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

We are collecting and analyzing biological, chemical, and physical variables in and above the water at target sites and in the lab, looking for hyperspectral proxies that covarying with pollutants. This project is applying an AI model to address water quality, using datasets collected around the Bay in combination with remotely sensed data during targeted field work to support the need to more effectively sort through disparate data sets to identify areas of poor water quality that result in shellfish bed closure.

ShareScore

24/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
4
Reuse readiness
8
Engagement
0