The Brattstrand Paragneiss, a highly deformed Neoproterozoic granulite-facies metasedimentary sequence, is cut by three generations of ~500 Ma pegmatite. The earliest recognizable pegmatite generation, synchronous with D2-3, forms irregular pods and veins up to a meter thick, which are either roughly concordant or crosscut S2 and S3 fabrics and are locally folded. Pegmatites of the second generation, D4, form planar, discordant veins up to 20-30 cm thick, whereas the youngest generation, post-D4, form discordant veins and pods. The D2-3 and D4 pegmatites are abyssal class (BBe subclass) characterized by tourmaline + quartz intergrowths and boralsilite (Al16B6Si2O37); the borosilicates prismatine, grandidierite, werdingite and dumortierite are locally present. In contrast, post-D4 pegmatites host tourmaline (no symplectite), beryl and primary muscovite and are assigned to the beryl subclass of the rare-element class. Spatial correlations between B-bearing pegmatites and B-rich units in the host Brattstrand Paragneiss are strongest for the D2-3 pegmatites and weakest for the post-D4 pegmatites, suggesting that D2-3 pegmatites may be closer to their source. Initial 87Sr/86Sr (at 500 Ma) is high and variable (0.7479-0.7870), while -Nd500 tends to be least evolved in the D2-3 pegmatites (-8.1 to -10.7) and most evolved in the post-D4 pegmatites (-11.8 to -13.0). Initial 206Pb/204Pb and 207Pb/204Pb and 208Pb/204Pb ratios, measured in acid-leached alkali feldspar separates with low U/Pb and Th/Pb ratios, vary considerably (17.71-19.97, 15.67-15.91, 38.63-42.84), forming broadly linear arrays well above global Pb growth curves. The D2-3 pegmatites contain the most radiogenic Pb while the post-D4 pegmatites have the least radiogenic Pb; data for D4 pegmatites overlap with both groups. Broad positive correlations for Pb and Nd isotope ratios could reflect source rock compositions controlled two components. Component 1 (206Pb/204Pb-20, 208Pb/204-43, Nd -8) most likely represents old upper crust with high U/Pb and very high Th/Pb. Component 2 (206Pb/204Pb -18, 208Pb/204Pb~38.5, -Nd500 -12 to -14) has a distinctive high-207Pb/206Pb signature which evolved through dramatic lowering of U/Pb in crustal protoliths during the Neoproterozoic granulite-facies metamorphism. Component 1, represented in the locally-derived D2-3 pegmatites, could reside within the Brattstrand Paragneiss, which contains detrital zircons up to 2.1 Ga old and has a wide range of U/Pb and Th/Pb ratios. The Pb isotope signature of component 2, represented in the 'far-from-source' post-D4 pegmatites, resembles feldspar Pb isotope ratios in Cambrian granites intrusive into the Brattstrand Paragneiss. However, given their much higher 87Sr/86Sr, the post-D4 pegmatite melts are unlikely to be direct magmatic differentiates of the granites, although they may have broadly similar crustal sources. Correlation of structural timing with isotopic signatures, with a general sense of deeper sources in the younger pegmatite generations, may reflect cooling of the crust after Cambrian metamorphism.

The Surface Hydrology Points (Regional) dataset provides a set of related features classes to be used as the basis of the production of consistent hydrological information. This dataset contains a geometric representation of major hydrographic point elements - both natural and artificial. This dataset is the best available data supplied by Jurisdictions and aggregated by Geoscience Australia it is intended for defining hydrological features.

This dataset is the most current national compilation of catchment scale land use data for Australia (CLUM), as at March 2015. It is a seamless raster dataset that combines land use data for all state and territory jurisdictions, compiled at a resolution of 50 metres by 50 metres. It has been compiled from vector land use datasets collected as part of state and territory mapping programs through the Australian Collaborative Land Use and Management Program (ACLUMP). Catchment scale land use data was produced by combining land tenure and other types of land use information, fine-scale satellite data and information collected in the field. The date of mapping (1997 to 2014) and scale of mapping (1:20 000 to 1:250 000) vary, reflecting the source data capture date and scale. This information is provided in a supporting polygon dataset.

The video explains the challenges faced when managing vast quantities of satellite data, for the benefit of humankind, to address a range of environmental, social and agricultural issues. The video introduces the architecture of the Australian Geoscience Data Cube as a key tool for unlocking Earth observation satellite data, to better manage and store vast amounts of data. The Data Cube has already been used to for understanding water observations from Space and its related application for better flood management. The video also provides a case study of developing a satellite data management infrastructure for Kenya. This video was used to launch Australia¿s tenure as the Chair of the Committee of Earth Observation Satellites (CEOS) at the 2015 Plenary CEOS meeting held in Kyoto, Japan in November 2015. Detailed production information: Concept development: Alex Held (CSIRO), Jonathon Ross (Geoscience Australia), Stephen Ward (Symbios Communications), Bobby Cerini (GA), Stuart Minchin (GA), Alexis McIntyre (GA), Chris McKay (CSIRO) Scriptwriter: Bobby Cerini (Geoscience Australia) Production management/ Direction: Bobby Cerini (Geoscience Australia), Adrian King (Redboat) Post production: Adrian King (Redboat), Peter Butz (Redboat), Woro Larasati (Geoscience Australia), Neil Caldwell (Geoscience Australia), CSIRO Land and Water Animation: Neil Caldwell (Geoscience Australia), Stanislav Galan (Redboat), Artjom Zenevich (Redboat), Adrian King (Redboat), NASA Goddard Space Flight Centre Scientific Visualization Laboratory Videography: Andy Wong (Redboat), Michael O'Rourke (Geoscience Australia) Stock footage: European Space Agency, NASA, AFP, Rick Ray/Shutterstock.com, Stock4KVideo/Shutterstock.com, Rekindle Photo and Video/Shutterstock.com, Frazao Production/Shutterstock.com, paintings/Shutterstock.com Photography: NASA-SEO, Clinton Climate Initiative, Stephen Ward (Symbios Communications) Voice recording: AbesAudio Subtitles: Neil Caldwell (Geoscience Australia), Chantelle Farrar (Geoscience Australia)

The RadWaste Reporting Tool allows Dept of Industry and GHD staff to analyse and compare Multi Criteria Analysis (MCA) ratings of a site within a nominated location and ascertain the reason for the ranking and score. This tool also outputs a snapshot of the nominated site, giving a context map and scores against requirement criteria.

Exploration geologists are increasingly being inundated by a large volume and variety of digital spatial data. Unsupervised clustering algorithms, such as Self-Organizing Maps (SOM), provide an opportunity to gain insight into complex geological phenomena not evident from a single dataset. Unsupervised clustering algorithms are able to efficiently integrate and recognize patterns within 'Big Data' into manageable and interpretable outputs. This study demonstrates data fusion for mineral exploration and highlights the potential for data-driven clustering analysis to assist geoscientists in gaining robust understanding of the geological controls on mineralization in regolith dominated terrains. We interpret the nature of Uranium mineralization across the Australian continent by integrating remotely sensed, continental-scale geophysical and mineralogical data using SOM. We combine the outputs of our cluster analysis with Uranium mineral occurrence data (n = 1138) to construct prospectivity maps of regional Uranium mineralization for the Australian continent. Furthermore, we divide prospective areas into several unique groups. These groups represent subtle but significant differences in regolith and bedrock geophysical and mineralogical characteristics of Uranium mineralization targets. A total 11.94% of the samples input into the SOM analysis are likely to be prospective for Uranium mineralization. The resulting Uranium prospectivity map identifies the location of Uranium mines (operating and historic) with an accuracy 88.89% (n = 119). By interrogating the unique geophysical and mineralogical characteristics of Uranium prospectivity groups we can distinguish regions of: older landscapes with subdued topography dominated by arid climatic conditions and mechanical weathering processes; and relatively young landscapes over thin crust exhibiting moist climatic conditions and deeply weathered regolith profiles. These broad groups can be further subdivided into areas likely to represent magmatic-hydrothermal, unconformity and calcrete-hosted paleochannel Uranium deposits. The clustering analysis methodology presented here can be applied to the analysis of other bedrock and regolith associated mineral commodities and at local- and/or prospect-scales. Our techniques provide additional tools for the exploration geologist to develop a robust understanding of likely geological context of target mineralization. In turn, this will help to define the geological controls on mineralization and will contribute significantly to developing appropriate exploration strategies.

The `Inferred Isotopic Domain Boundaries of Australia data set is based on an interpretation of the recently released Neodymium depleted mantle model age map of Australia (GA Record 2013/44). The isotopic map of Australia was produced by gridding two-stage depleted mantle model ages calculated from Sm-Nd isotopic data for just over 1490 samples of felsic igneous rocks throughout Australia. The resultant isotopic map serves as a proxy for bulk crustal ages and accordingly allows the potential recognition of geological domains with differing geological histories. One of the major aims of the Neodymium depleted mantle model age map, therefore, was to use the isotopic map (and associated data) to aid in the recognition and definition of crustal blocks (geological terranes) at the continental and regional scale. Such boundaries are recognisable by regional changes in isotopic signature but are hindered by the variable and often low density of isotopic data points. Accordingly two major procedures have been adopted to locate the regional distribution of such boundaries across the geological continent. In areas of high data density (and high confidence), such as the Yilgarn Craton Western Australia, isotopic data alone was used to delineate crustal domains. In such regions it is evident that identified crustal blocks often but not universally approximate known geological terranes. In areas of moderate data density (and corresponding moderate confidence) (smoothed) boundaries of known geological provinces were used as a proxy for the isotopic boundary. For both high and moderate data densities identified crustal boundaries were extended (with corresponding less confidence) into regions of lower data density. In areas of low data density (and low confidence) boundaries were either based on other geological and/or geophysical data sets or were not attempted. The latter was particularly the case for regions covered by thick sedimentary successions. Two levels of confidence have been documented, namely the level of confidence in the location of the isotopic domain boundary, and the level of confidence that a boundary may actually exist. The `Inferred Isotopic Domain Boundaries of Australia map shows the locations of inferred boundaries of isotopic domains, which are assumed to represent the crustal blocks that comprise the Australia continent. The map therefore provides constraints on the three dimensional architecture of Australia, and allows a better understanding of how the Australian continent was constructed from the Mesoarchean through to the Phanerozoic. It is best viewed as a dynamic dataset, which will need to be refined and updated as new information, such as new isotopic data, becomes available.

Geological Survey of South Australia SAREIC Technical Day conference 2015

Submarine canyons have been recognised as areas of significant ecological and conservation value. In Australia, 713 canyons were mapped and classified in terms of their geomorphic properties. Many of them are identified as Key Ecological Features (KEFs) and protected by Commonwealth Marine Reserves (CMRs) using expert opinion based on limit physical and ecological information. The effectiveness of these KEFs and CMRs to include ecologically significant submarine canyons as prioritised conservation areas needs to be objectively examined. This study used two local-based spatial statistical techniques, Local Moran's I (LMI) and the Gi* statistic, to identify hotspots of Australian canyons (or unique canyons) for conservation priority. The hotspot analysis identified 29 unique canyons according to their physical attributes that have ecological relevance. Most of these unique physical canyons are distributed on the southern margins. Twenty-four of the 29 canyons are enclosed by the existing KEFs and protected by CMRs to varied extents. In addition, the hotspot analysis identified 79 unique canyons according to their chlorophyll a concentrations, all of which are located in the South-east marine planning region. The findings can be used to update or revise the profile descriptions for some existing KEFs. In future, if the boundaries of these KEFs are deemed necessary to be reviewed, the new information and knowledge could also be used to enhance the conservation priorities of these KEFs.

This dynamic map service will be used to provide reference layers for the Department of Industry for use in the Multi Criteria Site Analysis (MCSA) for the RadWaste Project. This MCSA will be used to determine an appropriate location for establishing a radioactive waste storage facility.