A multi-scale data assimilation framework for layered sensing and hierarchical control of disease spread in field crops

This project is focused on developing data analytics and decision-making techniques for early detection and mitigation of soybean diseases via fusing data from ground robots, UAVs and satellites. We aim to collect RGB and hyperspectral image data for soybean diseases from research farms at Iowa State and via collaboration with the Iowa Soybean Association and the NASA Jet Propulsion Lab (for satellite data).