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.

<div>The Abbot Point to Hydrographers Passage bathymetry survey was acquired for the Australian Hydrographic Office (AHO) onboard the RV Escape during the period 6 Oct 2020 – 16 Mar 2021. This was a contracted survey conducted for the Australian Hydrographic Office by iXblue Pty Ltd as part of the Hydroscheme Industry Partnership Program. The survey area encompases a section of Two-Way Route from Abbot Point through Hydrographers Passage QLD. Bathymetry data was acquired using a Kongsberg EM 2040, and processed using QPS QINSy. The dataset was then exported as a 30m resolution, 32 bit floating point GeoTIFF grid of the survey area.</div><div>This dataset is not to be used for navigational purposes.</div>

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

Seismic interval velocities derived from stacking velocities can provide some clues to determination of rock lithology. This concept has been applied to understand the divergent dipping reflector (DDR) and seaward dipping reflector (SDR) packages over the Wallaby Plateau and Wallaby Saddle that were imaged on the 2008/2009 seismic survey GA310 contracted by Geoscience Australia. Root mean square velocities (Vrms) used to calculate interval velocities (Vint) were derived from long cable data. Vrms were picked on traces after pre-stack time migration, and the 4th order normal move-out (NMO) correction was implemented. Therefore, distortions to interval velocities due to insufficient curvature of NMO curve at short offsets, structural dip and ray bending due to stratification are assumed to be largely suppressed. Consequently Vrms velocities are assumed to approximate average velocities.

Marine physical and geochemical data can be valuable in predicting the potential distributions and assemblages of marine species, acting as surrogate measures of biodiversity. The results of surrogacy analysis can also be useful for identifying ecological processes that link physical environmental attributes to the distribution of seabed biota. This paper reports the results of a surrogacy study in Jervis Bay, a shallow-water, sandy marine embayment in south-eastern Australia. A wide range of high-resolution co-located physical and biological data were employed, including multibeam bathymetry and backscatter data and their derivatives, parameters that describe seabed sediment and water column physical characteristics, seabed exposure, and infauna species. The study applied three decision tree models and a robust model selection process. The results show that the model performance for three diversity indices and seven out of eight infauna species range from acceptable to good. Important surrogates for infauna diversity and species distributions within the mapped area are broad-scale habitat type, seabed exposure, sediment nutrient status, and seabed rugosity and heterogeneity. The results demonstrate that abiotic environmental parameters of a sandy embayment can be used to effectively predict infauna species distributions and biodiversity patterns. International Journal of Geographical Information Science

The northern Australian continental shelf is the focus for an expanding offshore energy industry and is also recognised for its high-value marine biodiversity in regional marine management plans. To reduce uncertainty and risk in the future development and management of the region, Geoscience Australia has an ongoing program to provide integrated marine environmental information to support both activities. The program includes collation of existing marine data and acquisition of new high resolution datasets. In 2009 and 2010, marine surveys in eastern Joseph Bonaparte Gulf were completed to characterise the seabed in representative areas, assess potential for geohazards and identify unique or sensitive benthic habitats. Data acquired included multibeam sonar bathymetry (~1900 km2), shallow (<120 m) sub-bottom profiles, sediment grabs and shallow (2-5 m) cores, towed video and epibenthic sleds. Geomorphic features mapped range from expansive soft-sediment plains, to isolated carbonate banks that rise tens of metres and incised valleys up to 200 m deep. Each feature is characterised by a distinctive biota, ranging from coral and sponge gardens on banks to diverse infaunal communities across plains. Geohazards include potential for localised slumping in valleys and escape of subsurface fluid/gas from plains and valley floors. To facilitate uptake of this information, results are integrated as generalised graphical models representing key spatial patterns of shelf ecosystems. This work has led to further work in targeted areas of the Gulf as part of a new four-year Australian Government program to inform geological and environmental assessments of offshore basins for CO2 storage.

Map showing Australia's Maritime Jurisdiction in the Torres Strait on a blue imagery background made from data collected from research vessels and/or derived from satellite imagery. Additional information includes the Special Quarantine Zone for the Australia Quarantine Inspection Service.

Spatial interpolation methods for generating spatially continuous data from point locations of environmental variables are essential for ecosystem management and biodiversity conservation. They can be classified into three groups (Li and Heap 2008): 1) non-geostatistical methods (e.g., inverse distance weighting), 2) geostatistical methods (e.g., ordinary kriging: OK) and 3) combined methods (e.g. regression kriging). Machine learning methods, like random forest (RF) and support vector machine (SVM), have shown their robustness in data mining fields. However, they have not been applied to the spatial prediction of environmental variables (Li and Heap 2008). Given that none of the existing spatial interpolation methods is superior to the others, several questions remain, namely: 1) could machine learning methods be applied to the spatial prediction of environmental variables; 2) how reliable are their predictions; 3) could the combination of these methods with the existing interpolation methods improve the predictions; and 4) what contributes to their accuracy? To address these questions, we conducted a simulation experiment to compare the predictions of several methods for mud content on the southwest Australian marine margin. In this study, we discuss results derived from this experiment, visually examine the spatial predictions, and compare the results with the findings in previous publications. The outcomes of this study have both practical and theoretical importance and can be applied to the spatial prediction of a range of environmental variables for informed decision making in environmental management. This study reveals a new direction in and provides alternative methods for spatial interpolation in environmental sciences.

PLEASE NOTE: These data have been updated. See Related Links for new data. Geodatabase of the Commonwealth Coastal Waters (State/Territory Powers) Act 1980 - An Act to extend the legislative powers of the States/Northern Territory in and in relation to coastal waters.

South East Queensand (SEQ) 2009 LiDAR data was funded by Queensland Department of Environment and Resource management (DERM) , which was captured and delivered by AAMHatch between March 25th 2009 and June 9th 2009. The project area covering 5300 sqkm was divided into three sub areas, namely South East Queensland Priority Area, Gold Coast and the Balance of SEQ. Data acquisition and post-processing has been controlled to achieve a vertical accuracy witihn 0.15m (RMS, 68% CI) and horizontal accuracy within 0.45 m. Horizontal coordinates are based upon Map Grid of Australia (MGA) Zone 56 projection. Vertical coordinates are referenced to Australian Height Datum (AHD). The data was captured with point density of 2.5 points per square metre and the data is available as mass point files (ASCII, LAS) and ESRI GRID files with 1m grid spacing in 1km tiles and inundation contours (0.25m). A hydrologically conditioned and drainage enforced 2m DEM or HDEM has also been developed in 2010 as part of the Urban DEM project managed by the CRC for Spatial Information and Geoscience Australia. The HDEM was produced by SKM using the ANUDEM program. Hydrologic enforcement and conditioning has included the testing of data for sinks, the referencing of transport and hydrology vector layers for intersections and flow, and the use of high-resolution imagery for visual validation. The methodology for hydrologic enforcement has required deriving a stream network based on flow direction and accumulation, using TIN and ANUDEM processes to analyse sinks and artificial damming affects caused by objects such as roads, bridges and trees which have not been previously filtered. Break lines have been included via the insertion of culvert/drainage channels, which has been used to interpolate these features into the main DEM as descending grid values. All data are referenced to GDA94/MGA Zone 56.