Abstract
Agrivoltaics is a farming method that strategically integrates solar panels with agricultural production, a dual-use system that boosts food production while generating clean energy. China is the one of leading countries in agrivoltaics. However, no robust vectorized dataset has been available to verify the distribution of agrivoltaics in China. This study aims to provide the first nationwide agrivoltaics distribution and type dataset in China using comprehensive identification methods based on published spatial data of photovoltaic power stations and agrivoltaics records. The overall accuracy of agrivoltaics through visual examination is 89.71%. The results show that: (1) By 2022, there are 1,678 agrivoltaics projects in China with a total installation capacity of 134.55 GW. (2) China launched its first commercial agrivoltaics in 2010, reaching a peak of 347 projects in 2017, after which the number of new agrivoltaics projects has remained no less than 140 annually. (3) The three most common agrivoltaics types are crop-based, fishery-based, and greenhouse-based. This vectorized agrivoltaics dataset will support macro-level management and the sustainable development of agrivoltaics.
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Data availability
The dataset is available at https://doi.org/10.57760/sciencedb.26240.
Code availability
The code is available at https://doi.org/10.57760/sciencedb.26240.
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Acknowledgements
This work was jointly supported by the National Key R&D Program of China (2023YFF0805904), National Natural Science Foundation of China (No. 32271638 and 32171561), the Central Public-interest Scientific Institution Basal Research Fund (No. BSRF202502), and the Low Carbon Science Center of the Agricultural Science and Technology Innovation Program (ASTIP—CAAS).
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Xueyan Zhang: conceptualization, investigation, data curation, formal analysis, writing – original draft, writing – review & editing; Xin Ma: conceptualization, writing – review & editing, supervision.
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Zhang, X., Ma, X. Vectorized Agrivoltaics Dataset in China from 2010 to 2022.
Sci Data (2026). https://doi.org/10.1038/s41597-025-06305-w
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DOI: https://doi.org/10.1038/s41597-025-06305-w
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