U.S. Department of EnergyOffice of Scientific and Technical Information
Dataset of U.S. School Bus Depots
Abstract
A large body of environmental justice and public health literature describes how undesirable or dangerous facilities, such as truck depots and polluting industrial plants, are disproportionately located in or near communities of color, low-income communities, or populations that have been otherwise marginalized or underserved, leading to health harms. Research also describes the high levels of traffic-related air and noise pollution that is linked to health harms and inequitably distributed near many schools. Therefore, a primary use case for this dataset is to analyze the extent to which school bus depots are located in underserved areas and to create an evidence base that would better enable the work of community members, advocates, and other stakeholders toward improving air quality, equity, and public health in underserved areas. Other possible uses for this school bus depot dataset include electricity grid planning and resilience, given recent policy progress and other momentum toward school bus electrification. It could also be useful to identify school bus depots that are at risk from climate and other hazards and may not be strong candidates for large investments in electric infrastructure, and conversely to identify depots that could serve as resilience hubs. This dataset was created using an object-basedmore »
- Authors:
-
- Virginia Tech
- Publication Date:
- DOE Contract Number:
- AC05-76RL01830
- Research Org.:
- National Renewable Energy Laboratory; Pacific Northwest National Laboratory; Idaho National Laboratory
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Transportation Office. Vehicle Technologies Office (EE-3V)
- Subject:
- 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; electric vehicle infrastructure planning; equity; medium-duty vehicles
- OSTI Identifier:
- 2429432
- DOI:
- https://doi.org/10.15483/2429432
Citation Formats
Shao, Yang. Dataset of U.S. School Bus Depots. United States: N. p., 2025.
Web. doi:10.15483/2429432.
Shao, Yang. Dataset of U.S. School Bus Depots. United States. doi:https://doi.org/10.15483/2429432
Shao, Yang. 2025.
"Dataset of U.S. School Bus Depots". United States. doi:https://doi.org/10.15483/2429432. https://www.osti.gov/servlets/purl/2429432. Pub date:Fri Dec 12 04:00:00 UTC 2025
@article{osti_2429432,
title = {Dataset of U.S. School Bus Depots},
author = {Shao, Yang},
abstractNote = {A large body of environmental justice and public health literature describes how undesirable or dangerous facilities, such as truck depots and polluting industrial plants, are disproportionately located in or near communities of color, low-income communities, or populations that have been otherwise marginalized or underserved, leading to health harms. Research also describes the high levels of traffic-related air and noise pollution that is linked to health harms and inequitably distributed near many schools. Therefore, a primary use case for this dataset is to analyze the extent to which school bus depots are located in underserved areas and to create an evidence base that would better enable the work of community members, advocates, and other stakeholders toward improving air quality, equity, and public health in underserved areas. Other possible uses for this school bus depot dataset include electricity grid planning and resilience, given recent policy progress and other momentum toward school bus electrification. It could also be useful to identify school bus depots that are at risk from climate and other hazards and may not be strong candidates for large investments in electric infrastructure, and conversely to identify depots that could serve as resilience hubs. This dataset was created using an object-based approach with remote sensing data. The primary source of aerial imagery was the National Agriculture Imagery Program (NAIP) dataset. NAIP imagery was analyzed to locate individual school buses based on their color and size, and then classified clusters of school buses as potential depots, which were then verified visually. The resulting dataset contains 11,309 depots across the 48 contiguous U.S. states and Washington, D.C. Fifty-one percent (5,730 depots) are at schools, defined as being 350 meters or less from the nearest school. The accuracy of the dataset was assessed by comparing it with independent reference datasets containing 506 depots from the records of two school transportation companies. We found good agreement, with an omission error rate of 15.2% (77 depots). This dataset represents one of the only remote sensing projects to conduct object detection using data at the sub-meter to 1-meter resolution for a continental-scale application.},
doi = {10.15483/2429432},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Dec 12 04:00:00 UTC 2025},
month = {Fri Dec 12 04:00:00 UTC 2025}
}