Abstract
Accurate farmland market data plays a crucial role in decision-making for policymakers, investors and operators. We present a nationwide, parcel-level dataset of farmland rent in China, derived from eight survey waves conducted between 2021 and 2025 across 27 provinces. The dataset comprises 7,237 rigorously validated samples, covering 191 cities and 422 counties in major agricultural production regions. Each record contains georeferenced parcel attributes and detailed transaction information, including parcel size, rental price, contracting parties, contractual terms. Compared with existing sources, this dataset offers broader coverage, finer spatial resolution, and improved temporal continuity, thereby addressing long-standing limitations of farmland transfer data in China. No other publicly available dataset provides comparable scope, reliability, and detail. Its release will enhance transparency in farmland markets and enable robust analyses of spatial and temporal dynamics, cross-regional comparisons, and the effects of institutional arrangements on land transactions. The dataset provides a valuable empirical foundation for advancing research in agricultural economics, rural development, and land use policy.
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Data availability
The data in this research is available in the Zenodo repository (https://doi.org/10.5281/zenodo.17161815)23.
Code availability
No custom code has been used for the dataset presented in this paper.
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Acknowledgements
This research was supported by the Center for Land Policy and Law (CLPL) at China Agricultural University through the Farmland Market Insight Project. We sincerely thank the China Farmland Rent Survey (CFRS) project team for their invaluable support, including providing resources, data, and assistance that were essential to the successful completion of this study.
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J.W. proposed the idea and designed the study, overseeing the design and implementation of the survey, as well as the overall data collection strategy. Q.X. wrote the original draft of the manuscript. S.Z. and Q.X. were involved in training enumerators, coordinating survey efforts, ensuring fieldwork consistency across multiple waves of the study, and assisting with data cleaning and validation. D.Z. assisted in writing and reviewing the manuscript. All authors contributed to data analysis and the editing of the manuscript.
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Xing, Q., Zhu, S., Zhu, D. et al. A spatiotemporal dataset of farmland rent aligned with farming seasons across China 2021–2025. Sci Data (2026). https://doi.org/10.1038/s41597-026-07040-6
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DOI: https://doi.org/10.1038/s41597-026-07040-6
