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  • <p>Flythrough movie of Gifford Marine Park, which is located 700 km east of Brisbane, Australia. The park is situated about halfway along the Lord Howe Rise seamount chain on the western flank of the Lord Howe Rise. Seamounts along this chain formed from Miocene volcanism via a migrating magma source (“hotspot”) after the opening of the Tasman Sea. Two large, flat-topped volcanic seamounts dominate the park. Their gently sloping summits have accumulated veneers of sediment, which in places have formed fields of bedforms. Steep cliffs, debris and large mass movement scars encircle each seamount, and contrast with the lower gradient abyssal plains from which they rise. Spanning over 3 km of ocean depths, the seamounts are likely to serve multiple and important roles as breeding locations, resting areas, navigational landmarks or supplementary feeding grounds for some cetaceans (e.g. humpback whales, sperm whales). They may also act as important aggregation points for other highly migratory pelagic species. The bathymetry shown here was collected on two surveys - the first in 2007 by Geoscience Australia and the second in 2017 by Geoscience Australia in collaboration with the Japan Agency for Marine-Earth Science and Technology. The Gifford Marine Park has also been the focus of a study undertaken by the Marine Biodiversity Hub as part of the National Environmental Science Program. <p>This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

  • <p>Bathymetry flythrough of Perth Canyon using data acquired by Schmidt Ocean Institute in 2015 on RV Falkor (University of Western Australia et al.). The flythrough highlights geomorphic features mapped by Geoscience Australia, including landslides, escarpments and bedform fields and biodiversity associated with the canyon (benthic and pelagic). Produced as a science communication product for the Marine Biodiversity Hub (National Environmental Science Program). <p>This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

  • <p>Flythrough movie of Bremer Commonwealth Marine Reserve, southwest Western Australia showing bathymetry of Bremer Canyon, Hood Canyon, Henry Canyon and Knob canyon. <p>This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

  • <p>Lu-Hf isotopic analysis of zircon is becoming a common way to characterise the source signature of granite. The data are collected by MC-LA-ICP-MS (multi-collector laser ablation inductively coupled plasma mass spectrometry) as a series of spot analyses on a number of zircons from a single sample. These data are often plotted as spot analyses, and variable significance is attributed to extreme values, and amount of scatter. <p>Lu-Hf data is used to understand the origin of granites, and often a distribution of εHf values is interpreted to derive from heterogeneity in the source or from mixing processes. As with any physical measurement, however, before the data are used to describe geologic processes, care ought to be taken to account for sources of analytical variability. The null hypothesis of any dataset is that there is no difference between measurements that cannot be explained by analytical uncertainty. This null hypothesis must then be disproven using common statistical methods. <p>There are many sources of uncertainty in any analytical method. First is the uncertainty associated with the counting statistics of each analysis. This uncertainty is usually recorded as the SE (standard error) uncertainty attributed to each spot. This uncertainty commonly underestimates the total uncertainty of the population, as it only contains information about the consistency of the measurement within a single analysis. The other source of uncertainty that needs to be characterised is similarity over multiple analyses. This is very difficult to assess in an unknown material, but can be assessed by measuring well-understood reference zircons. <p>Reference materials are characterised by homogeneity in the isotope of interest, and multiple analyses of this material should produce a single statistical population. Where these populations display significant excess scatter, manifested as a MSWD value that far exceeds 1, this means that counting statistics are not the sole source of uncertainty. This can be addressed by expanding the uncertainty on the analyses until the standard zircons form a coherent statistical population. This expansion should then be applied to the unknown zircons to accommodate this ‘spot-to-spot-uncertainty’ or ‘repeatability’ factor. This approach is routinely applied to SHRIMP U-Pb data, and here is similarly applied to Lu-Hf data from granites of the northeast Lachlan Orogen. <p>By applying these uncertainty factors appropriately, it is then possible to assess the homogeneity of unknown materials by calculating weighted means and MSWD factors. The MSWD is a measure of scatter away from a single population (McIntyre et al., 1966; Wendt and Carl, 1991). Where the MSWD is 1, the scatter in data points can be explained solely by analytical means. The higher the MSWD, the less likely it is that the data can be described as a single population. Data which disperses over several εHf units can still be attributed to a single population if the uncertainty envelopes of analyses largely overlap each other. These concepts are illustrated using the data presented in Figure 1. Four out of five of the εHf datasets on zircons from granites form statistically coherent populations (MSWD = 0.69 to 2.4). <p>A high MSWD does not necessarily imply that variation is due to processes occurring during granite formation. Although zircon is a robust mineral, isotopic disturbances are still possible. In the U-Pb system, there is often evidence of post-crystallisation ‘Pb-loss’ which leads to erroneously young apparent U-Pb ages. The Lu-Hf system in zircon is generally thought to be more robust than the U-Pb system, but that does not mean that it is impervious to such effects. In the data set presented in Figure 1, the sample with the most scatter in Lu-Hf (Glenariff Granite, εHf = -0.2 ± 1.5, MSWD = 7.20) is also the sample which had the most rejections in the SHRIMP U-Pb data due to Pb-loss. The subsequent Hf analyses targeted only those grains which fell within the magmatic population (i.e., no observed Pb-loss), but the larger volume excavated by laser Hf analysis means that it is likely that disturbed regions of these grains were incorporated into the measurement. This gives an explanation for the scatter that has nothing to do with geological source characteristics. <p>This line of logic can similarly be applied to all types of multi-spot analyses, including O-isotope analyses. While most of the εHf datasets presented here form coherent populations, the O-isotope data are significantly more scattered (MSWD = 2.8 to 9.4). The analyses on the unknowns scatter much more than on the co-analysed TEMORA2 reference zircon. This implies a source of scatter additional to those described above. In addition to the above described sources of uncertainty, O-isotope analysis by SIMS is also extremely sensitive to topography on the surface of the epoxy into which zircons are mounted (Ickert et al., 2008). O isotopes may also be susceptible to post-formation disturbance and so care should also be taken when interpreting O data, before assigning geological meaning. <p>While it is possible for Lu-Hf and O analyses of zircons in granites to reflect heterogeneous sources and/or complex formation processes, it is important to first exclude other sources of heterogeneity such as analytical sources of uncertainty, and post-formation isotopic disturbances.

  • A compilation video of flythrough footage showing Great Barrier Reef bathymetry visualisations. Primarily for use by media.

  • Factsheet for DEA with information relevant to stakeholders from the Australian Government

  • The Location Index (Loc-I) project commenced in 2018 and aims to bring together geospatial data from across a number of government sources, making it openly available to government policy developers and decision makers via one central location. This video animation is 3:47 long in MP4 format and describes the Location Index project aims and objectives

  • The Exploring for the Future program Virtual Roadshow was held on 7 July and 14-17 July 2020. The Minerals session of the roadshow was held on 14 July 2020 and consisted of the following presentations: Introduction - Richard Blewett Preamble - Karol Kzarnota Surface & Basins or Cover - Marie-Aude Bonnardot Crust - Kathryn Waltenberg Mantle - Marcus Haynes Zinc on the edge: New insights into sediment-hosted base metals mineral system - David Huston Scale reduction targeting for Iron-Oxide-Copper-Gold in Tennant Creek and Mt Isa - Anthony Schofield and Andrew Clark Economic Fairways and Wrap-up - Karol Czarnota

  • The annual Asia Pacific Regional Geodetic Project (APRGP) GPS campaign is an activity of the Geodetic Reference Frame Working Group (WG) of the Regional Committee of United Nations Global Geospatial Information Management for Asia and the Pacific (UN-GGIM-AP). This document describes the data analysis of the APRGP GPS campaign undertaken between the 15th and 22nd of September 2019. Campaign GPS data collected at 101 sites in ten countries across the Asia Pacific region were processed using version 5.2 of the Bernese GNSS Software in a regional network together with selected IGS (International GNSS Service) sites. The GPS solution was constrained to the ITRF2014 reference frame by adopting IGS14 coordinates on selected IGS reference sites and using the final IGS earth orientation parameters and satellite ephemerides products. The average of the root mean square repeatability of the station coordinates for the campaign was 1.8 mm, 1.6 mm and 5.4 mm in north, east and up components of station position respectively.

  • Understanding disaster risk enables Government, industry and the community to make better decisions on how to prepare for disasters and improve the resilience of communities. Geoscience Australia develops and provides fundamental data and information to understand disaster risk so that we can determine how hazards impact the things that are valuable to us. Through robust and proven methodologies, technical expertise and trusted data, our national capability can support informed decisions to prepare for and respond to hazard events so that the impact of disasters can be reduced, and to inform where and how our future communities and supporting infrastructure are built.