This service has been created specifically for display in the National Map and the chosen symbology may not suit other mapping applications. The Australian Topographic web map service is seamless national dataset coverage for the whole of Australia. These data are best suited to graphical applications. These data may vary greatly in quality depending on the method of capture and digitising specifications in place at the time of capture. The web map service portrays detailed graphic representation of features that appear on the Earth's surface. These features include the administration boundaries from the Geoscience Australia 250K Topographic Data, including state forest and reserves.

Geoscience Australia carried out a marine survey on Carnarvon shelf (WA) in 2008 (SOL4769) to map seabed bathymetry and characterise benthic environments through colocated sampling of surface sediments and infauna, observation of benthic habitats using underwater towed video and stills photography, and measurement of ocean tides and wavegenerated currents. Data and samples were acquired using the Australian Institute of Marine Science (AIMS) Research Vessel Solander. Bathymetric mapping, sampling and video transects were completed in three survey areas that extended seaward from Ningaloo Reef to the shelf edge, including: Mandu Creek (80 sq km); Point Cloates (281 sq km), and; Gnaraloo (321 sq km). Additional bathymetric mapping (but no sampling or video) was completed between Mandu creek and Point Cloates, covering 277 sq km and north of Mandu Creek, covering 79 sq km. Two oceanographic moorings were deployed in the Point Cloates survey area. The survey also mapped and sampled an area to the northeast of the Muiron Islands covering 52 sq km. cloates_3m is an ArcINFO grid of Point Cloates of Carnarvon Shelf survey area produced from the processed EM3002 bathymetry data using the CARIS HIPS and SIPS software

This dataset contains species identifications of micro-benthic worms collected during survey SOL4934 (R.V. Solander, 27 August - 24 September, 2009). Animals were collected from the Joseph Bonaparte Gulf with a Smith-McIntyre grab. Specimens were lodged at Northern Territory Museum on the 1 February 2010. Species-level identifications were undertaken by Chris Glasby at the Northern Territory Museum and were delivered to Geoscience Australia on the 7 March 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.

Legacy product - no abstract available

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.

Legacy product - no abstract available

AMB is a dataset depicting the limits of Australia's maritime jurisdiction as set out under UNCLOS and relevant domestic legislation. To this extent, AMB provides a digital representation of the outer limit of the 12 nautical mile territorial sea, the 24 nautical mile contiguous zone, the 200 nautical mile Exclusive Economic Zone and Australia's Continental Shelf, as well as, the 3 nautical mile coastal waters. Where Australia has agreements with neighbouring countries these treaty lines are also included in the data. The dataset has been compiled by Geoscience Australia in consultation with other relevant Commonwealth Government agencies including the Attorney-General's Department, the Department of Foreign Affairs and Trade, as well as the Australian Hydrographic Office.

This presentation will provide an overview of some of the work currently being undertaken at Geoscience Australia GA) as part of the National Coastal Vulnerability Assessment (NCVA), funded by the Department of Climate Change (DCC). The presentation will summarise the methodology applied, and highlight the issues, including the limitations and data gaps.

Map prodiced for Department of Foreign Affairs and Trade to illustrate petroleum permits in the shared Australia/Indonesia zone. Produced at the request of DFAT. ***CONFIDENTIAL NOT FOR SALE OR GENERAL RELEASE***

A key component of Geoscience Australia's marine program involves developing products that contain spatial information about the seabed for Australia's marine jurisdiction. This spatial information is derived from sparse or unevenly distributed samples collected over a number of years using many different sampling methods. Spatial interpolation methods are used for generating spatially continuous information from the point samples. These methods are, however, often data- or even variable- specific and it is difficult to select an appropriate method for any given dataset. Machine learning methods, like random forest (RF) and support vector machine (SVM), have proven to be among the most accurate methods in disciplines such as bioinformatics and terrestrial ecology. However, they have been rarely previously applied to the spatial interpolation of environmental variables using point samples. To improve the accuracy of spatial interpolations to better represent the seabed environment for a variety of applications, including prediction of biodiversity and surrogacy research, Geoscience Australia has conducted two simulation experiments to compare the performance of 14 mathematical and statistical methods to predict seabed mud content for three regions (i.e., Southwest, North, Northeast) of Australia's marine jurisdiction Since 2008. This study confirms the effectiveness of applying machine learning methods to spatial data interpolation, especially in combination with OK or IDS, and also confirms the effectiveness of averaging the predictions of these combined methods. Moreover, an alternative source of methods for spatial interpolation of both marine and terrestrial environmental properties using point survey samples has been identified, with associated improvements in accuracy over commonly used methods.