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Comprehensive inventory of seafloor mapping, ground-truthing, and predictive habitat modeling datasets to support Deepwater Horizon mesophotic and deep benthic community restoration

Metadata Updated: November 1, 2023

This dataset is a collection and inventory of existing seafloor mapping, ground-truthing, and predictive habitat modeling data within the Gulf of Mexico. The inventory was compiled by the Mesophotic and Deep Benthic Communities (MDBC): Mapping Ground-truthing, and Predictive Habitat Modeling Project. This project is one of many selected by the Open Ocean Trustee Implementation Group to restore natural resources injured by the 2010 Deepwater Horizon oil spill in the Gulf of Mexico. Data collected from 1980 to 2021 were sourced from federal and state agencies, as well as from academia and industry. Each dataset is represented in the inventory as a spatial footprint with corresponding quantitative and qualitative attributes. The seafloor mapping data are primarily remote sensing observations used to survey and derive depth, shape, and texture of the seafloor and characterize the geomorphological forms, substrates, and biota used to define MDBC habitats. Ground-truthing data are in-situ observations that provide visual and analytical characterization of information documenting the abundance and distribution of MDBC, substrate, and geomorphology. Predictive habitat models analyze habitat-environment or species-environment relationships from seafloor mapping data, in situ observations, and environmental data to predict MDBC habitat. The spatial extent of the dataset is as follows, except for predictive habitat models which have a more global extent.

Access & Use Information

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.

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Dates

Metadata Date 2023-10-04T12:27:51Z
Metadata Created Date March 17, 2023
Metadata Updated Date November 1, 2023
Reference Date(s) December 5, 2022 (publication)
Frequency Of Update asNeeded

Metadata Source

Harvested from NOAA/NESDIS/ncei/accessions

Graphic Preview

Preview graphic

Additional Metadata

Resource Type Series
Metadata Date 2023-10-04T12:27:51Z
Metadata Created Date March 17, 2023
Metadata Updated Date November 1, 2023
Reference Date(s) December 5, 2022 (publication)
Responsible Party (Point of Contact)
Contact Email
Guid gov.noaa.nodc:MDBC-MGM-Inventory
Access Constraints Cite as: Paxton, Avery; Herting, Jennifer; Winship, Arliss (2022). Comprehensive inventory of seafloor mapping, ground-truthing, and predictive habitat modeling datasets to support Deepwater Horizon mesophotic and deep benthic community restoration. [indicate subset used]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.25921/r39j-k881. Accessed [date]., Use liability: NOAA and NCEI cannot provide any warranty as to the accuracy, reliability, or completeness of furnished data. Users assume responsibility to determine the usability of these data. The user is responsible for the results of any application of this data for other than its intended purpose.
Bbox East Long -83.4463
Bbox North Lat 30.1216
Bbox South Lat 27.0000
Bbox West Long -96.9266
Coupled Resource
Frequency Of Update asNeeded
Graphic Preview Description Preview graphic
Graphic Preview File https://www.ncei.noaa.gov/access/metadata/landing-page/bin/gfx?id=gov.noaa.nodc:MDBC-MGM-Inventory
Graphic Preview Type PNG
Harvest Object Id ea695c6e-f627-4162-b099-b11f361dbb8c
Harvest Source Id c084a438-6f6b-470d-93e0-16aeddb9f513
Harvest Source Title NOAA/NESDIS/ncei/accessions
Licence accessLevel: Public
Lineage
Metadata Language eng
Metadata Type geospatial
Old Spatial {"type": "Polygon", "coordinates": [[[-96.9266, 27.0], [-83.4463, 27.0], [-83.4463, 30.1216], [-96.9266, 30.1216], [-96.9266, 27.0]]]}
Progress completed
Spatial Data Service Type
Spatial Reference System
Spatial Harvester True
Temporal Extent Begin 1980-01-01
Temporal Extent End 2021-04-30

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