Sample Output Graphics
and Alpine Research,
Except for the Google Earth Global Viewer this page gives examples of the mappings
and other data displays that have been produced for various projects.
For actual data please contact the project team.
|Google Earth World Ocean Floor|
A browser for the data in dbSEABED, presented in 0.1 degree bins. The display web page, LINK HERE, allows users to download or start a KML file which integrates data tiles for the world for viewing.
Google Earth (or other fully compatible applications) zoom down to
about 1000km altitude, till when white bin outlines appear. Then click
on any of the cells to discover what sediment / rock / biologic remains
have been observed there.
These data are not intended for bulk download, for discovery only.
The 0.1 dg grid of sediment textures offshore of the Amazon River. The
muds (green colour code) tend to move northward out of the delta area.
holds data characterizing the seabed at about 5 million samplings, at 3
million geographic sites. It
is clearly the largest integration of data on the global seafloor
substrates. But the fractional coverage of the ocean floor is still
less than needed, because of the vastness of the ocean. Efforts
continue in the project to find and activate datasets to increase the
fractional coverage. Progress is rapid. In 2 months (mid 2015)
another 60,000 data sites have been added from Russian, Norwegian,
Australian and other sources.
at 0.1dg cellwise resolution, the
active data in dbSEABED characterize 29% of the seabed (1254305 cells
of 4337130). The median distance from any position in the
ocean to a site with data is ~54km. The greatest distance is 600km. It
is often said that we know about only 5% of the
ocean: 5% of the ocean area lies within ~6km of dbSEABED data. For more statistics see these SpatialStatistics
Graphic: Worldwide distribution
of the data, showing recent additions (2015; colours represent individual datasets) (click to enlarge)
|Hurricane Seabed Sediment Pickup: Gulf of Mexico Time Series|
For a project with BOEM, VIMS, UCSB and ROMS at RutgersU, hurricane wave data from ROMS was convolved with seabed data from dbSEABED and bathymetry from SRTM30+.
suspension ('pickup') under the oscillating bottom currents
from sea-surface waves that attained 8m height and 90m wavelength
in storms 'Gustav' and 'Ike' 2008, was modelled using erosion relations
from Parchure and Mehta (1985) and Nielsen (1992) for the muddy and
sandy environments, and also decremented the results for areas of rock,
gravel that are shown by dbSEABED. The results are therefore spatially
and temporally explicit. This can be seen for the muddy facies
around the delta.
The analysis went on to apply sediment diffusion
models (1D) and predict the Richardson and Reynolds numbers for the
suspended sediment layers, and finally the criterea for flow
instabilities leading to gravity flows in sloping areas. Deeper levels
of the seafloor are less affected by the waves.
Time-series movie-mapping of the ppm volume suspended sediment
concentrations, near-seafloor, created by flows from the sea-surface
waves during hurricanes Gustav and Ike, 2008. This single image shows
activity near storm-peak. The depth contours are 25,50,100,250, 500,
1000 and 2000 m WD. (click to rum)
Click for Gif Movie
Under project work for future regulation of global deep-sea trawling, methods
for map-interpolation of seabed characteristics have been extended. For statistical correctness, the mapping and analysis is
done in equal-area projections, giving unbiased results over the
latitude gradients of large areas. A fusion of Inverse Distance
Weighted interpolation and Random Forest classification solves
the problem of local versus regional map gridding for large
areas having varying data densities. The IDW process allows proper
mapping of actual local, perhaps unexpected materials. The RF process
fills in areas far from actual data, with the regionally expectable results. The IDW method is a modified one, appropriate
for the coastal zonation, directional
biases in the data, and water depth variations. Full estimation of
the map uncertainties is also carried out.
The Bering Sea is an extremely important economic area for the USA in
its fisheries, and these mappings will help plan for economic
sustainability. The figure shows Folk seafloor sediment texture codes for the
region based on the combined IDW-RF mapping, computed and rendered in
Alaska Albers Equal Area Projection. Click HERE for legend
and HERE for the
mapping depicts the zonation and patchiness of the seabed conditions. The IDW method rendered features
like the Yukon prodelta correctly, which the RF method did not
reproduce. The sandy spots marked on the abyssal plain are probably from
scattered ice-rafted materials, or turbidites.
mappings have been made for many areas of the globe, and can be
computed to specification for areas with sufficient data.
interface with whole-earth scale models, such as climate and
circulation models, ocean substrates data has been synthesized
from dbSEABED at the
global scale. The resolution however, is low (best, 0.1 degrees) - as
for most of the models. A parameter of high interest is the carbonate
content of the bottom.
However, a global synthesis of any main dbSEABED parameter or
component/feature is now possible (see lists HERE).
The carbonate synthesis follows early work by Archer (1996, "An
atlas of the distribution of calcium carbonate in sediments of the deep
sea." Global Biogeochemical Cycles 10, 159-174), but has
a number of changes: (i) the amount of data available is much greater;
(ii) the core-top criterion is relaxed (based on arguments involving
bioturbation, erosion, managment of core overpenetrations in underlying
database); (iii) rock areas bare of sediment (such as the spreading
ridges) and Fe-Mn nodule areas are accounted for; (iv)
shallow-water areas - which also play a role in ocean carbonate
chemistry (see Andersson, AJ & Mackenzie
2012. "Revisiting four scientific debates in ocean
research", Biogeosciences. 9, 893-905) are mapped. Prime amongst
the shallow water areas is the "Coral Triangle" area of SE-Asia,
Indonesia. Some geographic data on the regional distributions of
skeletal carbonate types and mineralogies are also available from the
The mapping suggests lower carbonate contents overall
than mapped in earlier works. This may affect modeled budgets for
earth-system carbon dioxide and outcomes for ocean acidification.
The synthesised data are rapidly being extended, and can be generated on request from the latest version of the full dbSEABED
Global-scale carbonate contents, interpolated using Radial
Function methods. Deep blue to dark red, 0 to 100%.
|Gulf of Mexico
region is extraordinarily rich in data and provides a strong test of
system capabilities for data ingestion, integration and visualization.
Coverages from the system have assisted with shrimp and fish stocks
protection, numerical modeling of unstable sediment slopes, and naval
object burial potential.
gridded data is available from "http://csdms.colorado.edu/wiki/DBSEABED#Northern_Gulf_of_Mexico".
(2010; contact INSTAAR for more
recent comprehensive coverage.)
Habitat-related data layers may be obtained from NOAA NCDDC "Gulf of Mexico Data Atlas"
Graphic: Seafloor carbonate contents in the sediments and crusts.
(2011) (click to enlarge)
|Ganges Offshore Delta
Ganges delta is the site of the largest discharge of sediment into the
world ocean and approx 200 million people live proximal to the delta,
in association with valued wildlife species.
mappings of the offshore delta zones aim to progress habitat, fisheries
and sediment transport studies. Since the data is being updated
regularly, apply to dbSEABED for the most up-to-date coverages.
Graphics: Suspended sediment
plumes; mud content in sampled bottom sediments; dominant bottom
textures (dated Aug 2013). (click to enlarge)
region is a significant one for research into mapping and modeling. The
data available is huge, but there are significant conflicts between the
many mapping syntheses that have been released over time. This
compilation is a consensus built primarily from public point
data, but also employing published grid/polygon maps.
The comprehensive gridded and pointwise data are available on request.
The work was prompted by an investigation of spatial variabilities for
seabed mesoscale roughness and drag relevant to tidal modelling (see
Graphic: Sediment mud contents
(%) in a 3-D visualization of the seafloor of the North Sea and
surrounds. (Dated: 2012) (click to enlarge)
|100My of Ocean Carbonates in Paleocoordinates
can be used for large-scale data analysis. Here a sedimentological
attribute (carbonate) of the DSDP, ODP, IODP and many other deep-time
samples is plotted in Paleocoordinates through 100My.
This allows the actual core data to be viewed in terms of true
paleo-latitudes and longitudes - that is, exactly by paleogeography and
bottom panels are Continent-Ocean Boundaries at present and 100Ma ago.
The tracklines show the plate tectonic paths represented by individual
cores. The color of points represent the percentages of carbonate at
each paleolatitude, paleolongitude, and age. Composed in Summer 2014 for the Deep Carbon Observatory project and ESIP (poster). We acknowledge the contribution of the GPlates facility, thanks.)
Adriatic Sea has been an area for benchmarking numerical
for sedimentation processes. dbSEABED coverages have
helped some modeling projects and also studies of ecology.
gridded data available
(Contact INSTAAR for more
recent, more comprehensive coverages.)
Graphic: Bottom-type dominances
in a 3-D visualization of the seafloor of the Adriatic Sea. (Dated: 2011) (click to enlarge)
|Louisiana Ship Shoal (3D
This area, WSW of the Mississippi Delta was used a the development
dataset for Core
Depiction of 3D stratigraphic data is a complex matter and necessarily,
involves a suite of files. Therefore the data are presented as a
zipfile collection. There is also a Google-Earth variation of
Other areas where 3D CoreNavigator structures
have been built include the German Bight, offshore slope of the
Mississippi Delta and various ODP sites.
Graphic: The core collections of
the USGS and UNO through Ship Shoal, Louisiana. (Dated: 2008) (click to enlarge)