Very short News item for ASEG's Preview newsletter announcing the availability of the Tasman Frontier Geophysical Data Base

We describe a new framework for quantitative bushfire risk assessment that has been produced in the Bushfire Cooperative Research Centre's (Bushfire CRC) research program. The framework is aimed at assisting state of the art fire research in Australia and fire risk managers in state and territory governments. There is a need for improved bushfire risk information to address the recommendations on bushfire risk management from the inquiries held after disastrous fires in the past decade. Quantitative techniques will improve this risk information however quantitative bushfire risk assessment is in its infancy in Australia. We use the example of calculating house damage and loss to describe the elements of the framework. The framework builds upon the well-defined processes in the Australian Risk Management standard (AS/NZS ISO 31000:2009) and the National Emergency Risk Assessment Guidelines.

Overview of the Deep Crustal Seismic surveys conducted by Geoscience Australia and funded through the Onshore Energy Security Program since it's commencement in 2006 to September 2009.

We measured the light absorption properties of two naturally occurring Australian hydrocarbon oils, a Gippsland light crude oil and a North West Shelf light condensate. Using these results in conjunction with estimated sensor environmental noise thresholds, the theoretical minimum limit of detectability of each oil type (as a function of oil thickness) was calculated for both the hyperspectral HYMAP and multispectral Quickbird sensors. The Gippsland crude oil is discernable at layer thickness of 20 micro metres or more in the Quickbird green channel. The HYMAP sensor was found to be theoretically capable of detecting a layer of Gippsland crude oil with a thickness of 10 micro metres in approximately six sensor channels. By contrast, the North West Shelf light condensate was not able to be detected by either sensor for any thickness up to 200 icro metres. Optical remote sensing is therefore not applicable for detecting diagnostic absorption features associated with this light condensate oil type, which is considered representative for the prospective Australian Northwest Shelf area. We conclude that oil type is critical to the applicability of optical remote sensing for natural oil slick detection and identification. We recommend that a sensor- and oil-specific sensitivity study should be conducted prior to applying optical remote sensors for oil exploration. The oil optical properties were obtained using two different laboratory methods, a reflectance-based approach and transmittance-based approach. The reflectance-based approach was relatively complex to implement, but was chosen in order to replicate as closely as possible real world remote sensing measurement conditions of an oil film on water. The transmittance-based approach, based upon standard laboratory spectrophotometric measurements was found to generate results in good agreement with the reflectance-based approach. Therefore, for future oil- and sensor-specific sensitivity studies, we recommend the relatively accessible transmittance-based approach, which is detailed in this paper.

The Albany Canyon complex off southwest Australia extends 700 km from Cape Leeuwin to east of Esperance. The Canyons head on the uppermost continental slope and extend up to 90 km offshore, to the lowermost slope and onto the abyssal plain. The largest have cut down 1500-2000 m in places. In general, on the upper slope they have cut down into harder, older rocks: Canyon walls are steep, thalwegs slope at up to 15?, and ancient structures control their orientation. On the lower slope the Canyons generally have not reached harder rocks, Canyon walls are less steep, thalweg slopes are less, and they are generally oriented down slope. The Canyons have exposed Jurassic and younger sequences: their nature and information from seismic profiles, have helped us build an understanding of Canyon history. Flood plain deposition rather than erosion occurred during Australia-Antarctic rifting in the Late Jurassic, not supporting cutting of river Canyons. Shallow marine sedimentation characterised the Early Cretaceous, when gradients were low and Canyon cutting unlikely. Deep river Canyons were probably cut during uplift and erosion immediately before the Santonian break-up from Antarctica, and their paths controlled later marine Canyons. Only with the onset of rapid seafloor spreading and subsidence in the Middle Eocene (~43 Ma) did gradients steepen and major marine Canyon cutting become possible. The major sea level fall at the Middle/Late Eocene boundary (~40 Ma) brought sediment to the edge of the continental shelf, which may have initiated the Canyons. Carbonate sedimentation replaced siliciclastic sedimentation in the Late Middle Eocene, but carbonate grains from the outer shelf could cut the Canyons, largely during periods of low sea level.

The Leeuwin Current has significant ecological impact on the coastal and marine ecosystem of south-western Australia. This study investigated the spatial and temporal dynamics of the Leeuwin Current using monthly MODIS SST dataset between July 2002 and December 2012. Topographic Position Index layers were derived from the SST data for the mapping of the spatial structure of the Leeuwin Current. The semi-automatic classification process involves segmentation, 'seeds' growing and manual editing. The mapping results enabled us to quantitatively examine the current's spatial and temporal dynamics in structure, strength, cross-shelf movement and chlorophyll a characteristic. It was found that the Leeuwin Current exhibits complex spatial structure, with a number of meanders, offshoots and eddies developed from the current core along its flowing path. The Leeuwin Current has a clear seasonal cycle. During austral winter, the current locates closer to the coast (near shelf break), becomes stronger in strength and has higher chlorophyll a concentrations. While, during austral summer, the current moves offshore, reduces its strength and chlorophyll a concentrations. The Leeuwin Current also has notable inter-annual variation due to ENSO events. In El Niño years the current is likely to reduce strength, move further inshore and increase its chlorophyll a concentrations. The opposite occurs during the La Niña years. In addition, this study also demonstrated that the Leeuwin Current has a significantly positive influence over the regional nutrient characteristics during the winter and autumn seasons. Apart from surface cooling and advection, the Leeuwin Current's sizable cross-shelf movement may be another contributing factor to the seasonal and inter-annual variations of its chlorophyll a concentrations.

One page article discussing aspects of Australian stratigraphy; this article discusses new unit definitions, ne regional publications and changes to the membership of the Australian Stratigraphy Commission.

The spectral signature of an about 1 micrometer thick oil slick has been identified from airborne hyperspectral data (HyMap sensor) acquired over a floating oil production facility located on the North West Shelf of Australia. The paper describes spectral characteristrics of the signature and identifies conditions in which it can be observed.

Obtaining reliable predictions of the subsurface will provide a critical advantage for explorers seeking mineral deposits at depth and beneath cover. A common approach in achieving this goal is to use deterministic property-based inversion of potential field data to predict a 3D subsurface distribution of physical properties that explain measured gravity or magnetic data. Including all prior geological knowledge as constraints on the inversion ensures that the recovered predictions are consistent with both the geophysical data and the geological knowledge. Physical property models recovered from such geologically-constrained inversion of gravity and magnetic data provide a more reliable prediction of the subsurface than can be obtained without constraints. The non-uniqueness of inversions of potential field data mandates careful and consistent parameterization of the problem to ensure realistic solutions.

No abstract available