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A comprehensive UK crop yield dataset incorporating satellite, weather, and soil type information

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Abstract

Agricultural research increasingly relies on data-driven approaches for crop yield prediction that complement more established crop growth models, including machine learning techniques. However, these approaches rely on large training datasets. Here, we present the Crop Yields, Climate, Soils, and Satellites (CYCleSS) dataset, a large-scale crop yield dataset derived from precision yield data for 934 fields across England on which a variety of crops are grown. In addition, the data also contains satellite-derived remote sensing data, weather data, and data on soil type, all aligned at a grid resolution of 10 km. Weather data is available at a daily temporal resolution, satellite data at 5-day resolution, while crop yield data is available at yearly resolution. This effort has been made possible through careful anonymisation of the yield data while preserving the alignment with remote sensing, weather, and soil data. This data will be useful both to train machine learning models of yield prediction as well as to parameterize mechanistic crop growth models. Furthermore, the anonymisation procedure itself will be of interest to the research community, as it represents a solution to a common problem on the interface of agricultural research and farming practice.

Data availability

All data comprising the final CYCleSS dataset is available through Figshare repository (https://doi.org/10.6084/m9.figshare.27225807)48. See the Data Records section for a detailed breakdown of the contents of this repository. Researchers who are further interested in the underlying data should contact the authors affiliated with UKCEH.

Code availability

R code used to merge and align available UK climate, soil, and Sentinel-1 synthetic aperture radar data to the same 1 km2 grid is provided in the following GitHub repository: https://github.com/alan-turing-institute/CYCLeSS-dataset-code. Dummy data and code needed to replicate the final process of merging climate, soil, and satellite data with UKCEH precision yield data and anonymisation of field locations is contained within the ‘CLYCESS_anonymisation.zip’ folder shared as part of this repository. R version 4.2.3 was used for the creation of this dataset.

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Acknowledgements

This work was supported by Wave 1 of The UKRI Strategic Priorities Fund under the EPSRC grant EP/W006022/1, particularly the “Environment and Sustainability” theme within that grant and The Alan Turing Institute. The contributions by JWR and RFP were funded by the Natural Environment Research Council (NERC) under research programme NE/W005050/1 AgZero+: Towards sustainable, climate-neutral farming. AgZero + is an initiative jointly supported by NERC and the Biotechnology and Biological Sciences Research Council (BBSRC). We thank the European Space Agency (ESA) for providing the Sentinel-1 (S-1) synthetic aperture radar (SAR) images. Climate hydrology and ecology research support system meteorology dataset for Great Britain (1961–2012) [CHESS-met] data licensed from NERC – Centre for Ecology & Hydrology.

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Authors and Affiliations

  1. The Alan Turing Institute, 96 Euston Road, London, NW1 2DB, UK

    Evangeline Corcoran, Natalia Efremova & Sebastian E. Ahnert

  2. Department of Biosciences, University of Exeter, Geoffrey Pope Building, Exeter, EX4 4QD, UK

    Daniel P. Bebber

  3. Statistics and Data Science Section, Intelligent Data Ecosystems, Rothamsted Research, Harpenden, Hertfordshire, AL5 2JQ, UK

    Stelian Curceac & Andrew Mead

  4. Regional Climate & Hydrology, Karlsruhe Institute of Technology, Kaiser Street 12, 76131, Karlsruhe, Germany

    Stelian Curceac

  5. School of Business and Management, University of Queen Mary of London, Mile End Road, London, E1 4NS, UK

    Natalia Efremova

  6. Department of Computational and Systems Biology, John Innes Centre, Norwich Research Park Colney Lane, Norwich, NR4 7UH, UK

    Azam Lashkari & Richard J. Morris

  7. UK Centre for Ecology and Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford Wallingford, OX10 8BB, Oxfordshire, UK

    Richard F. Pywell & John W. Redhead

  8. Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Dr, Cambridge, CB3 0AS, UK

    Sebastian E. Ahnert

Authors

  1. Evangeline Corcoran
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  2. Daniel P. Bebber
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  3. Stelian Curceac
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  4. Natalia Efremova
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  10. Sebastian E. Ahnert
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Contributions

E.C. led creation and development of the CYCLeSS dataset, and the writing of the manuscript. J.W.R. facilitated merging of the aligned remote sensing, climate soil and land use data with precision yield data so that farms from which precision yield data was collected could remain sufficiently anonymous, and contributed to writing, reviewing and editing the manuscript. All other authors contributed to the conceptual design of the CYCLeSS dataset, advised on its development, contributed to writing, reviewing, and editing the manuscript, and approved the submitted version.

Corresponding author

Correspondence to
Sebastian E. Ahnert.

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Corcoran, E., Bebber, D.P., Curceac, S. et al. A comprehensive UK crop yield dataset incorporating satellite, weather, and soil type information.
Sci Data (2026). https://doi.org/10.1038/s41597-025-06528-x

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