<div>The Abbot Point to Hydrographers Passage bathymetry survey was acquired for the Australian Hydrographic Office (AHO) onboard the RV Escape during the period 6 Oct 2020 – 16 Mar 2021. This was a contracted survey conducted for the Australian Hydrographic Office by iXblue Pty Ltd as part of the Hydroscheme Industry Partnership Program. The survey area encompases a section of Two-Way Route from Abbot Point through Hydrographers Passage QLD. Bathymetry data was acquired using a Kongsberg EM 2040, and processed using QPS QINSy. The dataset was then exported as a 30m resolution, 32 bit floating point GeoTIFF grid of the survey area.</div><div>This dataset is not to be used for navigational purposes.</div>

<div>The A1 poster incorporates 4 images of Australia taken from space by Earth observing satellites. The accompanying text briefly introduces sensors and the bands within the electromagnetic spectrum. The images include examples of both true and false colour and the diverse range of applications of satellite images such as tracking visible changes to the Earth’s surface like crop growth, bushfires, coastal changes and floods. Scientists, land and emergency managers use satellite images to analyse vegetation, surface water or human activities as well as evaluate natural&nbsp;hazards.</div>

The Historical Bushfire Boundaries service represents the aggregation of jurisdictional supplied burnt areas polygons stemming from the early 1900's through to 2022 (excluding the Northern Territory). The burnt area data represents curated jurisdictional owned polygons of both bushfires and prescribed (planned) burns. To ensure the dataset adhered to the nationally approved and agreed data dictionary for fire history Geoscience Australia had to modify some of the attributes presented. The information provided within this service is reflective only of data supplied by participating authoritative agencies and may or may not represent all fire history within a state.

This Record presents six previously unpublished U–Pb SHRIMP zircon geochronological results from the Aileron Province in the Northern Territory. The data was collected to investigate the timing of localised and poorly documented granulite facies high-T, low-P metamorphism across isolated outcrops in the central and western Aileron Province. The study was also designed to test the maximum deposition ages of the metasedimentary rocks across this large area, and whether the data are consistent with the samples being high-grade equivalents of the Lander Rock Formation. <b>Bibliographic Reference:</b> Kositcin N, and Scrimgeour IR, 2020. Summary of results: Joint NTGS–GA geochronology project: central and western Aileron Province. <i>Northern Territory Geological Survey</i>, <b>Record 2020-011</b>.

This report provides a preliminary assessment of the utility of a satellite remote sensing approach for the identification and characterisation of coastal habitats that are critical for threatened and migratory species in northern Australia. This work is part of the Habitats research theme in the A12 Northern Seascapes Scoping Project. The Australian Landsat archive in the Digital Earth Australia (DEA) analysis platform for satellite imagery was utilised to demonstrate its potential for mapping intertidal areas and mangrove extent, and changes over time in the extent of coastal landforms and habitats. Seven estuaries were examined, Darwin Harbour and the Keep, Daly, Roper, Macarthur, Flinders and Gilbert River estuaries. The estuaries were selected by the A12 Project team because they are known to provide important areas for the species of interest. Features of importance to shorebird populations were a focus. The focus of this scoping work was to utilise the DEA Landsat archive to build understanding of the effects of tidal dynamics on intertidal habitats across this region of large and complex tides, examine approaches to mapping the extent of key coastal habitats, and test the potential of the archive to detect coastal habitat change, in particular mangrove. In northern Australia, cloud interference can make it difficult to obtain clear satellite imagery. To avoid this issue, the geometric median of surface reflectance values was used to produce crisp, cloud-free composite images that depict the maximum observed tidal extent in the seven estuaries. Tide-tagging of satellite imagery was also successfully employed to allow any tide induced change to be removed from change-detection analyses and clearly depict the intertidal extent. Application of the Intertidal Extent Model in the DEA enabled the extent and morphology of estuarine intertidal environments to be mapped. The DEA also enabled habitat change change detection using the fully processed, high density, three decade long Landsat time series. The results clearly depict the dynamic nature of some areas, including large-scale rapid island growth and mangrove expansion (e.g. Keep River and Gilbert River estuaries), gradual long-term expansion of mangrove (Flinders River and McArthur River estuaries), and estuaries with areas of rapid recent die back of mangrove (Roper River and Flinders estuaries). This information is important for the management of key species as well decisions around coastal developments. With Landsat and new satellite data streams (e.g. Sentinal 2) continually being added to the DEA, this time-series analysis approach could be developed into an effective habitat extent and condition monitoring tool for northern Australia. The image products and analysis tools employed in this study demonstrate the potential utility of DEA for mapping the extent and dynamics of key coastal and estuarine habitats utilised by threatened and migratory species. To better inform the management of these species, a key next step in this approach is to utilise ground-validation data to enable these habitats to be robustly classified and quantified using the Landsat archive. This analysis should provide important baseline information and enable the extent and condition of key habitats to be monitored. <b>Preferred Citation:</b> <i>Phillips, C., Lymburner, L. & Brooke, B. (2018). Characterising northern estuaries using Digital Earth Australia.</i> Report to the National Environmental Science Programme, Marine Biodiversity Hub. <i>Geoscience Australia.</i>

Abstract: Spatial predictions of seabed sediments based on samples in the Australian Marine Samples (MARS) database provide environmental baseline information used in the management of Australia’s marine jurisdiction, offshore resource development, and marine protected areas. The MARS database holds 14204 samples, distributed unevenly across the Australian Exclusive Economic Zone (AEEZ). As such, interpolations of seabed samples are often required for understanding target regions between collection sites. Data quality in the MARS database also varies, with data quality control resulting in the exclusion of over 7,000 samples, most of which were dredged samples. Dredged samples are thought to lower the accuracy of the spatial predictions produced from the database. In this study we examined whether these excluded dredged samples should for spatial predictions by assessing whether the dredged samples decreased or increased the accuracy of the resulting spatial predictions of seabed mud content, and whether the dredging method used altered the accuracy of the resulting prediction. We confined our analyses to two contrasting areas in the AEEZ: the Southwest Region (407 total samples; 150 dredged) and Petrel Region (534 total samples; 297 dredged). We compared the accuracy of interpolated surfaces of mud content generated from QC’d samples with surfaces generated with samples from different dredge types (benthic, pipe, chain bag and unspecified). In the Southwest region samples included 73 benthic, 19 pipe, 41 chain bag, and 17 unspecified dredged samples. In the Petrel region samples included 46 pipe and 251 unspecified dredged samples. Spatial predictions of seabed mud content were made using Inverse Distance Weighting (IDW) and Ordinary Kriging (OK). Predictive errors were assessed based on leave-one-out cross-validation in terms of relative mean absolute error (RMAE). The effects of dredged samples on the predictive error were analysed using paired Mann-Whitney tests. For sediment samples in the Southwest region, including benthic dredge samples in the prediction reduced the accuracy of IDW by 1.79% in terms of RMAE. Including chain bag dredge samples increased the accuracy of IDW with a small difference in RMAE of 0.47%. The difference in accuracy of IDW was insignificant for the unspecified type samples, all dredged sample types and pipe dredged samples. Including samples with all-dredged type and unspecified type dredge samples improved the accuracy of the OK predictions over the QCed samples in the Southwest region with a small effect on RMAE of 0.68% for all-dredged samples and 0.65% for unspecified type dredged samples. The difference in accuracy of OK was insignificant for benthic dredged, pipe dredged and chain bag dredged samples in the Southwest region. No significant effects on the accuracy of IDW in the Petrel region were found for all the tested dredged sample types (unspecified type, pipe dredged samples, and all-dredged samples). The difference in accuracy of OK in the Petrel Region for samples with all dredged and with unspecified dredged samples was insignificant. Including pipe dredged samples increased the accuracy of OK in the Petrel with a negligible effect on RMAE of 0.02%. In summary, the inclusion of dredged samples produced minimal effects on the accuracy of spatial predictive models. Effects were not consistent across region or dredge type, but findings showed dredged samples had surprisingly little effect on the accuracy of the predictions Including the dredged samples would require reprocessing the spatial predictions for the AEEZ based on the MARS database, so as the findings are only based mud sediment data from two regions caution should be taken to generalise these findings to other sediment types and to the entire Australian marine margin. Further testing is required to verify these findings for other regions and sediment types and identify whether future spatial predictions can include some of this extra data without a loss in accuracy. This paper was submitted/presented at the 22nd International Congress on Modelling and Simulation (MODSIM2017) conference, 3-8 December 2017

Exploring for the Future (EFTF) is an ongoing multiyear (2016–2024) initiative of the Australian Government, conducted by Geoscience Australia. This program aims to improve Australia’s desirability for industry investment in resource exploration of frontier regions across Australia. This paper will focus on the science impacts delivered in central northern Australia, by the acquisition and interpretation of seismic surveys, petroleum geochemistry and the drilling of the NDI Carrara 1. This work has been undertaken in collaboration with the Northern Territory Geological Survey, the Queensland Geological Survey, AuScope and the MinEx CRC. The new data acquired across central northern Australia as part of the Exploring for the Future program are foundational datasets and includes seismic surveys, geochronology and geochemistry. These data link the highly prospective resource rich areas of the McArthur Basin and Mt Isa Province via a continuous seismic traverse across central northern Australia. The Exploring for the Future program aims to further de-risk exploration within greenfield regions and position northern Australia for future exploration investment. This presentation was given at the 2023 Australasian Exploration Geoscience Conference (AEGC) 13-18 March, Brisbane (https://2023.aegc.com.au/)

The High Quality Geophysical Analysis (HiQGA) package is a fully-featured, Julia-language based open source framework for geophysical forward modelling, Bayesian inference, and deterministic imaging. A primary focus of the code is production inversion of airborne electromagnetic (AEM) data from a variety of acquisition systems. Adding custom AEM systems is simple using Julia’s multiple dispatch feature. For probabilistic spatial inference from geophysical data, only a misfit function needs to be supplied to the inference engine. For deterministic inversion, a linearisation of the forward operator (i.e., Jacobian) is also required. HiQGA is natively parallel, and inversions from a full day of production AEM acquisition can be inverted on thousands of CPUs within a few hours. This allows for quick assessment of the quality of the acquisition, and provides geological interpreters preliminary subsurface images of EM conductivity together with associated uncertainties. HiQGA inference is generic by design – allowing for the analysis of diverse geophysical data. Surface magnetic resonance (SMR) geophysics for subsurface water-content estimation is available as a HiQGA plugin through the SMRPInversion (SMR probabilistic inversion) wrapper. The results from AEM and/or SMR inversions are used to create images of the subsurface, which lead to the creation of geological models for a range of applications. These applications range from natural resource exploration to its management and conservation.

The ‘Australia’s Future Energy Resources’ (AFER) project is a four-year multidisciplinary investigation of the potential energy commodity resources in selected onshore sedimentary basins. The resource assessment component of the project incorporates a series of stacked sedimentary basins in the greater Pedirka-western Eromanga region in eastern central Australia. Using newly reprocessed seismic data and applying spatially enabled, exploration play-based mapping tools, a suite of energy commodity resources have been assessed for their relative prospectivity. One important aspects of this study has been the expansion of the hydrocarbon resource assessment work flow to include the evaluation of geological storage of carbon dioxide (GSC) opportunities. This form of resource assessment is likely to be applied as a template for future exploration and resource development, since the storage of greenhouse gases has become paramount in achieving the net-zero emissions target. It is anticipated that the AFER project will be able to highlight future exploration opportunities that match the requirement to place the Australian economy firmly on the path of decarbonisation.

Internationally, the number of carbon capture and storage (CCS) projects has been increasing with more than 61 new CCS facilities added to operations around the globe in 2022, including six projects in Australia (GCCSI, 2022). The extraction of reservoir fluid will be an essential component of the CCS workflow for some of projects in order to manage reservoir pressure variations and optimise the subsurface storage space. While we refer to reservoir fluid as brine throughout this paper for simplicity, reservoir fluids can range from brackish to more saline (briny) water. Brine management requires early planning, as it has implications for the project design and cost, and can even unlock new geological storage space in optimal locations. Beneficial use and disposal options for brine produced as a result of carbon dioxide (CO2) storage has been considered at a regional or national scale around the world, but not yet in Australia. For example, it may be possible to harvest energy, water, and mineral resources from extracted brine. Here, we consider how experiences in brine management across other Australian industries can be transferred to domestic CCS projects.