In 2010, a network of Marine Protected Areas (MPAs) was proposed for the East Antarctic region. This proposal was based on the best available data, which for the benthic regime consisted chiefly of seabed geomorphology and satellite bathymetry data. Case studies from the East Antarctic region indicate that depth and morphology are important factors in delineating marine benthic communities, particularly on the continental shelf. However, parameters such as sediment composition also show a strong association with the distribution and diversity of benthic assemblages. A better assessment of the nature of benthic habitats within the proposed MPA network is now possible with the incorporation of a compilation of sediment properties and higher resolution bathymetry grids across the East Antarctic region (see Figures A and B). Based on these physical properties, and in combination with the seabed morphology, we can now distinguish a range of distinct habitats, such as deep muddy basins, scoured sandy shelf banks, ruggedly eroded slope canyons and muddy deep sea plains. In this presentation, we assess the types of benthic habitats across the East Antarctic region, and then determine how well the proposed MPA network represents the diversity of habitats across this margin. The diversity of physical environments within the proposed MPAs suggests that they likely support a diverse range of benthic communities which are broadly representative of the surrounding region.

Spatially continuous information is often required for environmental planning and conservation. Spatial modelling methods are essential for generating such information from point samples. The accuracy of spatial predictions is crucial for evidence-based decision making and often affected by many factors. Spatial reference systems can alter the features of spatial data and thus are expected to affect the predictions of spatial modelling methods. However, the degree to which such systems can affect the predictions has not been examined yet. It is not clear whether such effect changes with spatial modelling methods neither. In this study, we aim to test how sensitive spatial modelling methods are to different spatial reference systems. On the basis of a review of different spatial reference systems, we select eight systems that are suitable for environmental variables for the Australian Exclusive Economic Zone. We apply two most commonly used spatial interpolation methods to a marine dataset that is projected using the eight systems. Finally we assess the accuracy of the methods using leave-one-out cross validation in terms of their predictive errors. The sensitivities of the spatial modelling methods to the eight spatial reference systems are then analyzed. The data manipulation and modelling work are implemented in ArcGIS and R. In this paper, we discuss the testing results; examine the spatial predictions visually; and discuss the implications of the findings on spatial predictions in the marine environmental sciences. The outcomes of this study can be applied to the spatial predictions of both marine and terrestrial environmental variables. ModSim 2013, Adelaide, South Australia

Geoscience Australia Flyer prepared for LOCATE14.

Geoscience Australia defines a borehole as the generalized term for any narrow shaft drilled in the ground, either vertically or horizontally, and would include Mineral Drillholes, Petroleum Wells and Water Bores along with a variety of others types, but does not include Costean, Trench or Pit. For the purpose of a borehole as defined by GeoSciML Borehole 3.0, the dataset has been restricted to onshore and offshore Australian boreholes, and bores that have the potential to support geological investigations and assessment of a variety of resources.

Geoscience Australia's entry to the ASC2014 SPECTRUM science-art exhibition Title: Seeing Water Through Time Author: Norman Mueller Type: Science Communication image Description: The WOfS, Water Observations from Space, image is a colour-scale of how many times water was detected from the Landsat 5 and 7 satellites over central Australia from 1998 to 2012. The colours range from very low number of times (red) to very high number of times (blue), using a standard rainbow colour scheme (red-orange-yellow-green-blue). This means that red areas are hardly ever wet while blue areas are more permanent water features like lakes. The area covered includes Lake Eyre (at left) Cooper Creek (right of centre) to the Paroo River (bottom right).

Understanding surface water resources is important for communities, agriculture and the environment, especially in water-limited environments. In 2014 Geoscience Australia released the Water Observations from Space (WOfS) product, providing information on the presence of surface water across the Australian continent from 27 years of Landsat satellite imagery. WOfS was created to provide insight into the extent of flooding anywhere in Australia, but broader applications are emerging in the areas of wetland behaviour, river system mapping, groundwater surface water interaction, and water body perenniality. Understanding the characteristics of inundation for every waterbody across a county, over a period of time, gives a greater knowledge of perenniality and helps support decision making for a wide range of users including aquatic ecological community and water resource management. WOfS provides a consistent tool to locate and characterise water bodies at the continental scale.

This dataset provides the spatially continuous data of seabed gravel (sediment fraction >2000 µm), mud (sediment fraction < 63 µm) and sand content (sediment fraction 63-2000 µm) expressed as a weight percentage ranging from 0 to 100%, presented in 0.0025 decimal degree (dd) resolution raster grids format and ascii text file. The dataset covers the Petrel sub-basin in the Australian continental EEZ. This dataset supersedes previous predictions of sediment gravel, mud and sand content for the basin with demonstrated improvements in accuracy. Accuracy of predictions varies based on density of underlying data and level of seabed complexity. Artefacts occur in this dataset as a result of insufficient samples in relevant regions. This dataset is intended for use at the basin scale. The dataset may not be appropriate for use at smaller scales in areas where sample density is insufficient to detect local variation in sediment properties. To obtain the most accurate interpretation of sediment distribution in these areas, it is recommended that additional samples be collected and interpolations updated.

This study explored the full potential of high-resolution multibeam data for an automatic and accurate mapping of complex seabed under a predictive modelling framework. Despite of the extremely complex distributions of various hard substrata at the inner-shelf of the study area, we achieved a nearly perfect prediction of 'hard vs soft' classification with an AUC close to 1.0. The predictions were also satisfactory for four out of five sediment properties, with R2 values range from 0.55 to 0.73. In general, this study demonstrated that both bathymetry and backscatter information (from the multibeam data) should be fully utilised to maximise the accuracy of seabed mapping. From the modelled relationships between sediment properties and multibeam data, we found that coarser sediment generally generates stronger backscatter return and that deeper water with its low energy favours the deposition of mud content. Sorting was also found to be a better sediment composite property than mean grain size. In addition, the results proved one again the advantages of applying proper feature extraction approaches over original backscatter angular response curves.

This web service contains marine geospatial data held by Geoscience Australia. It includes bathymetry and backscatter gridded data plus derived layers, bathymetry coverage information, bathmetry collection priority and planning areas, marine sediment data and other derived products. It also contains the 150 m and optimal resolution bathymetry, 5 m sidescan sonar (SSS) and synthetic aperture sonar (SAS) data collected during phase 1 and 2 marine surveys conducted by the Governments of Australia, Malaysia and the People's Republic of China for the search of Malaysian Airlines Flight MH370 in the Indian Ocean. This web service allows exploration of the seafloor topography through the compilation of multibeam sonar and other marine datasets acquired.

Geoscience Australia defines a borehole as the generalized term for any narrow shaft drilled in the ground, either vertically or horizontally, and would include Mineral Drillholes, Petroleum Wells and Water Bores along with a variety of others types, but does not include Costean, Trench or Pit. For the purposes of a Water Well as defined by Groundwater ML v1.0, the dataset has been restricted to onshore Australian boreholes only, and bores that have the potential to support assessment of groundwater resources, within a Bioregional Assessment.