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Data & Web Services

The United States Large-Scale Solar Photovoltaic Database (USPVDB) provides the locations and array boundaries of U.S. ground-mounted photovoltaic (PV) facilities with capacity of 1 megawatt or more. Large-scale facility data are collected and compiled from various public and private sources, digitized and position-verified from aerial imagery, and quality checked. The USPVDB is available for download in a variety of tabular and geospatial file formats to meet a range of user/software needs. Cached and dynamic web services are available for users that wish to access the USPVDB as a Representational State Transfer Services (RESTful) web service.

About the USPVDB
Lawrence Berkeley National Laboratory

Raw Data & Metadata Downloads

The USPVDB is available in a variety of downloadable file formats to meet a range of user needs. Legacy versions of the database can be found here. The following file formats and associated metadata files include:

GIS Data: Shapefile format (~7 MB zipped) | GeoJSON format (~2 MB zipped). The shapefile format is a popular geospatial vector data format compatible with a variety of GIS software. A shapefile stores non-topological geometry and attribute information for the spatial features in a data set. The geometry for a feature is stored as a shape comprising a set of vector coordinates. It is a (mostly) open specification for data interoperability among GIS software products. GeoJSON is an open standard format designed for representing simple geographical features, along with their non-spatial attributes. It is based on JSON (JavaScript Object Notation) and plays an important role in many spatial databases, web APIs, and open data platforms. Learn more about the GeoJSON format.

Tabular Data: CSV format (~2 MB zipped). The CSV (comma-separated values) format is common non-proprietary format for storing tabular data stored as plain text.

Metadata: XML format (117 KB). Metadata is the background information which describes the content, quality, condition, and other appropriate characteristics of the data. Users are encouraged to download the metadata file for detailed information about the USPVDB. Note that XML files can be read in any text editor.

Variable definitions for the CSV file can be found here, and a full codebook (data dictionary) here.

Geospatial Web Services

For the majority of users, the USGS Energy Resources Program has designed a dedicated USPVDB Viewer for visualization, analysis and dissemination of the USPVDB product. However, users who wish to access the USPVDB web service can do so by using the RESTful service endpoints below. USPVDB web services can be accessed by GIS applications that support ArcGIS map services or OGC Web Map Service (WMS) specifications.

Cached USPVDB Service: Cached map services use a set of pre-created images to quickly serve maps over the web or via applications that support map services. When viewing a cached service, users will be viewing static pictures of the USPVDB and will be limited in dynamic functionality like filtering and data-driven styling. The USPVDB cached map service allows find, identify, and query tasks to reach the underlying data.

Dynamic USPVDB Service: Dynamic map services are drawn at the time they are requested by a user. They are not as fast as cached maps, but have built-in capabilities that allow clients to dynamically change the layer's behavior and appearance.

Computational Notebooks

Researchers commonly use computational notebooks to share live code, equations, computational output, visualizations, and explanatory text in a single document. Notebooks provide an environment in which users execute code, examine results, modify, and repeat in an iterative fashion between the user and data. Jupyter Notebooks have emerged in recent years as a de facto open-source standard, allowing researchers to supplement their code and data with analysis, hypothesis, and conjecture. See a short tutorial using the USPVDB API in a Jupyter notebook to learn more about computational notebooks, or download the USPVDB notebook (requires Jupyter).

Citing the Dataset

The suggested citation for use in academic papers and otherwise where applicable is as follows:
Fujita, K.S., Ancona, Z.H., Kramer, L.A., Straka, M., Gautreau, T.E., Garrity, C.P., Robson, D., Diffendorfer, J.E., and Hoen, B., 2023, United States Large-Scale Solar Photovoltaic Database v1.0 (November, 2023): U.S. Geological Survey and Lawrence Berkeley National Laboratory data release,


The USPVDB combines Environmental Information Administration (EIA) solar facility location and attribute data spanning 1986 to 2021 with information on previously and suspected contaminated lands from the Environmental Protection Agency (EPA) and a dataset defining agrivoltaic sites from the National Renewable Energy Laboratory (NREL). The USPVDB is updated annually, with a lag time of 1-2 years, pending the release of underlying data.

Facility locations in the data set are visually verified using high-resolution aerial imagery and X/Y locations are manually moved to paneled areas. Polygons are digitized around facility array boundaries within an accuracy of 10 meters. Because of a lag in obtaining up-to-date aerial imagery, some facility locations could not be visually verified; these facilities have been excluded from the final data set.

The uncertainties associated with location data quality are rated, and a confidence level is recorded. None of the data in the USPVDB are field verified.