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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Sarasota Climate: Monitoring Heat and Assessing Heat Vulnerability to Identify Locations for Heat Mitigation Efforts in Sarasota, Florida

The coastal county of Sarasota, Florida, is located within the humid subtropical climate region and experiences an average of 250 days of sunshine every year. The county has large, urbanized communities which are vulnerable to urban heat island (UHI) effects. These rapidly growing communities contribute to the increasing surface temperatures and placing more residents at risk of heat-related illness. In partnership with Sarasota County Sustainability, the Sarasota Climate team utilized Earth observation data from NASA Landsat 8 and Landsat 9’s Thermal Infrared Sensors (TIRS), and the International Space Station’s Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) to model UHI effects within the county during the Summer for the last five years, 2019 to 2023. Data analysis with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) and Urban Heat Exposure Assessment Tempe 1.0 (UHEAT 1.0) models and within ModelBuilder produced maps that identified the land surface temperature (LST) variance within the county, the regions that are most susceptible to extreme heat, and areas least capable of mitigating the effects of UHI. The results revealed that heat intensity varies significantly across Sarasota County with the highest temperatures in the more developed western part of the county. Additionally, the team identified that there are at least three vulnerable communities that exist in high-heat regions, including North Sarasota, Venice, and North Port. These regions have an overlap between socioeconomic sensitivity and environmental hazard that indicate a high priority in future heat mitigation efforts.

Remote sensing↗
DOE OSTI2025

Corrigendum to ‘Under-capacitated and over-powered? Rural austerity and asymmetrical negotiating relationships in US wind energy development’ [J. Rural Stud., 119 (2025) 1–14]

The authors regret that there is an incomplete sentence in the abstract of the article, and request that the portion “, and counties incre” be deleted from the abstract (found at the end of the sentence beginning with “However …”). The portion to be deleted is underlined and bolded below. The authors would like to apologise for any inconvenience caused. Current abstract: Though rural local governments are central actors in renewable energy development, local governments in the United States (US) remain systematically under-funded. This paper considers what the manifestations of austerity in local governments broadly and rural localities specifically mean for renewable energy development and for energy transitions. Drawing on a survey of 262 elected county officials with experience with wind energy in eight US states, this paper asks how local officials understand the impacts of wind development, how local governments are involved in wind energy negotiations, how the resources and expertise needed to navigate negotiations are distributed among counties, and analyze the relationship between local capacity, access to resources, and involvement in negotiations. We find that local officials express simultaneously affective and material concerns with the impacts of wind development and see negotiations with the developer as central to realizing local benefits. However, the expertise and staffing needed to negotiate with developers is less accessible to poorer or sparsely populated counties, and counties with lower overall revenues have narrower scopes of negotiation, and counties incre. Our results suggest that uneven rural capacity heightens an already asymmetrical relationship between localities and developers. In analyzing how infrastructure developments are shaped by relationships between localities and developers that are conditioned by austerity and (under)capacity, this paper contributes to and bridges scholarly discussions on rural austerity, rescaling, and renewable energy transitions. These results challenge conventional wisdoms around centralizing energy siting processes, contextualize popular and academic debates about opposition to renewable energy development, and highlight the need for rural reinvestment to realize meaningfully participatory energy developments.

Elmallah, Salma↗
DOE OSTI2026

Who is benefiting from the dramatic decline in U.S. cancer mortality? Place-based evidence of disparities in rates of improvement

After decades of increasing cancer mortality, U.S. rates declined from 1991 to 2019, a 32% decrease. we investigated rates of cancer mortality improvement across 2954 counties and selected characteristics associated with mortality improvements. Data was 21,381,009 county-level neoplasm deaths gleaned from death certificates via CDC WONDER. Analytical techniques included GIS and Moran’s I, OLS, GWR models, and trend comparisons. Counties with the greatest improvement (reduction) in cancer mortality tended to be coastal, higher-income, metropolitan locations. OLS model (R 2 = 0.65) indicated that greatest improvements were observed in counties with higher initial mortality ($\beta =.32$) closely followed by percent urban ($\beta =.31$) and median household income ($\beta =.16$). Whereas percent Black residents ($\beta =-.06$), and percent with education beyond high school ($\beta =-.10$) was less associated on outcomes. Highest income counties were the first to experience improvement in cancer mortality, the highest rates of mortality decline, and the greatest reduction in excess deaths. Even though there was significant improvement in cancer mortality nationally, there were variations in the degree of improvement linked to county location, income, and urbanisation. These results underlie the need to expand place-based initiatives designed to advance cancer health and more equitable improvements in cancer mortality outcomes.

developing world↗
DOE OSTI2025

Finding gaps in the national electric vehicle charging station coverage of the United States

Abstract The United States federal government has invested $7.5 billion into charging infrastructure, including the National Electric Vehicle Infrastructure Program, to build fast charging stations along designated highways for long-distance car travel. We develop a consecutive coverage metric to compute the percent of United States roads (traffic-weighted) that are consecutively accessible within 500 miles of each county. We answer (1) what the state of consecutive coverage is in each county and (2) what the increase in coverage is when designated highways receive fast chargers. In 2023, 10% of counties had at least 75% minimum viable coverage. We find that if all designated highways receive fast-charging stations, 94% of United States counties will reach at least 75% fast charger coverage. However, the remaining counties are rural. This demonstrates that federal funding for fast chargers will help connect most—but not all—counties to the national network of continuously accessible charging stations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Conscientious vaccination exemptions in kindergarten to eighth-grade children across Texas schools from 2012 to 2018: A regression analysis

Background: As conscientious vaccination exemption (CVE) percentages rise across the United States, so does the risk and occurrence of outbreaks of vaccine-preventable diseases such as measles. In the state of Texas, the median CVE percentage across school systems more than doubled between 2012 and 2018. During this period, the proportion of schools surpassing a CVE percentage of 3% rose from 2% to 6% for public schools, 20% to 26% for private schools, and 17% to 22% for charter schools. The aim of this study was to investigate this phenomenon at a fine scale. Methods and findings: Here, we use beta regression models to study the socioeconomic and geographic drivers of CVE trends in Texas. Using annual counts of CVEs at the school system level from the 2012–2013 to the 2017–2018 school year, we identified county-level predictors of median CVE percentage among public, private, and charter schools, the proportion of schools below a high-risk threshold for vaccination coverage, and five-year trends in CVEs. Since the 2012–2013 school year, CVE percentages have increased in 41 out of 46 counties in the top 10 metropolitan areas of Texas. We find that 77.6% of the variation in CVE percentages across metropolitan counties is explained by median income, the proportion of the population that holds a bachelor's degree, the proportion of the population that self-reports as ethnically white, the proportion of the population that is English speaking, and the proportion of the population that is under the age of five years old. Across the 10 top metropolitan areas in Texas, counties vary considerably in the proportion of school systems reporting CVE percentages above 3%. Sixty-six percent of that variation is explained by the proportion of the population that holds a bachelor’s degree and the proportion of the population affiliated with a religious congregation. Three of the largest metropolitan areas—Austin, Dallas–Fort Worth, and Houston—are potential vaccination exemption "hotspots," with over 13% of local school systems above this risk threshold. The major limitations of this study are inconsistent school-system-level CVE reporting during the study period and a lack of geographic and socioeconomic data for individual private schools. Conclusions: In this study, we have identified high-risk communities that are typically obscured in county-level risk assessments and found that public schools, like private schools, are exhibiting predictable increases in vaccination exemption percentages. As public health agencies confront the reemerging threat of measles and other vaccine-preventable diseases, findings such as ours can guide targeted interventions and surveillance within schools, cities, counties, and sociodemographic subgroups.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

1997/1998 Regional Travel Household Interview Survey

The 1997/1998 Regional Travel—Household Interview Survey was conducted in the 28-county New York-New Jersey-Connecticut metropolitan area, including 12 counties in New York, 14 counties in New Jersey, and 2 counties in Connecticut. The study was jointly funded by the New York Metropolitan Transportation Council and the North Jersey Transportation Planning Authority (NJTPA). The purpose of the survey was to provide information suitable for gaining an in-depth understanding of the travel behavior of households and individuals, as well as the activities, demographics, and other factors that affect such behavior. The survey was a diary-type travel survey, in which detailed travel information and basic demographic and socioeconomic features were collected for each member of the 11,264 participating households during an entire travel day. The sample for analysis of resident-based weekday travel is 10,971 for the entire 28-county metro area. The weekend sample, comprised of 275 households, is restricted to the NJTPA counties of northern New Jersey and compliments the results of the 1995 Nationwide Personal Transportation Survey for the entire area.

1Hz data↗
DOE OSTI2026

1990 St. Louis Region Travel Survey

The 1990 St. Louis Region Travel Survey was performed in the fall of 1990 for the St. Louis region. The study was done for the East-West Gateway Coordinating Council by Barton-Aschman Associates, Inc., with assistance from NSI Research Group. The area surveyed included the city of St. Louis, St. Louis County, and parts of Jefferson County, Madison County, St. Clair County, Monroe County, and St. Charles County. The survey was used primarily for the calibration of trip production models. Other uses will include the calibration of trip attraction models and trip distribu¬tion models. The total number of completed, useable household samples for the survey area totaled 1,446.

1Hz data↗
NASA NTRS1982

LANDSAT Applications for the State of Delaware

The first phase of a cooperative demonstration project between the Eastern Regional Remote Sensing Applications Center and the Delaware Department of Natural Resources and Environmental Control is summarized. Separate land cover classifications were performed for three counties in Delaware using multiseasonal LANDSAT data from April 3 and July 20, 1974. The objective of the New Castle County and Kent County classifications was to provide general land cover information with special emphasis on existing farmland and deciduous and coniferous forest, respectively. A detailed study of existing inland and coastal wetland vegetation communities was attempted for Sussex County. Detailed accuracy assessments were conducted for general land cover in New Castle and Kent Counties and for wetland communities in Sussex County. The classifications were combined to provide a statewide Level I land cover map and acreage statistics. Based on these results, the participating state agencies determined that LANDSAT is a viable tool for mapping and monitoring land cover within the state.

Gervin, J. C.↗
DOE OSTI2020

Urban-scale Energy Modeling: Scaling Beyond Tax Assessor Data

In an attempt to attain building-specific characteristics for urban-scale building energy models, county-specific tax assessors’ data is often an initial data source. This data source can contain valuable information such as year built, area, height, HVAC type, and roof/wall descriptions.We will show examples of 2,000 fields from Hamilton County in Tennessee with examples of many fields which are not relevant to urban-scale building energy modeling, are incorrect compared to other data sources, and highlight some lessons learned working with such a data source.There are currently 3,142 counties in the United States, each with their own data format, field definitions, and data access policy. As urban-scale involves city-scale analysis potentially covering multiple counties and matures toward state- or nation-scale analysis, county-by-county approaches are not scalable. While there are efforts to unify these datasets, there is an increasing proliferation of data and algorithms that can cover wider areas and provide more accurate inputs for urban-scale models. This paper summarizes computer vision of imagery, cartographic layers, building type assessment, and model generation used to achieve scalable detection and analysis of buildings.

New, Joshua↗
DOE OSTI2022

Defining and Measuring Forest Dependence in the United States: Operationalization and Sensitivity Analysis

This manuscript helps bridge a gap between theoretical work that advocates for a broad view of forest dependence, and empirical work that has focused narrowly on economic measures. Background: Forest dependence has been widely recognized as a valuable concept for understanding human communities’ well-being and vulnerability to shocks and changes. Past theoretical literature has highlighted the importance of recognizing various types of dependence—environmental, economic, and social—yet past empirical literature on the topic in the United States has almost exclusively relied on measures of economic dependence such as employment and earnings from the traditional forest products sector. Objective and Methods: As a first step to bridge the gap between the theoretical and empirical, we reviewed the existing, publicly available, reliable, wall-to-wall data sources to identify alternate proxy measures for forest dependence. Data availability made the analysis feasible only at the county level—the administrative subdivisions of the state—or higher. Results and Conclusions: We created environmental, economic, and social criteria based on threshold levels of the following proxy variables: forest area, earnings, employment, and indigenous population. Using these criteria, we identified 524 counties to be potentially forest-dependent of 3140 total counties in the United States. The largest concentration was in the Pacific Northwest and Southeast regions, and a higher proportion were non-metro counties than metro. Varying the threshold levels significantly changes the number of counties identified but does not alter the overall geographic trends.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Under-capacitated and over-powered? Rural austerity and asymmetrical negotiating relationships in US wind energy development

Though rural local governments are central actors in renewable energy development, local governments in the United States (US) remain systematically under-funded. This paper considers what the manifestations of austerity in local governments broadly and rural localities specifically mean for renewable energy development and for energy transitions. Drawing on a survey of 262 elected county officials with experience with wind energy in eight US states, this paper asks how local officials understand the impacts of wind development, how local governments are involved in wind energy negotiations, how the resources and expertise needed to navigate negotiations are distributed among counties, and analyze the relationship between local capacity, access to resources, and involvement in negotiations. We find that local officials express simultaneously affective and material concerns with the impacts of wind development and see negotiations with the developer as central to realizing local benefits. However, the expertise and staffing needed to negotiate with developers is less accessible to poorer or sparsely populated counties, and counties with lower overall revenues have narrower scopes of negotiation, and counties incre. Our results suggest that uneven rural capacity heightens an already asymmetrical relationship between localities and developers. In analyzing how infrastructure developments are shaped by relationships between localities and developers that are conditioned by austerity and (under)capacity, this paper contributes to and bridges scholarly discussions on rural austerity, rescaling, and renewable energy transitions. These results challenge conventional wisdoms around centralizing energy siting processes, contextualize popular and academic debates about opposition to renewable energy development, and highlight the need for rural reinvestment to realize meaningfully participatory energy developments.

Elmallah, Salma↗
DOE OSTI2023

Geographic disparities of cardiovascular and cancer mortality in the USA: 1981–2019

Background: Cardiovascular and cancer mortality are the two leading causes of death in the developed world including the USA. However, mortality trends for these diseases are highly dynamic, and the geographic landscape is in transition. We analyze patterns of mortality improvement at county level during recent decades focusing on mortality decline and geographic diversity. Methods: We grouped age-adjusted mortality rates of cardiovascular and cancer diseases from CDC WONDER for 2959 US counties into 3-year time periods to improve reliability. We calculated percent mortality decrease between 1981–83 and 2016–19 for both causes to quantify mortality improvements for counties. Results: Using standard deviation as an index of disparities, place-based cancer mortalities were 68% larger than cardiovascular disparities. Significantly, 566 US counties had same or higher rates of cancer mortality in 2019 as in 1981. The geographic distribution of mortality improvement in either cause tends to favor largely populated areas along coasts. Less-populated, rural places in the interior and southeastern regions were experiencing less improvement. Conclusions: At the county level, large place-based disparities exist for both causes of death with the magnitude of disparities being substantially larger for the reduction in cancer deaths. Put differently, place matters, more for cancer than cardiovascular mortality.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Evaluation of the 2022 West Nile virus forecasting challenge, USA

Abstract Background West Nile virus (WNV) is the most common cause of mosquito-borne disease in the continental USA, with an average of ~1200 severe, neuroinvasive cases reported annually from 2005 to 2021 (range 386–2873). Despite this burden, efforts to forecast WNV disease to inform public health measures to reduce disease incidence have had limited success. Here, we analyze forecasts submitted to the 2022 WNV Forecasting Challenge, a follow-up to the 2020 WNV Forecasting Challenge. Methods Forecasting teams submitted probabilistic forecasts of annual West Nile virus neuroinvasive disease (WNND) cases for each county in the continental USA for the 2022 WNV season. We assessed the skill of team-specific forecasts, baseline forecasts, and an ensemble created from team-specific forecasts. We then characterized the impact of model characteristics and county-specific contextual factors (e.g., population) on forecast skill. Results Ensemble forecasts for 2022 anticipated a season at or below median long-term WNND incidence for nearly all (> 99%) counties. More counties reported higher case numbers than anticipated by the ensemble forecast median, but national caseload (826) was well below the 10-year median (1386). Forecast skill was highest for the ensemble forecast, though the historical negative binomial baseline model and several team-submitted forecasts had similar forecast skill. Forecasts utilizing regression-based frameworks tended to have more skill than those that did not and models using climate, mosquito surveillance, demographic, or avian data had less skill than those that did not, potentially due to overfitting. County-contextual analysis showed strong relationships with the number of years that WNND had been reported and permutation entropy (historical variability). Evaluations based on weighted interval score and logarithmic scoring metrics produced similar results. Conclusions The relative success of the ensemble forecast, the best forecast for 2022, suggests potential gains in community ability to forecast WNV, an improvement from the 2020 Challenge. Similar to the previous challenge, however, our results indicate that skill was still limited with general underprediction despite a relative low incidence year. Potential opportunities for improvement include refining mechanistic approaches, integrating additional data sources, and considering different approaches for areas with and without previous cases. Graphical Abstract

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Cancer survival in the United States 2007–2016: Results from the National Program of Cancer Registries

Background Cancer survival has improved for the most common cancers. However, less improvement and lower survival has been observed in some groups perhaps due to differential access to cancer care including prevention, screening, diagnosis, and treatment. Methods To further understand contemporary relative cancer survival (one- and five- year), we used survival data from CDC’s National Program of Cancer Registries (NPCR) for cancers diagnosed during 2007–2016. We examined overall relative cancer survival by sex, race and ethnicity, age, and county-level metropolitan and non-metropolitan status. Relative cancer survival by metropolitan and non-metropolitan status was further examined by sex, race and ethnicity, age, and cancer type. Results Among persons with cancer diagnosed during 2007–2016 the overall one-year and five-year relative survival was 80.6% and 67.4%, respectively. One-year relative survival for persons living in metropolitan counties was 81.1% and 77.8% among persons living in non-metropolitan counties. We found that persons who lived in non-metropolitan counties had lower survival than those who lived in metropolitan counties, and this difference persisted across sex, race and ethnicity, age, and most cancer types. Conclusion Further examination of the differences in cancer survival by cancer type or other characteristics might be helpful for identifying potential interventions, such as programs that target screening and early detection or strategies to improve access to high quality cancer treatment and follow-up care, that could improve long-term outcomes. Impact This analysis provided a high-level overview of contemporary cancer survival in the United States.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

A scalable variational method for estimating the latent infection-rate field of an outbreak

In this paper, we explore whether the infection-rate of a disease can serve as a robust monitoring variable in epidemiological surveillance algorithms. The infection-rate is dependent on population mixing patterns that do not vary erratically day-to-day; in contrast, daily case-counts used in contemporary surveillance algorithms are corrupted by reporting errors. The technical challenge lies in estimating the latent infection-rate from case-counts. Here we devise a Bayesian method to estimate the infection-rate across multiple adjoining areal units, and then use it, via an anomaly detector, to discern a change in epidemiological dynamics. We extend an existing model for estimating the infection-rate in an areal unit by incorporating a Markov random field model, so that we may estimate infection-rates across multiple areal units, while preserving spatial correlations observed in the epidemiological dynamics. To carry out the high-dimensional Bayesian inverse problem, we develop an implementation of mean-field variational inference specific to the infection model and integrate it with the random field model to incorporate correlations across counties. The method is tested on estimating the COVID-19 infection-rates across all 33 counties in New Mexico using data from the summer of 2020, and then employing them to detect the arrival of the Fall 2020 COVID-19 wave. We perform the detection using a temporal algorithm that is applied county-by-county. We also show how the infection-rate field can be used to cluster counties with similar epidemiological dynamics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

2006 Greater Triangle Household Travel Survey

The Greater Triangle Household Travel Survey was a comprehensive study of travel behavior throughout the 12-county Research Triangle Region, including all portions of Chatham, Durham, Franklin, Granville, Johnston, Lee, Orange, Person, Wake, and Vance counties, the eastern portion of Harnett County, and the southern portion of Nash County. The primary objective of this survey effort was to document demographic and travel behavior characteristics of regional travelers in order to update the current regional model and to develop a new, more robust travel demand model for the 12-county region. The 2006 survey was conducted in association with NuStats' DataSource and Louis Berger Group and was sponsored by the Capital Area Metropolitan Planning Organization, the Durham-Chapel Hill-Carrboro Metropolitan Planning Organization, the Triangle Transit Authority, and the North Carolina Department of Transportation. The project was conducted over an eleven-month period from August 2005 through June 2006. The survey utilized standard household travel survey methods, in which all household members from 5,107 households were asked to record all trips for a specified 24-hour period using a specially designed travel log on a non-holiday weekday.

1Hz data↗
DOE OSTI2026

2001 KIPDA Regional Household Travel Survey

The Kentuckiana Planning and Development Agency (KIPDA) conducted this four-month study from October 2000 through January 2001 to update regional travel demand models. The universe for the survey consisted of households in the five-county Louisville transportation planning study area, including Clark and Floyd counties in Indiana and Bullitt, Jefferson, and Oldham counties in Kentucky. Demographic variables and travel behavior characteristics were collected for 4,433 households in a 24-hour period. Of these, 4,113 were completed with households that were selected at random, and the remaining 320 were completed with representatives. The data from the survey only reflect travel by the selected residents of the five counties listed above and do not account for travel in the region by persons who were not residents of those five counties.

1Hz data↗
DOE OSTI2021

Scat Detection Dog Surveys for the San Joaquin Kit Fox on the Lawrence Livermore National Laboratory's Experimental Test Site (Site 300) and the Corral Hollow Ecological Reserve: 2020 Deployment

The San Joaquin kit fox (Vulpes macrotis mutica) historically occupied an extensive range in the San Joaquin Valley, California; however, their populations and habitat have since been significantly reduced by human impacts (United States Fish and Wildlife Service [USFWS] 1998). More than 95% of the potential habitat for kit foxes on the San Joaquin Valley floor has been converted to irrigated agriculture, urbanized, or industrialized lands. The San Joaquin kit fox was listed as endangered by the USFWS in 1967 and as threatened by the State of California in 1971. Records from local surveys, research projects, and incidental sightings indicate the present distribution of kit foxes extends from 1) southern Kern County north to Contra Costa, Alameda, and San Joaquin counties on the west side of the valley and to Stanislaus County on the east side; 2) into some of the larger, uncultivated valley-floor land parcels in Kern, Tulare, Kings, Fresno, Madera, and Merced counties; and 3) westward within 5 counties in the interior coastal range (USFWS 1998). Kit foxes have been denoted to occur in 3 geographically distinct core and several satellite populations in a heavily fragmented landscape, with the largest extant populations concentrated in the southern part of the range and smaller populations and isolated sightings in the central and northern portions (USFWS 1998, 2010).

54 ENVIRONMENTAL SCIENCES↗