Mapping global yields of four major crops at 5-minute resolution from 1982 to 2015 using multi-source data and machine learning
Abstract Accurate, historical, and continuous global crop yield data are essential for assessing risks to the global food system. However, existing datasets often have limited spatial and temporal resolution. Here, we introduce GlobalCropYield5min, a novel gridded dataset providing crop yield data f...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04650-4 |
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