This compilation data release is a selection of remotely sensed imagery used in the Exploring for the Future (EFTF) East Kimberley Groundwater Project. Datasets include: • Mosaic 5 m digital elevation model (DEM) with shaded relief • Normalised Difference Vegetation Index (NDVI) percentiles • Tasselled Cap exceedance summaries • Normalised Difference Moisture Index (NDMI) • Normalised Difference Wetness Index (NDWI) The 5m spatial resolution digital elevation model with associated shaded relief image were derived from the East Kimberley 2017 LiDAR survey (Geoscience Australia, 2019b). The Normalised Difference Vegetation Index (NDVI) percentiles include 20th, 50th, and 80th for dry seasons (April to October) 1987 to 2018 and were derived from the Landsat 5,7 and 8 data stored in Digital Earth Australia (see Geoscience Australia, 2019a). Tasselled Cap Exceedance Summary include brightness, greenness and wetness as a composite image and were also derived from the Landsat data. These surface reflectance products can be used to highlight vegetation characteristics such as wetness and greenness, and land cover. The Normalised Difference Moisture Index (NDMI) and Normalised Difference Water Index (NDWI) were derived from the Sentinel-2 satellite imagery. These datasets have been classified and visually enhanced to detect vegetation moisture stress or water-logging and show distribution of moisture. For example, positive NDWI values indicate waterlogged areas while waterbodies typically correspond with values greater than 0.2. Waterlogged areas also correspond to NDMI values of 0.2 to 0.4. Geoscience Australia, 2019a. Earth Observation Archive. Geoscience Australia, Canberra. http://dx.doi.org/10.4225/25/57D9DCA3910CD Geoscience Australia, 2019b. Kimberley East - LiDAR data. Geoscience Australia, Canberra. C7FDA017-80B2-4F98-8147-4D3E4DF595A2 https://pid.geoscience.gov.au/dataset/ga/129985

To set out how Geoscience Australia will meet its vision for the Exploring for the Future program, we have summarised the ways our scientific activities, outputs and intended outcomes and impacts are linked, using the Impact Pathway diagram.

<p>This package contains airborne electromagnetic (AEM) data from the "SkyTEM helicopter EM Howard East region" survey which was flown over Howard East region, Northern Territory during July - August 2017. The area is comprised of 2073.6 line kilometres in total. <p>The aim of the survey is to provide at a reconnaissance scale: <p>a) trends in regolith thickness and variability <p>b) variations in bedrock conductivity <p>c) conductivity of key bedrock (lithology related) conductive units under cover <p>d) the groundwater resource potential of the region <p>This report lists the SkyTEM system information and specifications relevant for this survey, and describes the processing carried out on the data. <p>Geoscience Australia commissioned the survey as part of the Exploring for the Future (EFTF) program. The EFTF program is led by Geoscience Australia (GA), in collaboration with the Geological Surveys of the Northern Territory, Queensland, South Australia and Western Australia, and is investigating the potential mineral, energy and groundwater resources in northern Australia and South Australia. The EFTF is a four-year $100.5 million investment by the Australian Government in driving the next generation of resource discoveries in northern Australia, boosting economic development across this region (https://www.ga.gov.au/eftf).

Many scientific talks by Geoscience Australia staff are published on YouTube. These documents provide summaries (‘crib sheets’) of the presentations along with easy access links to each part of the video. They are intended to help teachers of Year 11/12 classes learning about natural hazards

Millions of data points have been acquired or compiled through both phases of the Exploring for the Future (EFTF) program at Geoscience Australia (GA). This data that graces the EFTF Portal and appears in many publications has another home within specialist databases designed and built to house the specific data that GA collects. One such database is HYDROCHEM, which was implemented as part of the Enhanced Data Delivery (EDD) and National Groundwater Systems (NGS) projects. HYDROCHEM hosts 190,097 rows of groundwater, surface water and rainfall water chemistry analyses. This data was either previously hosted in the GNDWATER database, or compiled from legacy data stores. The redevelopment of GNDWATER to HYDROCHEM saw the de-duplication and updating of sample and site-specific metadata into other GA databases, such as SAMPLES, BOREHOLES and FIELDSITES. The redevelopment also added additional constraints to the database, including minimum metadata requirements, constrained look-up tables for units of measure, laboratory, method, filter sizes, standards and uncertainty types. Other features include minimum and maximum values for particular analytes and delivery of the data in standardised GA-preferred units of measure.

The Exploring for the Future program Showcase 2022 was held on 8-10 August 2022. Day 2 (9th August) included talks on two themes moderated by Marina Costelloe. Data and toolbox theme: - Data acquisition progress - Dr Laura Gow - Quantitative tool development: HiQGA.jl and HiPerSeis - Dr Anandaroop Ray - Data delivery advances: Underpinned by careful data curation - Mark Webster Geology theme: - Mapping Australia's geology: From the surface down to great depths - Dr Marie-Aude Bonnardot - Towards a national understanding of Groundwater - Dr Hashim Carey - Uncovering buried frontiers: Tennant Creek to Mount Isa - Anthony Schofield and Dr Chris Carson - Lithospheric characterisation: Mapping the depths of the Australian tectonic plate - Dr Marcus Haynes You can access the recording of the talks from YouTube here: Showcase Day 2 – Part 1 https://youtu.be/US6C-xzMsnI Showcase Day 2 – Part 2 https://youtu.be/ILRLXbQNnic

The AEM method measures regolith and rocks' bulk subsurface electrical conductivity, typically to a depth of several hundred meters. AEM survey data is widely used in Australia for mineral exploration (i.e. mapping undercover and detection of mineralisation), groundwater assessment (i.e. hydro-stratigraphy and water quality) and natural resource management (i.e. salinity assessment). Geoscience Australia (GA) has flown Large regional AEM surveys over Northern Australia, including Queensland, Northern Territory and Western Australia. The surveys were flown nominally at 20-kilometre line spacing, using the airborne electromagnetic systems that have signed technical deeds of staging with GA to ensure they can be modelled quantitatively. Geoscience Australia commissioned the survey as part of the Exploring for the Future (EFTF) program. The EFTF program is led by Geoscience Australia (GA), in collaboration with the Geological Surveys of the Northern Territory, Queensland, South Australia and Western Australia, and is investigating the potential mineral, energy and groundwater resources in northern Australia and South Australia. We have used a machine learning modelling approach that establishes predictive relationships between the inverted flight-line modelled conductivity with a suite of national environmental and geological covariates. These covariates include terrain derivatives, gamma-ray radiometric, geological maps, climate derived surfaces and satellite imagery. Conductivity-depth values were derived from a single model using GA's deterministic 1D smooth-30-layer layered-earth-inversion algorithm. (Brodie and Richardson 2015). Three conductivity depth interval predictions are generated to interpolate the actual modelled conductivity data, which is 20km apart. These depth slices include a 0-50cm, 9-11m and 22-27m depth prediction. Each depth interval was modelled and individually optimised using the gradient boosted tree algorithm. The training cross-validation step used label clusters or groups to minimise over-fitting. Many hundreds of conductivity models are generated (i.e. ensemble modelling). Here we use the median of the models as the conductivity prediction and the upper and lower percentiles (95th and 5th) to measure model uncertainty. Grids show conductivity (S/m) in log 10 units. Reported out-of-sample r-squares for each interval in order of increasing depth are 0.74, 0.64, and 0.67. A decline in model performance with increasing depth was expected due to the decrease in suitable covariates at greater depths. Modelled conductivities seem to be consistent with the geological, regolith, geomorphological, and climate processes in the study area. The conductivity grids are at the resolution of the covariates, which have a nominal pixel size of 85 meters. Datasets in this data package include; 1. 0-50cm depth interval 0_50cm_median.tif; 0_50_upper.tif; 0_50_lower.tif 2. 9-11m depth interval 9_11m_median.tif; 9_11m_upper.tif; 9_11m_lower.tif 3. 22-27m depth interval 22_27_median.tif; 22_27_upper.tif; 22_27_lower.tif 4. Covariate shift; Cov_shift.tif (higher values = great shift in covariates) Reference: Ross C Brodie & Murray Richardson (2015) Open Source Software for 1D Airborne Electromagnetic Inversion, ASEG Extended Abstracts, 2015:1, 1-3, DOI: 10.1071/ ASEG2015ab197

Background It is important to know where water is normally present in a landscape, where water is rarely observed, and where inundation has occasionally occurred. These observations tell us where flooding has occurred in the past, and allows us to understand wetlands, water connectivity and surface-groundwater relationships. This can lead to more effective emergency management and risk assessment. This is the principal Digital Earth Australia (DEA) Water product (previously known as Water Observations from Space (WOfS)), providing the individual water observations per satellite image that are subsequently used in the following DEA Watersuite and related water bodies products: DEA Waterbodies (Landsat), DEA Water Observations Statistics (Landsat), DEA Water Observations Filtered Statistics (Landsat). This product shows where surface water was observed by the Landsat satellites on any particular day since mid 1986. These daily data layers are termed Water Observations (WOs). What this product offers DEA Water Observations provides surface water observations derived from Landsat satellite imagery for all of Australia from 1986 to present. The Water Observationsshow the extent of water in a corresponding Landsat scene, along with the degree to which the scene was obscured by clouds, shadows or where sensor problems cause parts of a scene to not be observable.

This flythrough highlights shallow and mesophotic seabed environments of Elizabeth and Middleton Reefs, located within the Lord Howe Marine Park. These reefs are unique because they are the southern-most platform reefs in the world and host a diverse range of tropical, sub-tropical and temperate marine species. High-resolution multibeam bathymetry data and seafloor imagery used in this flythrough was acquired by the Marine Biodiversity Hub, during the period 31 January to 6 February 2020 on board the Australian Maritime College vessel, TV Bluefin. Participating agencies included Geoscience Australia, the Institute for Marine and Antarctic Studies (University of Tasmania), the Australian Centre for Field Robotics (University of Sydney) through their involvement with the Integrated Marine Observing System (IMOS), NSW Department of Primary Industries and Parks Australia. The specific aim of the survey was to fill knowledge gaps on the distribution, extent and structure of seabed habitats and associated sessile and mobile fauna in the lagoon and mesophotic shelves of Elizabeth (Recreational Use Zone) and Middleton (National Park Zone) Reefs, using a suite of national standard survey tools and best practice sampling procedures. Data acquisition for the project included seabed mapping using multibeam sonar (Kongsberg EM 2040C HD, 300 kHz), seabed imagery acquisition by Autonomous Underwater Vehicles (AUV Sirius and AUV Nimbus), sediment samples, and imagery of demersal fish communities by stereo-baited remote underwater videos (stereo-BRUVs). This work was undertaken by the Marine Biodiversity Hub, a collaborative partnership supported through funding from the Australian Government’s National Environmental Science Program (NESP), and Parks Australia. AUV data was sourced from Australia’s Integrated Marine Observing System (IMOS) – IMOS is enabled by the National Collaborative Research Infrastructure Strategy (NCRIS). It is operated by a consortium of institutions as an unincorporated joint venture, with the University of Tasmania as Lead Agent. This multimedia product is published with the permission of the CEO, Geoscience Australia.

A series of short video clips illustrating how to use the Community and Education Data Portal (https://portal.ga.gov.au/persona/education). The Community and Education data portal is one of many data delivery portals available from Geoscience Australia, giving users access to a wealth of useful data and tools. It has been designed specifically for non-technical users, so that general community members, including educators, can access themed surface and subsurface datasets or images with enhanced capabilities including 3D visualisation, and online analysis tools. The User Guide Video complements the help menu in the portal. The User guide is broken into a series of topics 1. Introduction 2. Toolbar 3. Map layers 4. Multiple Layers 5. Background Layers and Sharing 6. 3D Layers 7. Tools 8. Custom Layers The step by step guides were produced by James Cropper.