Connecting and collaboration

The Virginia Cost of Living Dashboard was created as part of the Virginia Tech Data Science for the Public Good (DSPG) Summer Research Program in 2025. This tool helps individuals, policymakers, and researchers explore how the cost of living varies across Virginia’s 133 counties and independent cities.

It includes two views: the minimum cost of living (a basic survival budget) and the average cost of living (a more typical monthly budget). Users can view breakdowns by family structure and customize scenarios to see how costs differ from one place to another.

https://aaec-vt.shinyapps.io/DSPG25_VA_Cost_of_Living/

The goal of this project is to identify potential gaps between the demographics of communities and the populations served by existing programming, as well as potential demographic gaps between volunteers and their communities at large. This project will be driven by American Community Survey data and Virginia Cooperative Extension programming needs.

https://aaec-vt.shinyapps.io/DSPG25_VCE_Demographics/

Virginia, founded in 1607, is a state made up of 95 counties and 38 independent cities, and has a unique landscape which is made up of the coastal plain, piedmont, blue ridge mountains, valley and ridge, and the Appalachian plateau. Virginia spans over 42,000 square miles and is known for its colonial history, as well as its agricultural heritage.

In 2023, Virginia was ranked as the 9th largest producer of solar energy in the US. Virginia also gets 5% of its energy from solar (Virginia Department of Energy). The development of utility-scale facilities presents an important step towards green energy, in the fight against climate change.

https://aaec-vt.shinyapps.io/DSPG25_Solar/

This dashboard was developed through the Data Science for the Public Good (DSPG) program at Virginia Tech, in collaboration with the Virginia Corn Board and the Kohl Centre for Agricultural Economic Development. The project leverages public datasets, remote sensing imagery, and predictive analytics to support Virginia’s corn growers and stakeholders.

Our goal was to create an interactive, data-driven tool that enables users to explore corn crop trends at both state and county levels. This dashboard integrates data from the USDA National Agricultural Statistics Service (NASS), Google Earth Engine (GEE), and MODIS satellite products to track crop condition, planting progress, weather trends, and yield estimates in near real-time.

The DSPG program empowers undergraduate and graduate students to apply statistical and computational methods to real-world challenges in agriculture, public health, education, and beyond. By combining stakeholder engagement with technical training, the program fosters the development of tools that are both impactful and accessible.

With support from the Virginia Corn Board, this tool was developed to improve transparency, planning, and decision-making across the Commonwealth’s corn sector. Farmers, extension agents, and policymakers can use this dashboard to monitor crop progress, assess environmental stressors, and anticipate yield outcomes — ultimately promoting more resilient and informed agricultural systems.

This work is supported by the U.S. Department of Agriculture, National Institute of Food and Agriculture as part of the DATA-ACRE program [grant no. 2022-67037-36639 / project accession no. 2021-10424]. Special thanks to the Virginia Corn Board for supporting this project and to Robert Harper (Virginia Farm Bureau) for his insights during the project!

https://aaec-vt.shinyapps.io/DSPG25_Crop_Progress/

This dashboard is a one-stop tool to explore and analyze the ideal location for a dairy plant to be placed amongst different counties in Virginia.

https://aaec-vt.shinyapps.io/DSPG25_Dairy/

Childcare acts as a foundational pillar for economic stability and workforce engagement; however, the rising cost of care has become a major barrier to employment. According to the Center for American Progress, the lack of affordable childcare is one of the most significant obstacles to sustained employment, leading to parents reducing hours, turning down opportunities, or exiting the labor force altogether. The burden associated with childcare and the workforce falls disproportionately on mothers, who are more likely to bear caregiving responsibilities. When women are unable to find proper childcare, they are less likely to be employed, reducing household income with potentially long-term career setbacks.

Moreover, the affordability and availability of childcare vary widely across different regions nationally and within the state of Virginia. Families living in rural areas or economically disadvantaged regions face additional barriers, including fewer childcare providers. These disparities exacerbate labor market inequalities and deepen the economic precarity of working families.

Childcare subsidies help low and moderate-income families afford the cost of childcare, enabling parents to work, look for work, attend school, or participate in vocational training. The primary federal program providing this funding is the Child Care and Development Fund (CCDF), which in the state of Virginia has been administered and maintained by the Virginia Department of Education since 2020, priorly being managed by the Virginia Department of Social Services.

https://aaec-vt.shinyapps.io/DSPG25_Childcare/

The project meticulously investigated the socioeconomic determinants of deaths of despair in Appalachia and Virginia. By thoroughly examining a range of variables, including employment rates, percentage of the population with a bachelor’s degree or higher, demographic factors such as race and age group, median household income, and harm reduction programs, the project sought to uncover the underlying causes and identify potential solutions to this escalating crisis. The project results >>

The market for renewable energy in the United States has experienced the third-largest growth rate globally, due both to the U.S. Inflation Reduction Act as well as individual state efforts to transition to renewable sources (International Energy Agency, 16). One such effort is the Virginia Clean Economy Act, which requires all energy production in the state to be renewable by 2050. (Virginia Department of Energy). In 2022, 11% of Virginia’s electricity came from renewable sources with solar power being the most prominent form (EIA Virginia). It accounted for 6% of all state energy production in 2022, which is more than double what it was in 2020 (EIA Virginia).

However, in spite of global, national, and state compliance with renewable energy initiatives, local resistance is common. Leading objections to the installation of solar photovoltaic facilities include the visual deterioration of the landscape, various ecological concerns, and a potential reduction in the value of neighboring residential properties. This project investigates the latter, as seen in Prince George's County. While some long-time members of the community wish to preserve the county's rich rural history, others recognize the value of transitioning to solar energy. Common concerns are similar to those mentioned above. Currently, there are two utility-scale solar facilities in the region: Fort Powhatan Solar Facility and Caden Energix Rives Road Solar Facility. By measuring the impact that a utility-scale solar facility has on the value of nearby residential properties, the team assessed whether a solar facility functions as a neighborhood amenity, disamenity, or neither. The project results >>

The project aimed to simulate future food insecurity in Southwest Virginia. We used publicly available information, such as the U.S. Census Bureau’s American Community Survey (ACS) and Bureau of Labor Statistics (BLS) data, along with data compiled by Feeding America. When gathering this data, we focused on variables including income, age, educational attainment, and vehicle access which we found from existing literature to be potential determinants for food insecurity. We also selected variables used by Feeding America in their Map the Meal Gap report, such as unemployment and poverty rate. Using a regression model in R, we simulated food insecurity rates for the years 2010 through 2022 at the state level, and then brought them down to the county and city level. We also ran an XGBoost machine learning model to simulate future food insecurity rates for the years 2023 through 2027 at the county and city level.

We developed interactive maps that include food insecurity rates for both previous and future years, which are exhibited on this website to display our findings. Another map featured on this website shows the locations of farmers markets, grocery stores, dollar stores, and food pantries and distributors in Southwest Virginia that we gathered, as well as additional information. The results of our project could be used by Feeding Southwest Virginia and other food programs to demonstrate a need for increased funding to specific areas that we found are likely to see a rise in food insecurity in future years. The project results >>