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  • This is the list for the GEN category 'Oceans and Sea Regions'. It has been developed to support the GEN element of the ANZLIC Metadata Guidelines and forms part of the GEN Register. The list contains the names and the Miniumum Bounding Box (MBB) coordinates for all oceans and sea regions around Australia.

  • Please note: This product has been superseded by 50m Multibeam Dataset of Australia 2018. - This tile contains all multibeam data held by Geoscience Australia on August 2012 within the specified area. The data has been gridded to 50m resolution. Some deeper data has also been interpolated within the mapped area. The image provided can be viewed on the free software CARIS Easyview, available from the CARIS website: www.caris.com under Free Downloads.

  • Please note: This product has been superseded by 50m Multibeam Dataset of Australia 2018. - This tile contains all multibeam data held by Geoscience Australia on August 2012 within the specified area. The data has been gridded to 50m resolution. Some deeper data has also been interpolated within the mapped area. The image provided can be viewed on the free software CARIS Easyview, available from the CARIS website: www.caris.com under Free Downloads.

  • These data are the recorded Global Positioning System navigation points for every 60 seconds whilst on CSIRO Marines "Southern Surveyor" for the duration of Geoscience Australia's survey 265 in March 2004.

  • Zoning within the Great Barrier Reef Marine Park (effective 1st July 2004)

  • Please note: This product has been superseded by 50m Multibeam Dataset of Australia 2018. - This tile contains all multibeam data held by Geoscience Australia on August 2012 within the specified area. The data has been gridded to 50m resolution. Some deeper data has also been interpolated within the mapped area. The image provided can be viewed on the free software CARIS Easyview, available from the CARIS website: www.caris.com under Free Downloads.

  • In the past two decades, multibeam sonar systems have become the preferred seabed mapping tool. Many users have assumed that multibeam bathymetry data is highly accurate in spatial position. In reality, both vertical and horizontal uncertainties exist in every data point. These uncertainties are often represented as one single measure of Total Propagated Uncertainty (TPU). TPU is important to understand because it affects the quality of products generated from multibeam bathymetry data. To account for the magnitude and spatial distribution of this influence, an objective uncertainty analysis is required. Randomisation is the key process in such an uncertainty analysis. This study compared two randomisation methods, restricted spatial randomness (RSR) and complete spatial randomness (CSR), in an uncertainty analysis of a slope gradient dataset derived from multibeam bathymetry data. CSR regards data error in every grid cell as independent and assumes that the data error varies within a known statistical distribution without any neighbourhood effect. RSR assumes spatial structure and thus spatial auto-correlation in the data. We present a case study from a survey of the Oceanic Shoals Commonwealth Marine Reserve in the Timor Sea, conducted in 2012 by the Marine Biodiversity Hub through the Australian Government National Environmental Research Program. The survey area is characterised by steep-sided carbonate banks and terraces with abrupt breaks in slope of limited spatial extent. As habitats, the carbonate banks and terraces are important because they provide hardground for diverse epibenthic assemblages of sponges and corals, with their steep sides marking the environmental transition to deeper water, soft sediment habitats. In this analysis, the data errors in the multibeam bathymetry data were assumed to follow a Gaussian distribution with a mean of zero and a standard deviation represented by the TPU. The CSR and RSR methods were each implemented using a Monte Carlo procedure with 500 iterations. After about 300 iterations, the Monte Carlo procedure converged for both methods. Results for the study area are compared against pre-processed slope data (Figure 1a). The averaged slope gradient from the CSR method is 4.5 degree greater than the original slope layer, whereas for the RSR method this value is 0.03 degree. Moreover, the slope layer from the CSR method resolves noticeably less detail than the original slope layer and is an over-simplification of the true bathymetry (Figure 1b). In contrast, the RSR method maintained the spatial pattern and detail observed in the original slope layer (Figure 1c). This study demonstrates that although the uncertainty in multibeam bathymetry data should not be ignored, its impact on the subsequent derivative analysis may be limited. The selection of appropriate randomisation method is important for the uncertainty analysis. When the data errors exhibit spatial structure, we recommend using the RSR method.

  • Please note: This product has been superseded by 50m Multibeam Dataset of Australia 2018. - This tile contains all multibeam data held by Geoscience Australia on August 2012 within the specified area. The data has been gridded to 50m resolution. Some deeper data has also been interpolated within the mapped area. The image provided can be viewed on the free software CARIS Easyview, available from the CARIS website: www.caris.com under Free Downloads.

  • Geoscience Australia has been updating its collection of navigation for marine surveys in Australia. These include original navigation files, the 2003 SNIP navigation files and survey track maps along with survey acquisition reports. The result will be an updated cleansed navigation collection. The collection is based on the standard P190 extended header navigation file which follows the UKOOA standard. Industry standard metadata associated with a seismic survey is preserved. To assist industry, Geoscience Australia is making available its updated version of cleansed navigation. Although the process of updating the navigation data is ongoing and there is still legacy data to check, the navigation data is at point where a significant improvement has been achieved and it is now usable. Users should be aware that this navigation is not final and there may be errors. The KML file can be viewed using a range of applications including Google Earth, NASA WorldWind, ESRI ArcGIS Explorer, Adobe PhotoShop, AutoCAD3D or any other earth browser (geobrowser) that accepts KML formatted data. Alternatively the Shapefiles can be downloaded and viewed using any application that supports shape files.