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    Visualizing the Census of Marine Life
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The Census of Marine Life was a global network of researchers in more than 80 nations engaged in a 10-year scientific initiative to assess and explain the diversity, distribution, and abundance of life in the oceans.  The world's first comprehensive census of the past, present, and future of life in the oceans was released in October 2010.

 

GEBCO Global Topography

30 arc-second global topography

GEBCO Global Topography
  • The GEBCO_08 Grid is a 30 arc-second grid of global elevations, a continuous terrain model for ocean and land.  The grid was generated by combining quality-controlled ship depth soundings with interpolation between sounding points guided by satellite-derived gravity data. The land data are largely taken from the Shuttle Radar Topography Mission (SRTM30) data set.
  • Metadata: http://www.bodc.ac.uk/data/online_delivery/gebco/info2/
  • Spatial Resolution: 30 arc-second
  • Extent: Global
  • Temporal Resolution:  N/A
  • Date Range: 01/2009
  • Format(s): NetCDF (GMT compatible, 1D)
  • Access Methods: HTTP (registration required)
  • Data Access: http://www.bodc.ac.uk/data/online_delivery/gebco/
  • CoML visualization guidance: TBD

ref_gebco.jpg 

 

 

 

 

 

 

 

 

 

 

 

 

Use Example

Download the full GEBCO_08 grid as a netCDF file, convert to a GeoTIF, and visualize with ArcGIS 9.3

                Download the zip file and unzip.

                From within the OSGeo4W Shell in Windows or shell in Linux, navigate to the unzipped GEBCO_O8.nc file.

                        Get information about the file with the gdalinfo utility

                                > gdalinfo GEBCO_08.nc

                        Convert to GeoTIF with the gdal_translate utility

                               > gdal_translate -a_srs EPSG:4326 GEBCO_08.nc GEBCO_08.tif

                Add the GeoTIF to any data frame in ArcGIS.

 

                This file may also be converted with the Generic Mapping Tools (GMT) software.

                This file may also be visualized natively with the open-source Quantum GIS package.

           

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