Geoscience Australia is supporting the exploration and development of offshore oil and gas resources and establishment of Australia's national representative system of marine protected areas through provision of spatial information about the physical and biological character of the seabed. Central to this approach is prediction of Australia's seabed biodiversity from spatially continuous data of physical seabed properties. However, information for these properties is usually collected at sparsely-distributed discrete locations, particularly in the deep ocean. Thus, methods for generating spatially continuous information from point samples become essential tools. Such methods are, however, often data- or even variable- specific and it is difficult to select an appropriate method for any given dataset. Improving the accuracy of these physical data for biodiversity prediction, by searching for the most robust spatial interpolation methods to predict physical seabed properties, is essential to better inform resource management practises. In this regard, we conducted a simulation experiment to compare the performance of statistical and mathematical methods for spatial interpolation using samples of seabed mud content across the Australian margin. Five factors that affect the accuracy of spatial interpolation were considered: 1) region; 2) statistical method; 3) sample density; 4) searching neighbourhood; and 5) sample stratification by geomorphic provinces. Bathymetry, distance-to-coast and slope were used as secondary variables. In this study, we only report the results of the comparison of 14 methods (37 sub-methods) using samples of seabed mud content with five levels of sample density across the southwest Australian margin. The results of the simulation experiment can be applied to spatial data modelling of various physical parameters in different disciplines and have application to a variety of resource management applications for Australia's marine region.

Open Geospatial Consortium (OGC) web services offer a cost efficient technology that permits transfer of standardised data from distributed sources, removing the need for data to be regularly uploaded to a centralised database. When combined with community defined exchange standards, the OGC services offer a chance to access the latest data from the originating agency and return the data in a consistent format. Interchange and mark-up languages such as the Geography Markup Language (GML) provide standard structures for transferring geospatial information over the web. The IUGS Commission for the Management and Application of Geoscience Information (CGI) has an on-going collaborative project to develop a data model and exchange language based on GML for geological map and borehole data, the GeoScience Mark-up Language (GeoSciML). The Australian Government Geoscience Information Committee (GGIC) has used the GeoSciML model as a basis to cover mineral resources (EarthResourceML), and the Canadian Groundwater Information Network (GIN) has extended GeoSciML into the groundwater domain (GWML). The focus of these activities is to develop geoscience community schema that use globally accepted geospatial web service data exchange standards.

Discusses reasons to use the Australian Stratigraphic Units Database (ASUD), and new features of the web query page and reports

Legacy product - no abstract available

Case Study: GeoFrame software helps Geoscience Australia provide quick access to 2D and 3D seismic survey data within newly released license/permit in support of successful Australian Acreage Release bidding rounds

This dataset contains species identifications of echinoderms collected during survey GA2476 (R.V. Solander, 12 August - 15 September 2008). Animals were collected from the Western Australian Margin with a BODO sediment grab or rock dredge. Specimens were lodged at Museum of Victoria on the 10 March 2009. Species-level identifications were undertaken by Tim O'Hara at the Museum of Victoria and were delivered to Geoscience Australia on the 24 April 2009. See GA Record 2009/02 for further details on survey methods and specimen acquisition. Data is presented here exactly as delivered by the taxonomist, and Geoscience Australia is unable to verify the accuracy of the taxonomic identifications.

This dataset contains species identifications of sponges collected during survey SOL4934 (R.V. Solander, 27 August - 24 September, 2009). Animals were collected from the Joseph Bonaparte Gulf with a benthic sled. Specimens were lodged at Northern Territory Museum on the 26 September 2009. Species-level identifications were undertaken by Belinda Glasby at the Northern Territory Museum and were delivered to Geoscience Australia on the 23 February 2011. See GA Record 2010/09 for further details on survey methods and specimen acquisition. Data is presented here exactly as delivered by the taxonomist, and Geoscience Australia is unable to verify the accuracy of the taxonomic identifications.

This dataset contains species identifications of molluscs collected during survey SOL4934 (R.V. Solander, 27 August - 24 September, 2009). Animals were collected from the Joseph Bonaparte Gulf with a benthic sled. Specimens were lodged at Northern Territory Museum on the 3 May 2010. Species-level identifications were undertaken by Richard Willan at the Northern Territory Museum and were delivered to Geoscience Australia on the 5 May 2010 (leg 1 only). See GA Record 2010/09 for further details on survey methods and specimen acquisition. Data is presented here exactly as delivered by the taxonomist, and Geoscience Australia is unable to verify the accuracy of the taxonomic identifications.

Examination of developing geothermal exploration techniques and a geothermal play systems framework in Australia.

The 1 Second DSM Version 1.0 is a gridded digital surface model representing the radar reflective surface (bare earth, vegetation and built structures) as observed by the Shuttle Radar Topographic Mission in February 2000. It was derived primarily from the 1 second SRTM version 2 provided by DIGO, supported by the Geodata 9 Second DEM in void areas and the SRTM surface water database. Stripes and voids have been removed from the 1 second SRTM data to provide an enhanced and complete digital surface model for Australia and near-shore islands. The grid spacing is 1 second in longitude and latitude (approximately 30 metres).