Dr. Hadi Jaafar announced GYMEE, an operational model that estimates crop yield at 30m resolution. The Global Yield Mapper utilizes images from Landsat and Sentinel-2 satellites, weather data, and global soil datasets.
GYMEE is based on the integration of crop water use and abiotic stressors into the light use efficiency Monteith model. Results from the model were validated against actual yield data for three agricultural schemes with different climatic, soil, and management conditions in Lebanon, Brazil, and Spain. GYMEE can estimate the yield of wheat, corn, and potato with an accuracy of greater than ±15%, and can estimate stressors, water use, and biomass globally at field scale, improving our understanding of crop water use. Crop yield modeling and prediction have broad implications for monitoring global food security and food production. Decision makers depend on yield information to determine potential reduction in crop yield, deliberate food prices, and make timely decisions.
The full study can be found in the recently published paper.