This use-inspired NASA AIST project collects biological, chemical, and physical variables in and above the water at Chesapeake Bay sites for analysis within the lab. These ground-truth data are then used for data labeling, in combination with remotely sensed data, within a machine learning model trained to identify water quality challenges of resource managers that could result in shellfish bed closures, for example.