An Africa-wide agricultural production database to support policy and satellite-based measurement systems

Creators: Geyman, Emily C.¹; Ferris, Alex²; Sahajpal, Ritvik³; Anderson, Weston³; Lee, Donghoon⁴; Hausmann, Neil²

1. California Institute of Technology
2. Bill & Melinda Gates Foundation
3. University of Maryland, College Park
4. University of Manitoba

Abstract

Agriculture remains a backbone of the African economy, contributing up to 70% of household income in rural areas. Yet crop yields across Africa are rising at a slower rate than the global average. Currently, strategies to improve agricultural productivity are limited by the availability of granular, accurate, and spatially-extensive data. These disaggregated statistics are required to understand how crop yields respond to climate variability, climate extremes, and agronomic practices. Here, we present GROW-Africa, a database that includes n = 535,844 georeferenced observations of crop yields across Africa focusing on 25 key crops including maize, sorghum, cassava, groundnuts, cowpeas, rice, yams, and millet. The database assimilates observations from a range of spatial scales, from regional government statistics, to household farmer surveys, to plot-level crop cuts. We use co-located observations to identify sources of bias and error in these varied data types. Finally, we demonstrate how the GROW-Africa database can be used to train remote sensing algorithms to produce continuous maps of crop yields across Africa.

Copyright and License

© The Author(s) 2025. This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Acknowledgement

We thank Renee Lafitte, Katherine Kahn, Youngwha Lee, Lakshmi Manavalan, Jeffrey Ehlers, Jim Lorenzen, Vipula Shukla, Gary Atlin, Nicholas Bate, Philip Welkhoff, and Ben Geyman for conversations and input that improved the curation and analysis of the GROW-Africa database. Local ground-truth agricultural data were made possible by the World Bank’s Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) project, as well as national ministries of agriculture and non-profit organizations including the One Acre Fund. E.C.G. was supported by the Fannie & John Hertz Foundation and the Gates Foundation.

Code Availability

The code developed for processing and cleaning the data presented in this study, along with the full GROW-Africa database, is available on Zenodo³⁸: https://doi.org/10.5281/zenodo.14961637.

Supplemental Material

Supplementary Information

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