
Data resulting from a project undertaken to generate a comprehensive set of crop field boundary labels throughout the continent of Africa, representing the years 2017-2023. The project was funded by the Lacuna Fund, and led by Farmerline, in collaboration with Spatial Collective and the Agricultural Impacts Research Group at Clark University. Please refer to the technical report in the accompanying repository for more details on the methods used to develop the dataset, an analysis of label quality, and usage guidelines.
Land cover, Labels, Machine learning, Africa, Agriculture, Remote sensing
Land cover, Labels, Machine learning, Africa, Agriculture, Remote sensing
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