The radiometric, or gamma-ray spectrometric method, measures the natural variations in the gamma-rays detected near the Earth's surface as the result of the natural radioactive decay of potassium (K), uranium (U) and thorium (Th). The data collected are processed via standard methods to ensure the response recorded is that due only to the rocks in the ground. The results produce datasets that can be interpreted to reveal the geological structure of the sub-surface. The processed data is checked for quality by GA geophysicists to ensure that the final data released by GA are fit-for-purpose. This radiometric potassium grid has a cell size of 0.0005 degrees (approximately 50m) and shows potassium element concentration of the Balta Baltana Creek, SA, 1986 (86SA03) (74sa) survey. The data used to produce this grid was acquired in 2000 by the SA Government, and consisted of UNKNOWN line-kilometres of data at 300.0m line spacing and 80.0m terrain clearance.

The radiometric, or gamma-ray spectrometric method, measures the natural variations in the gamma-rays detected near the Earth's surface as the result of the natural radioactive decay of potassium (K), uranium (U) and thorium (Th). The data collected are processed via standard methods to ensure the response recorded is that due only to the rocks in the ground. The results produce datasets that can be interpreted to reveal the geological structure of the sub-surface. The processed data is checked for quality by GA geophysicists to ensure that the final data released by GA are fit-for-purpose. This radiometric thorium grid has a cell size of 0.000971 degrees (approximately 100m) and shows thorium element concentration of the UNKNOWN survey. The data used to produce this grid was acquired in UNKNOWN by the UNKNOWN Government, and consisted of UNKNOWN line-kilometres of data at UNKNOWNm line spacing and UNKNOWNm terrain clearance.

This is a placeholder record only. The product may be released by GA in the future, but at the moment we are only hosting the metadata.

This is a placeholder record only. The product may be released by GA in the future, but at the moment we are only hosting the metadata.

This map shows the estimated extent of banana plantations that have been detected on the RADARSAT-2 image acquired on 2nd February 2011, two days prior to Tropical Cyclone Yasi (TC Yasi) impacting the area. Map is topographic data on a imagery background.

The national geodetic program in Australia is undertaken by the National Geospatial Reference System (NGRS) Section within Geoscience Australia. The NGRS is a continually evolving system of infrastructure implemented through the existing geodetic techniques such as Satellite Laser Ranging (SLR), Global Navigation Satellite Systems (GNSS) and Very Long Baseline Interferometry (VLBI). The NGRS serves the broader community by providing an accurate foundation for positioning, and consequently all spatial data, against which every position in Australia is measured and can be legally traced. In Australia, the sparsity of geodetic infrastructure has limited the developments of geodetic applications. For instance, the Geocentric Datum of Australia 1994 (GDA94) was based on observations (1992 - 1994) from a sparse network of Continuously Operating Reference Station (CORS) called the Australian Fiducial Network (AFN). Since that time the demand for higher accuracies has resulted in GDA94 no longer adequately serving user demand. The adoption of a fully dynamic datum will ensure that Australians can use positioning technology to its fullest capability, whereas at present when using GDA94 they are limited to the accuracy that was achievable in 1994 when GDA94 was created. Consequently, national infrastructure development programs, such as AuScope, have been implemented to improve the geodetic accuracies by contributing to the next generation of the Global Geodetic Observing System (GGOS). This presentation reviews the national geodetic activities in Australia, especially the AuScope program, a recent enhancement to the Australian geodetic infrastructure.

Known magmatic-related uranium mineralisation is rare in Australia, despite the widespread occurrence of uranium-rich igneous rocks. Known intrusive-related mineralisation is almost entirely restricted to South Australia, while uranium mineralisation related to volcanic rocks is mostly known from northern Queensland. This apparent discrepancy suggests that Australia is under-represented in this category of uranium mineral system, and as such, the potential for future discoveries is inferred to be high. Recent work by Geoscience Australia has sought to enhance the prospectivity for a range of uranium mineral system types in Australia, including those related to magmatic rocks, by undertaking regional scale assessments of the potential for these systems. Using a similar approach, an assessment for the potential for magmatic-related uranium mineral systems has been undertaken in a systematic manner on a national scale. This has been done in a GIS environment using the fuzzy logic method, which allows for uncertainty to be captured while being relatively easy to implement. Two subcategories of magmatic-related uranium systems have been assessed: intrusive- and volcanic-related. Rather than attempting to identify specific sites of mineralisation, this investigation has focused on delineating those igneous units and events which have the highest potential for a magmatic-related uranium mineral system to operate. This allows for potentially prospective tracts to be readily identified, in which the mineral potential and uranium depositional sites may be refined using detailed local knowledge and datasets. Potentially prospective igneous rocks have been identified in all States and Territories where uranium exploration is currently permitted, including regions already known for magmatic-related uranium occurrences. Significantly, this study has identified high potential in regions which are currently not well known for magmatic-related uranium mineralisation.

This Record presents data collected as part of the ongoing NTGS-GA geochronological collaboration between July 2000 and June 2011 under the National Geoscience Agreement (NGA). This record presents new SHRIMP U-Pb zircon and monazite geochronological results for 18 samples from the Arunta Region, Davenport Province, Simpson Desert and Pine Creek Orogen in the Northern Territory. Five Paleoproterozoic igneous and metasedimentary samples were collected from the Eastern Arunta (ILLOGWA CREEK), and one metasedimentary sample from the eastern Casey Inlier (HALE RIVER). One igneous volcanic sample and two metasedimentary samples are from the Davenport Province (MAPSHEET) and Simpson Desert regions (HAY RIVER), respectively. Ten samples in total were collected from the Pine Creek Orogen; one igneous sample from DARWIN, the remainder being igneous and metasedimentary samples from the Nimbuwah Domain (ALLIGATOR RIVER).

One of the important inputs to a probabilistic seismic hazard assessment is the expected rate at which earthquakes within the study region. The rate of earthquakes is a function of the rate at which the crust is being deformed, mostly by tectonic stresses. This paper will present two contrasting methods of estimating the strain rate at the scale of the Australian continent. The first method is based on statistically analysing the recently updated national earthquake catalogue, while the second uses a geodynamic model of the Australian plate and the forces that act upon it. For the first method, we show a couple of examples of the strain rates predicted across Australia using different statistical techniques. However no matter what method is used, the measurable seismic strain rates are typically in the range of 10-16s-1 to around 10-18s-1 depending on location. By contrast, the geodynamic model predicts a much more uniform strain rate of around 10-17s-1 across the continent. The level of uniformity of the true distribution of long term strain rate in Australia is likely to be somewhere between these two extremes. Neither estimate is consistent with the Australian plate being completely rigid and free from internal deformation (i.e. a strain rate of exactly zero). This paper will also give an overview of how this kind of work affects the national earthquake hazard map and how future high precision geodetic estimates of strain rate should help to reduce the uncertainty in this important parameter for probabilistic seismic hazard assessments.

Geoscience Australia has developed a wind hazard model for estimating the risk posed by peak wind gusts. In this study we have utilised the regional return period wind gusts as defined in the Australian/New Zealand wind loading standard (AS/NZS 1170.2, 2002) and applied the methodology detailed in the standard. In addition, our association with Dr. John Holmes (chairperson of the Australian Wind Loading committee) allowed us to make a significant attempt to remove the conservatism associated with the wind loading standard. Geoscience Australia entered into discussions with Dr. Holmes which resulted in a consultancy that reviewed the Geoscience Australia wind risk methodology and vulnerability model development (Holmes, 2004). Geoscience Australia's basic approach is detailed in the Perth Cities report (Lin et al., 2005). In the present study we build on that earlier work by examining three other city regions and contrasting the results. Each component of the methodology is described in this section with a brief overview provided below: Estimated return period regional wind speeds (for peak 3 second gusts at a height of 10 metres in open level terrain) were obtained from AS/NZS 1170.2. The local wind effects on these return period regional wind speeds were determined by assessing the local effect of terrain at the structure height of interest, the shielding effect on the structure and the topographic effect. These effects were numerically estimated using remote sensing techniques, digital elevation data and by using formulae given in AS/NZS 1170.2. Finally, the estimation of the local wind speeds that would be equalled or exceeded within a given time period (commonly called return period wind speeds or return levels) was derived by combining the local wind multipliers (terrain/height, shielding and topographic) for 8 cardinal directions with the return period regional wind speeds (from AS/NZS 1170.2) across a 25 by 25 metre grid covering each study region.