and urban areas. Wildfires dominated the type of detected active fires, and there was high correlation (R 2 = 0.6924) between active fires and burn permits in agricultural tracts. Furthermore, the team identified both high AOD vulnerability and high NO 2 vulnerability in census tracts in South Stockton, an area that has been historically redlined and disinvested in, and where LMR resides. There was also a moderate correlation between air quality reported from the satellites and in-situ ground monitors. These results will support LMR’s organizing strategies for stricter enforcement of air pollution regulations and increased public health equity for community members.

Agricultural Fires↗
DOE OSTI2026

Housing Unit Level Social Vulnerability Indices for 2010 and 2020

Housing unit level demographic characteristics for SETX counties. Census years 2010 and 2020. These data are in beta testing stage, designed for use with the SETX-UIFL project. Contact Nathanael Rosenheim (nrosenheim@arch.tamu.edu) for more information. Papers using these data should include Nathanael Rosenheim in the development phase and co-authorship discussions.

Rosenheim, Nathanael↗
DOE OSTI2025

Development of the Contamination Distribution Centered Toxics Mobility Vulnerability Index in the Beaumont–Port Arthur Region of Texas

This study advances the Toxics Mobility Inventory (TMI) and the Toxics Mobility Vulnerability Index (TMVI) to develop a new tool to assess the movement of hazardous substances and their implications for vulnerable communities. It emphasizes the need to include contamination distribution variables in such indices to address disproportionate impacts and more accurately reflect vulnerability. The study uses the TMI framework and TMVI methodology in the Beaumont–Port Arthur region of Texas, also integrating contamination distribution considerations into the analysis to develop a new framework and process. The new Contamination Distribution Centered Toxics Mobility Vulnerability Index (CDC-TMVI) consolidates climate change and topography variables into a broader built environment vulnerability category while introducing a contamination sources category. Using ArcGIS Pro and ToxPi tools, the study evaluates 27 geospatial variables across four categories: built environment vulnerability, social vulnerability, health outcomes, and contamination sources. The results indicate significant contributions from contamination and social vulnerability variables, highlighting areas with higher risks of flooding and air pollution. This article advocates for future research and policy efforts to enhance the integration of contamination sources and their spatial distributions into toxics mobility assessments to better protect vulnerable populations. Furthermore, the unique methodology and findings serve as a basis for developing targeted measures and strategic planning to improve environmental health.

contamination↗