Supporting Shellfish Aquaculture in the Chesapeake Bay using Artificial Intelligence to Detect Poor Water Quality through Sampling and Remote Sensing

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.

Data and Resources

Additional Info

Field Value
Maintainer Earthdata Forum
Last Updated March 30, 2026, 23:58 (UTC)
Created April 1, 2025, 19:18 (UTC)
accessLevel public
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harvest_source_id b99e41c6-fe79-4c19-bbc3-9b6c8111bfac
harvest_source_title Science Discovery Engine
identifier 10.5067/SeaBASS/CHESAPEAKE_BAY_WATER_QUALITY/DATA001
license https://www.usa.gov/government-works
modified 2026-03-23T22:16:03Z
programCode {026:000}
publisher NASA/GSFC/SED/ESD/GCDC/OB.DAAC;NASA/GSFC/SED/ESD/GCDC/SeaBASS
resource-type Dataset
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spatial [[{"EastBoundingCoordinate":180.0,"NorthBoundingCoordinate":90.0,"SouthBoundingCoordinate":-90.0,"WestBoundingCoordinate":-180.0}],"CARTESIAN"]
temporal 2019-11-20/2026-03-23
theme {"Earth Science"}