The National Geochemical Survey of Australia (NGSA) project (www.ga.gov.au/ngsa), part of Geoscience Australia's Onshore Energy Security Program 2006-2011, was carried out in collaboration with all state and territory geological surveys. It delivered Australia's first national geochemical atlas, the underpinning geochemical database, and a series of reports and papers. Catchment outlet sediments (mostly similar to floodplain sediments) were sampled in 1186 catchments covering ~6.2 million km2 or ~81% of the country (on average one sample per 5200 km2). Samples were collected at two depths (0-10 cm and ~60-80 cm), each sieved to two grain size fractions (<2 mm and <75 mm) and analysed for total, aqua regia, and Mobile Metal Ion® element contents; other analyses (pH, electrical conductivity, grain size distribution, spectroscopy, etc.) were also performed. Results to date have been used to: (1) investigate first-order controls on the geochemical makeup of Australian regolith in comparison to Europe; (2) compile preliminary, multi-continental, empirical 'Global Soil' reference values; (3) produce continental-scale soil pH maps; (4) map Fe oxide mineralogy and soil colour; (5) investigate the level and distribution of bioavailable elements in Australia; (6) determine element associations by multivariate statistical methods and compare resulting patterns to independent geoscience datasets; (7) model the distribution of soil carbonate using multiple environmental covariates; (8) assess the potential of the dataset for mineral prospectivity analysis (e.g., for base metals, U, Au and REEs); (9) select salt lakes to be investigated for their potential to host potash, Li and B resources; (10) ground truth, infill and 'correct' airborne radiometric concentration data for K, U and Th; and (11) shed light on the phenomenon of disequilibrium in the radioactive decay chain of U by comparing actual to estimated U concentrations at the continental scale. The NGSA project was Australia's first national-scale geochemical survey, requiring certain strategic decisions to be taken about sampling medium, density, etc. The resulting atlas and dataset have proven useful and applicable to many end-uses, but limitations and challenges exist as in every geochemical survey.

Presentation to be delivered at the Western Australian Marine Science Institution Symposium, Fremantle, 21 February Abstract text: Geoscience Australia, as the Australian Government's geoscience agency, has a long history of marine environment mapping and research on the North West Shelf of Australia. In recent times, several data acquisition surveys have been completed and subsequent interpretive products have been produced under Commonwealth Government programmes, including: the Offshore Energy Security Program (2006-2011); the Marine Biodiversity Hub under the Commonwealth Environmental Research Facilities (CERF) and the National Environmental Research Program (NERP), and; the National CO2 Infrastructure Plan (NCIP, 2011-15). Collaborations, such as those facilitated by CERF and NERP, and with the Australian Institute of Marine Science (AIMS), have resulted in further work in the region. Areas of investigation have included the North Perth Basin, Bonaparte Gulf and Timor Sea. Using data from these surveys and other sources, GA is continuing to develop regional-scale seabed datasets, including bathymetry, geomorphology, sediment properties, seabed disturbance and seabed hardness that are publicly available via the internet. A pilot program was started in 2010 to collate and archive environmental data generated by the offshore petroleum industry, with a focus on the North West Shelf. Geoscience Australia is currently undertaking marine surveys to provide seabed environmental information to support assessments of the CO2 storage potential of several offshore sedimentary basins under NCIP. A marine survey over the Browse Basin in May 2013, to be undertaken in collaboration with the AIMS, will acquire high-resolution bathymetry and information on seabed and shallow subsurface geology and ecology. Follow-up surveys are also proposed during 2013-2015. The Browse survey results will be publicly released as a data package integrating existing and the newly acquired seabed data, and in a report to the Department of Resources Energy and Tourism on the CO2 storage potential of selected areas of the Browse Basin.

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 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.

In this study, we aim to identify the most accurate methods for spatial prediction of seabed gravel content in the northwest Australian Exclusive Economic Zone. We experimentally examined: 1) whether input secondary variables affect the performance of RFOK and RFIDW, 2) whether the performances of RF, SIMs and their hybrid methods are data-specific, and 3) whether model averaging improves predictive accuracy of these methods in the study region. For RF and the hybrid methods, up to 21 variables were used as predictors. The predictive accuracy was assessed in terms of relative mean absolute error and relative root mean squared error based on the average of 100 iterations of 10-fold cross validation. In this study, the following important findings were achieved: - the predictive errors fluctuate with the input secondary variables; - the existence of correlated variables can alter the results of model selection, leading to different models; - the set of initial input variables affects the model selected; - the most accurate model can be missed out during the model selection; - RF, RFOK and RFIDW prove to be the most accurate methods in this study, with RFOK preferred; and these methods are not data-specific, but their models are, so best model needs to be identified; and - Model averaging is clearly data-specific. In conclusion, model selection is essential for RF and the hybrid methods. RF and the hybrid methods are not data-specific, but their models are. RFOK is the most accurate method. Model averaging is also data-specific. Hence best model needs to be identified for individual studies and application of model averaging should also be examined accordingly. RF and the hybrid methods have displayed substantial potentials for predicting environmental properties and are recommended for further test for spatial predictions in environmental sciences and other relevant disciplines in the future. This study provides suggestions and guidelines for improving the spatial predictions of biophysical variables in both marine and terrestrial environments.

This presentation will provide an overview of geological storage projects and research in Australia.

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.

This video explains the concept behind Geoscience Australia's Data Cube, a new way of organising, analysing and managing the large amounts of data collected from Earth Observation Satellites (EOS) studies over time. The Data Cube facilitates efficient data analysis and enables users to interrogate Australia's EOS data from the past and present. It is hoped that the Data Cube will become a useful tool used by remote sensing scientists and data analysts to extract information to support for informing future decision-making and policy development within Australia.

Data package containing an ESRI shapefile and associated comma-separated value table (.csv) of the Pacific islands, including the countries of Cook Islands, Federated States of Micronesia, Fiji, Kiribati, Nauru, Niue, Palau, Papua New Guinea, Republic of Marshall Islands, Samoa, Solomon Islands, Tokelau, Tonga, Tuvalu and Vanuatu. The ESRI shapefile contains polygons of the islands and has been adapted from the World Vector Shoreline dataset, with original scale suitability of 1:250,000 (reference: Soluri, E.A. and Woodson, V.A. 1990. World Vector Shoreline. International Hydrographic Review LXVII(1)). See lineage for more information. The .csv file contains tabular data associated with the island polygons. The file has been adapted to suit the purposes of the companion report by Dixon-Jain et al. (2014). The island polygon shapefile and .csv file can be joined using the common UniqueID field. The attribute fields within the .csv file include island hydrogeological and physical characteristics. Relative ratings for component of the potential vulnerability framework are included for the two projection periods (2035-2064 and 2070-2099), for each climate hazard (low rainfall periods and mean sea-level rise). See the field list within lineage in the Data Dictionary for more information on the source of each attribute. The full bibliographic reference for the companion report (catalogue number 79066) is: Dixon-Jain, P., Norman, R., Stewart, G., Fontaine, K., Walker, K., Sundaram, B., Flannery, E., Riddell, A., Wallace, L. 2014. Pacific Island Groundwater and Future Climates: First-Pass Regional Vulnerability Assessment. Record 2014/43. Geoscience Australia, Canberra. http://dx.doi.org/10.11636/Record.2014.043

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.