DBSEABED

Seafloor Substrates

About dbSEABED

Summary

dbSEABED is a comprehensive database/GIS describing the seabed materials of the global ocean. It holds data describing about 2 million seafloor sites, and integrates that pointwise data using an Information Processing System that has diverse processing steps and options. A unique and advantageous feature is that word-based descriptive data about seafloor bottom type is parsed and brought into conformance with the analytical numeric data type, so that they become co-mappable. This gives the best possible geographic coverage and information richness from the available data.

dbSEABED deals with the grain size textures, strengths and porosities, carbon and carbonate compositions, colors, structural features, and grain components of the seafloor. The diverse inputs on these properties from thousands of individual datasets are harmonized into one standardized and calibrated set of outputs, which initially is pointwise but then is computed into grids and other visualizations. For quality assurance reasons, a significant amount (about 20%) of the original data from the diverse input datasets is not accepted to outputs.

dbSEABED has stratigraphic (subbottom) capabilities that are not addressed here. The entire Ocean Drilling Program, Deep-Sea Drilling and Lamont-Doherty Core Repository datasets are entered.

The Project

Development of the system is based at INSTAAR, University of Colorado in Boulder. Partners at the USGS, LDEO at Columbia University, PIES at University of New Orleans, and UTIG at University of Texas Austin, Consortium of Ocean Leadership (CoL), and NGDC in NOAA (USA), BWB (Germany), Universities of Sydney and Adelaide, DSTO and CSIRO (Australia), also develop and validate the system data, dictionaries and software. Numerous institutions and individuals have shown foresight and generosity by providing sets of modern and legacy data to the system. Funding for dbSEABED has been provided by ONR, NSF, BWB, NOAA, DSTO, CSIRO, USGS, GSMFC, CoL.

More information on dbSEABED can be obtained from the Home Page, from the national usSEABED development by USGS, and from various papers listed in the Bibliography. The bibliography also shows the scope of applications of the system in ocean research and stewardship. dbSEABED outputs are already in use for models  of fisheries stocks, acoustic signal propagation, object burial, contaminant reservoirs, sediment transport, and taxonomic habitat suitability.

Data for Modellers

The Gridded Data

For modeling applications, gridded data is appropriate. The usual format for delivery of gridded data from dbSEABED is the E.S.R.I. ASCII grid format, at finest 0.02 degrees cell size, with WGS 84 datums. The grids are typically computed for regions, though a global gridding is being formed. The gridding technique uses the dbSEABED Competent Seafloor Interpolator, which applies the Inverse Distance Weighted mathematical method to judiciously searched data in order to produce geographically and ecologically reasonable results. For example, for each cell the data must be neighbouring in terms of distance and water depth, and isotropic (surrounding). Search radius shrinks to shore. Coupled parameters such as gravel/sand/mud are dealt with appropriately. The gridded results are especially good in coastal and archipelagic areas. Gridded quantitative uncertainties are also put out. Regions too distant from useable data are left blank, but may be filled client-side based on the CSI grid using any secondary, unspecialized gridding method from a commercial GIS. The maximum (open ocean) search radii are 20km for sediment parameters, 5km for rock.

Grid Availability

The data for modellers will be added progressively to this site, with priority on areas of active modelling research and overall data availability from dbSEABED.

To begin, the gridded parameters will be: gravel, sand, mud (%), rock exposure (%), average grainsize and sorting (phi), carbonate (%). A specification of the parameters is given under usSEABED. dbSEABED uses the Wentworth grain size classification and scale. A collection of ESRI ArcView 3.x and ArcGIS 9.x legends is available from this web address: GIS Legends.

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Adriatic Sea

Grid extents: bottom left: 12.00°E 40.20°N; upper right: 19.72°E 45.92°N; grid centred

Grid specifications: ncols 386; nrows 286; xllcorner 12.0; yllcorner 40.2; cellsize 0.02; NODATA_value -99

Point Data Pattern:

Gravel (%) Zipfile Set			RGSM Dominances (Classes) Zipfile Set
Sand (%) Zipfile Set			Folk Classification Zipfile Set
Mud (%) Zipfile Set
Rock (Exposure, %) Zipfile Set

The coverage was formed as a test-bed for the gridding software and to support the EUROSTRATAFORM initiative.

SACLANTCEN, BWB, USGS, A.W.Niedoroda and F.McKinney kindly provided valuable datasets.

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Northern Gulf of Mexico

Grid specifications: ncols 386; nrows 286; xllcorner 12.0; yllcorner 40.2; cellsize 0.02; NODATA_value -99

Grid extents: bottom left: 12.00°E 40.20°N; upper right: 19.72°E 45.92°N; grid centred

Gravel
Sand
Mud
Rock

The development of this coverage was funded by the USGS and GSMFC. A Google Earth display of browseable binned data is available.

NMFS at NOAA, USGS (St Petersburg) and USF provided invaluable datasets.

Statements

Suggested Citation

Jenkins, C.J. 2010. Seafloor Substrates. INSTAAR, University of Colorado, Boulder CO USA. [URL: "##"]

Technical Support

In case of queries about content, format and applicability of the data contact Chris Jenkins at INSTAAR. Albert Kettner's 24/7 help desk number is 303 735 6789.

Disclaimer

Neither the University of Colorado nor any partner thereof, nor any of their employees, makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed in this report, or represents that its use would not infringe privately owned rights. Reference therein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the University of Colorado or any partner thereof. Although all data and software published on this web page have been used by the University of Colorado, no warranty, expressed or implied, is made by the University of Colorado as to the accuracy of the data and related materials and (or) the functioning of the software. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the University of Colorado in the use of this data, software, or related materials.