AI and machine learning enhance systems by analyzing large satellite datasets quickly and accurately. These insights support crop type mapping, yield forecasts, and risk assessments. Researchers from the University of Maryland and Arizona State University are applying AI to improve early-warning systems and guide timely responses to crop threats.
Reliable agricultural data is critical to preventing crises. For example, poor data in the 1970s led to a major U.S. grain loss, known as the Great Grain Robbery. Accurate monitoring now helps governments and farmers plan ahead and avoid similar disasters.
This work is a team effort, combining expertise from fields like meteorology, hydrology, and computer science, alongside the real-world knowledge of farmers. Together, they are shaping a more resilient and informed future for agriculture.
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