https://phys.org/news/2018-06-algorithm-fuses-quality-quantity-satellite.html

In agricultural applications, imaging at 10- to 30-meter resolution is critical for farmers to see field-level rapid and subtle changes in crop conditions that affect yield, such as crop stress and disturbance after extreme weather events. Existing data have either insufficient spatial resolution or low frequency, the researchers said. Farmers usually require information with both high-resolution and near real-time occurrence.

"We struggled to find public satellite data that has both high spatial resolution and high frequency in our own research—it simply did not exist," said natural resources and environmental sciences professor and study co-author Kaiyu Guan. "So we took the initiative to produce it ourselves."