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.

Project In 2013, Geoscience Australia commissioned AAM to undertake a LiDAR survey with accompanying field survey and ortho imagery capture over the Macintyre river region comprising approx 7,500 square kilometres. Ref Deed CMC G3298 Contract CMC G4417. Collection of both LiDAR and simultaneous and near simultaneous imagery utilising the Optech ALTM Pegasus HA500 sensor and the Vision Map A3 digital camera occurred from 06 November 2013 to 17th December 2013 with a total of 20 LiDAR flights plus a very small infill (LiDAR only) flight on 17th March 2014. The LiDAR was controlled from existing CORS GPS stations and 3 newly setup reference GPS station. 158 test point sites that overlapped the LiDAR were surveyed by AAM using Kinematic Smartnet GPS. The specification for this survey was provided in the aforementioned contract document Data The LiDAR, Ortho and field surveys conform in accuracy, format and nomenclature conform to the above specification. The ortho imagery comprises 0.20m GSD RGB Geotiff imagery in Geotiff and ECW formats. The area spans MGA zones 55 and 56 products have been generated with an overlap as per the specification and nomenclature advice from the client.

This dataset details the Declared Indigenous Protected Areas (IPA) across Australia through the implementation of the Indigenous Protected Areas Programme. These boundaries are not legally binding. An Indigenous Protected Area (IPA) is an area of Indigenous-owned land or sea where traditional Indigenous owners have entered into an agreement with the Australian Government to promote biodiversity and cultural resource conservation. The Indigenous Protected Areas element of the Caring for our Country initiative supports Indigenous communities to manage their land as IPAs, contributing to the National Reserve System. Further information can be found at the website below. http://www.environment.gov.au/indigenous/ipa/index.html Declared IPAs in order of gazettal date: Nantawarrina Preminghana Risdon Cove putalina Deen Maar Yalata Warul Kawa Watarru Walalkara Mount Chappell Island Badger Island Dhimurru Guanaba Wattleridge Mount Willoughby Paruku Ngaanyatjarra Tyrendarra Toogimbie Anindilyakwa Laynhapuy - Stage 1 Ninghan North Tanami Warlu Jilajaa Jumu Kaanju Ngaachi Great Dog Island Babel Island lungatalanana Angas Downs Pulu Islet Tarriwa Kurrukun Warddeken Djelk Jamba Dhandan Duringala Kurtonitj Framlingham Forest Kalka - Pipalyatjara Boorabee and The Willows Lake Condah Marri-Jabin (Thamurrurr - Stage 1) Brewarrina Ngemba Billabong Uunguu - Stage 1 Apara - Makiri - Punti Antara - Sandy Bore Dorodong Weilmoringle Yanyuwa (Barni - Wardimantha Awara) Minyumai Gumma Mandingalbay Yidinji Southern Tanami Angkum - Stage 1 Ngunya Jargoon Birriliburu Eastern Kuku Yalanji Bardi Jawi Girringun Wilinggin Dambimangari Balanggarra Thuwathu/Bujimulla Yappala Wardaman - Stage 1 Karajarri - Stage 1 Nijinda Durlga - Stage 1 Warraberalgahl and Porumalgal Kiwirrkurra Nyangumarta Warrarn Matuwa Kurrara-Kurrara

Eonomic Fairways Explorer video presentation for PDAC 2015. The purpose of this video demonstration is to show the Proof of Concept (PoC) of the Economic Fairways Explorer application, which enables users to perform "what if" economic modelling and scenarios using GIS data. The Economic Fairways Explorer application is based upon the CIAP framework.

This dataset reflects the boundaries of those Indigenous Land Use Agreements (ILUA's) that have entered the notification process or have been registered and placed on the Register of Indigenous Land Use Agreements (s199A, Native Title Act; Commonwealth). This is a national dataset. Aspatial attribution includes National Native Title Tribunal number, Name, Agreement Type, Proponent, Area and Registration Date. Citation: ANZLIC unique identifier: ANZCW1101000005 Title: Registered and Notified Indigenous Land Use Agreements (ILUA) - agreement boundaries and core attributes about agreement Custodian: National Native Title Tribunal Jurisdiction: Australia

Terrain illumination correction is an important step in the normalisation of remotely sensed data for the inversion of land surface parameters, and for applications that aim to detect land surface change through time series analysis. To accurately normalise for the terrain effect, an appropriate resolution of the Digital Elevation Model (DEM) data with sufficient quality is critical for effective correction of remotely sensed data over mountainous areas. Conversely, using terrain illumination correction and scale-based analysis, such as filter bank analysis, the quality of DEM data can be evaluated. In this study, TanDEM-X Intermediate DEM (IDEM) data at 12 m and 30 m resolutions, and the 1-second SRTM data (~ 30 m resolution) were used to evaluate their effectiveness for terrain illumination correction of Landsat satellite data. The island of Tasmania in Australia has a fine scale of terrain detail as well as high relief. The high latitude and strong variability in the terrain illumination throughout the year make it an ideal study site for applying the methods available for this evaluation. Results from the terrain illumination correction and filter bank analysis show that IDEM 12 m and 30 m resolution datasets can resolve finer details of terrain shading than the SRTM based DEMs and deliver better results in the areas with detail-rich terrain. However, since the data available for this study is an intermediate product, spikes and other noise artefacts were prevalent, especially over areas covered by water. Operational use of the IDEM would require the removal of such noise artefacts. The filter bank analysis also found that both Landsat panchromatic data and IDEM 12 m data are oversampled and the signal-to-noise parameters for both DEM and Landsat data are yet to be fully established. Further evaluation of the relative merits of the TanDEM-X based DEM data and the SRTM based DEM data for terrain illumination correction would be possible when the WorldDEM product based on TanDEM-X data becomes routinely available.

The Sun's gravitational field deflects the apparent positions of close objects in accordance with the formulae of general relativity. Optical astrometry is used to test the prediction, but only with the stars close to the Sun and only during total Solar eclipses. Nowadays, more advanced technique, geodetic Very Long Baseline Interferometry (VLBI) is applied for testing of general relativity with precision about 0.01 percent. The geodetic VLBI is capable of measuring the gravitational delay based on the differential Shapiro's delay. By reason, the gravitational delay is equivalent to the deflection of the light from distant radio sources and could be measured at any time and across the whole sky. In accordance with the theory, all celestial objects display annual circular motion with the magnitude proportional to their ecliptic latitude due to the Earth orbital motion. In particular, the objects near the ecliptic pole draw an annual circle with magnitude of 4 millisecond of arc. In contrast to a single optical telescope, a single ground-based VLBI interferometer is made of two radio telescopes separated by several thousand kilometers. This provides an additional advantage to detect a secondary light deflection angle caused by the parallactic shift of the Sun as observed from both ends of the interferometer. This effect is proportional to the baseline length and is about 0".01 for grazing light at baseline of 8000 km. It could be used in future space interplanetary VLBI missions with baseline length of one billion kilometers (comparable to the Jupiter orbit size) for direct detection of invisible mass from extragalactic objects.

A video created for the Australia Minerals booth at the China Mining 2015conference. The video has key information translated into Mandarin.

Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia's marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy, can be inferred based on underwater video footage at limited locations. It can also be predicted to two classes. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e. hard90 and hard70) for seabed video footage by. We developed optimal predictive models to predict the spatial distribution of seabed hardness using random forest (RF) based on point data of hardness classes and spatially continuous multibeam backscatter data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), the combined, Boruta, and RRF were tested. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were also examined. Finally, the most accurate models were used to predict the spatial distribution of the hardness classes and the predictions were visually examined and compared with the predictions based on two-class hardness classification. This study confirms that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness can be predicted into a spatially continuous layer with a high degree of accuracy; 3) the typical approach used to pre-select predictors by excluding highly correlated predictors needs to be re-examined when using machine learning methods, at least, for RF, in the environmental sciences; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving the predictive models; 5) FS is essential for identifying an optimal RF predictive model and the RF methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data, can be applied to `small p and large n problems in environmental sciences, and is recommended for future studies. In addition, automated computational programs for AVI need be developed to improve its computational efficiency and caution should be taken when applying filter FS method in selecting predictive models in future studies.