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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

Metadata Updated: December 6, 2023

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.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

Downloads & Resources


Metadata Created Date May 30, 2023
Metadata Updated Date December 6, 2023

Metadata Source

Harvested from NASA Data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date May 30, 2023
Metadata Updated Date December 6, 2023
Identifier C2561597300-OB_DAAC
Data First Published 2019-11-20
Language en-US
Data Last Modified 2023-04-06
Category geospatial
Public Access Level public
Bureau Code 026:00
Metadata Context
Metadata Catalog ID
Schema Version
Catalog Describedby
Citation Archived by National Aeronautics and Space Administration, U.S. Government, NASA/GSFC/SED/ESD/GCDC/OB.DAAC.
Harvest Object Id 68bece17-1331-4f4c-a6ed-afaa4a4868f4
Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
Harvest Source Title NASA Data.json
Homepage URL
Metadata Type geospatial
Old Spatial -180.0 -90.0 180.0 90.0
Program Code 026:001
Source Datajson Identifier True
Source Hash e1a5edd24568f8e47f021ce953626281d99d30a2ff64337327c6cd9d34f2ed9c
Source Schema Version 1.1
Temporal 2019-11-20T00:00:02Z/2023-04-17T00:00:00Z

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