This service provides access to hydrochemistry data (groundwater and surface water analyses) obtained from water samples collected from Australian water bores or field sites.

Exploring for the Future (EFTF) is a four-year (2016-20) geoscience data and information acquisition program that aims to better understand on a regional scale the potential mineral, energy and groundwater resources concealed under cover in northern Australia and parts of South Australia. Hydrogeochemical surveys utilise groundwater as a passive sampling medium to reveal the chemistry of the underlying geology including hidden mineralisation. These surveys also potentially provide input into regional baseline groundwater datasets that can inform environmental monitoring and decision making. Geoscience Australia, as part of the Australian Government’s EFTF program, undertook an extensive groundwater sampling survey in collaboration with the Northern Territory Geological Survey and the Geological Survey of Queensland. During the 2017, 2018 and 2019 dry season, 224 groundwater samples (including field duplicate samples) were collected from 203 pastoral and water supply bores in the Tennant Creek-Mt Isa EFTF focus area of the Northern Territory and Queensland. An additional 38 groundwater samples collected during the 2013 dry season in the Lake Woods region from 35 bores are included in this release as they originate from within the focus area. The area was targeted to evaluate its mineral potential with respect to iron oxide copper-gold, sediment-hosted lead-zinc-silver and Cu-Co, and/or lithium-boron-potash mineral systems, among others. The 2017-2019 surveys were conducted across 21 weeks of fieldwork and sampled groundwater for a comprehensive suite of hydrogeochemical parameters, including isotopes, analysed over subsequent months. The present data release includes information and atlas maps of: 1) sampling sites; 2) physicochemical parameters (EC, pH, Eh, DO and T) of groundwater measured in the field; 3) field measurements of total alkalinity (HCO3-), dissolved sulfide (S2-), and ferrous iron (Fe2+); 4) major cation and anion results; 5) trace element concentrations; 6) isotopic results of water (δ18O and δ2H), DIC (δ13C), dissolved sulfate (δ34S and δ18O), dissolved strontium (87Sr/86Sr), and dissolved lead (204Pb, 206Pb, 207Pb, and 208Pb) isotopes; 7) dissolved hydrocarbon VFAs, BTEX, and methane concentrations, as well as methane isotopes (δ13C and δ2H); and 8) atlas of hydrogeochemical maps representing the spatial distribution of these parameters. Pending analyses include: CFCs and SF6; tritium; Cu isotopes; and noble gas concentrations (Ar, Kr, Xe, Ne, and 4He) and 3He/4He ratio. This data release (current as of July 2021) is the second in a series of staged releases and interpretations from the Northern Australia Hydrogeochemical Survey. It augments and revises the first data release, which it therefore supersedes. Relevant data, information and images are available through the GA website (https://pid.geoscience.gov.au/dataset/ga/133388) and GA’s EFTF portal (https://portal.ga.gov.au/).

The Geoscience Australia (GA) Inorganic Geochemistry database (GEOCHEM) contains chemical analyses and analytical metadata from rocks and regolith materials. The majority of analysed samples are from mapping and sampling programs in Australia by GA and its predecessor organisations (BMR, AGSO), along with a considerable collection from the Australian Antarctic Territory. A small number of analyses exist from Papua New Guinea and offshore sampling programs. The data set is currently used for internal GA consumption and is served off an application within the GA portal. As an enhancement, this data would be altered in terms of its structure adding more information out of such analyses. In addition, the data would me made compliant following GGIC standards. The data would be published within internal GA as well as to external third parties, through OGC web services viz. WMS and WFS.

<b>Background:</b> The European Space Agency (ESA) has operated the medium resolution satellites - Sentinel-2 series (Sentinel-2A and Sentinel-2B) since 2015. The spectral bands and spatial resolution of Sentinel-2 are similar to those of Landsat series, but Sentinel-2 has a higher revisit frequency and spatial coverage. A combination of Sentinel-2 and Landsat data can provide good spatial and temporal coverage of the Earth's surface and provide useful information to monitor environmental resources, such as agricultural production and mining activities, over time. However, the raw remotely sensed data received by these satellites in the solar spectral range do not directly characterise the underlying reflectance of surface objects. The data are modified by the atmosphere and variation of solar and sensor positions as well as surface anisotropic conditions. To make accurate comparisons of imagery acquired at different times, seasons and geographic locations and detect the change of surface, it is necessary to remove/reduce these effects to ensure the data are consistent and can be compared over time. <b>What this product offers:</b> This product takes Sentinel-2B imagery captured over the Australian continent and corrects for inconsistencies across land and coastal fringes. The result is accurate and standardised surface reflectance data, which is instrumental in identifying and quantifying environmental change. The imagery is captured using the Multispectral Instrument (MSI) sensor aboard Sentinel-2B. This product is a single, cohesive Analysis Ready Data (ARD) package, which allows the analysis of surface reflectance data as is, without the need to apply additional corrections. It contains two sub-products that provide corrections or attribution information: - DEA Surface Reflectance NBART(Sentinel-2B MSI) - Geoscience Australia Sentinel-2B MSI NBART Collection 3 - DEA Surface Reflectance OA(Sentinel-2B MSI) - Geoscience Australia Sentinel-2B Observation Attributes Collection 3 The resolution is a 10/20/60 m grid based on the ESA Level 1C archive. <b>Applications:,</b> - The development of derivative products to monitor land, inland waterways and coastal features, such as: - urban growth - coastal habitats - mining activities - agricultural activity (e.g. pastoral, irrigated cropping, rain-fed cropping) - water extent - The development of refined information products, such as: - areal units of detected surface water - areal units of deforestation - yield predictions of agricultural parcels - Compliance surveys - Emergency management This Collection 3 (C3) product and has been created by reprocessing Collection 1 (C1) and making improvements to the processing pipeline and packaging. <b>Packaging updates include: </b> - Open Data Cube (ODC) eo3 metadata - metadata includes STAC fields to enable users to filter by fields such as tile ID or cloud cover percentage in applications such as ODC - additional STAC metadata file in JSON format - directory structure and file names that are consistent with Geoscience Australia’s Landsat C3 products. <b>Additional updates include:</b> - upgrading the spectral response function to result in a more accurate product. These new versions include minor updates, slight changes of the central wavelengths for band B02 of S2A and S2B, and band B01 of S2B, along with slight changes of the Full Width Half Maximum (FMWH) for most of the bands - correction of solar constant errors in the conversion between reflectance and radiance as well as in the atmospheric correction - an additional cloud mask layer (s2cloudless) - removal of NBAR layers - reduced spatial resolution of observation attribute layers to 20m resolution, with the contiguity layer being maintained at 10m - additional of GQA information to dataset metadata - removal of buffering from fmask layer - BRDF ancillary upgraded from MODIS BRDF C5 to MODIS BRDF C6 - Upgrading from MODTRAN 5.2 to MODTRAN 6. <b>The introduction of a maturity concept.</b> The Collection 3 product is comprised of data produced to varying degrees of maturity. The maturity of a dataset is dictated by the quality of the ancillary information, such as BRDF and atmospheric data, used to generate the product. The maturity levels are Near Real Time (NRT), Interim and Final. The maturity level is designated in the filename and in the metadata. - Near Real Time (NRT) is a rapid ARD product produced < 48 hours after image capture. - Interim ARD – If there are extended delays (>18 days) in delivery of inputs to the ARD model, interim production is utilised until the issue is resolved. - Final ARD - As the higher quality ancillary datasets become available, a “Final” version of the Sentinel 2 ARD data is produced, which replaces the NRT or interim product.

Background: This is a sub-product of DEA Surface Reflectance (Sentinel-2A MSI) - Geoscience Australia Sentinel-2A MSI Analysis Ready Data Collection 3. See the parent product for more information. Reflectance data at top of atmosphere (TOA) collected by Sentinel-2A MSI sensors can be affected by atmospheric conditions, sun position, sensor view angle, surface slope and surface aspect. Surfaces with varying terrain can introduce inconsistencies to optical satellite images through irradiance and bidirectional reflectance distribution function (BRDF) effects. For example, slopes facing the sun appear brighter compared with those facing away from the sun. Likewise, many surfaces on Earth are anisotropic in nature, so the signal picked up by a satellite sensor may differ depending on the sensor’s position. These need to be reduced or removed to ensure the data is consistent and can be compared over time. What this product offers: This product takes Sentinel-2A MSI imagery captured over the Australian continent and corrects the inconsistencies across the land and coastal fringe. It achieves this using Nadir corrected Bi-directional reflectance distribution function Adjusted Reflectance (NBAR). In addition, this product applies terrain illumination correction to correct for varying terrain. The resolution is a 10/20/60 m grid based on the the ESA level 1C archive. Applications: - The development of derivative products to monitor land, inland waterways and coastal features, such as: - urban growth - coastal habitats - mining activities - agricultural activity (e.g. pastoral, irrigated cropping, rain-fed cropping) - water extent - The development of refined information products, such as: - areal units of detected surface water - areal units of deforestation - yield predictions of agricultural parcels - Compliance surveys - Emergency management

Earth Observations over Antarctica and the Southern Ocean are critical for understanding changes in the cryosphere, ecosystems and oceans through time. Our ability to observe Antarctica systematically at a continental scale is constrained by difficulties accessing, storing and pre-processing satellite imagery prior to analysis. Some of these challenges are unique to the Antarctic environment, where factors such as cloud masking, reflectivity, prolonged periods of darkness and atmospheric differences in water vapour, aerosol and signal scattering mean that corrections applied to satellite data in other regions of the world aren’t representative of Antarctic conditions. A new collaboration between Geoscience Australia and the Australian Antarctic Division, Digital Earth Antarctica, aims to improve access to corrected continental scale satellite data through use of Open Data Cube technology. This initiative builds on work in the international community in developing Open Data Cube platforms, which have been applied in the development of Digital Earth Australia and Digital Earth Africa. The Digital Earth Antarctica platform will provide open access to analysis ready time-series data that has been corrected and validated for Antarctic conditions. It will focus primarily on data from Landsat (optical), Sentinel-1 (synthetic aperture radar) and Sentinel-2 (optical), with other sensors to be added as the capability expands. Digital Earth Antarctica is an ambitious project that will work alongside other international efforts to enhance the accessibility of quality Antarctic Earth Observations. Abstract/Poster presented at the 2023 New Zealand - Australia Antarctic Science Conference (NZAASC)

<b>BACKGROUND</b> <p> <p>The United States Geological Survey's (USGS) Landsat satellite program has been capturing images of the Australian continent for more than 30 years. This data is highly useful for land and coastal mapping studies. <p>In particular, the light reflected from the Earth’s surface (surface reflectance) is important for monitoring environmental resources – such as agricultural production and mining activities – over time. <p>We need to make accurate comparisons of imagery acquired at different times, seasons and geographic locations. However, inconsistencies can arise due to variations in atmospheric conditions, sun position, sensor view angle, surface slope and surface aspect. These need to be reduced or removed to ensure the data is consistent and can be compared over time. <p>&nbsp</p> <b>WHAT THIS PRODUCT OFFERS</b> <p> <p>GA Landsat 7 ETM+ Analysis Ready Data Collection 3 takes Landsat 7 Enhanced Thematic Mapper (ETM+) imagery captured over the Australian continent and corrects for inconsistencies across land and coastal fringes. The result is accurate and standardised surface reflectance data, which is instrumental in identifying and quantifying environmental change. <p> <p>The ETM+ instrument is a fixed ‘whisk broom’, eight-band, multispectral scanning radiometer capable of providing high-resolution imaging information of the Earth’s surface. It is an enhanced version of the Thematic Mapper (TM) sensor. <p> <p>This product is a single, cohesive Analysis Ready Data (ARD) package, which allows you to analyse surface reflectance data as is, without the need to apply additional corrections. <p> <p>It contains three sub-products that provide corrections or attribution information: <p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;1) GA Landsat 7 ETM+ NBAR Collection 3 <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;2) GA Landsat 7 ETM+ NBART Collection 3 <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;3) GA Landsat 7 ETM+ OA Collection 3 <p> <p>The resolution is a 30 m grid based on the USGS Landsat Collection 1 archive.

Background: The European Space Agency (ESA) has operated medium resolution satellites - Sentinel-2 series (Sentinel-2A and Sentinel-2B) since 2015. The spectral bands and spatial resolution of Sentinel-2 are similar to those of the Landsat series, but Sentinel-2 has a higher revisit frequency and spatial coverage. A combination of Sentinel-2 and Landsat data can provide good spatial and temporal coverage of the Earth's surface and provide useful information to monitor environmental resources over time, such as agricultural production and mining activities. However, the raw remotely sensed data received by these satellites in the solar spectral range do not directly characterise the underlying reflectance of surface objects. The data are modified by the atmosphere, variation of solar and sensor positions as well as surface anisotropic conditions. To make accurate comparisons of imagery acquired at different times, seasons and geographic locations, and detect the change of surface, it is necessary to remove/reduce these effects to ensure the data are consistent and can be compared over time. What this product offers: This product takes Sentinel-2A imagery captured over the Australian continent and corrects for inconsistencies across land and coastal fringes. The result is accurate and standardised surface reflectance data, which is instrumental in identifying and quantifying environmental change. The imagery is captured using the Multispectral Instrument (MSI) sensor aboard Sentinel-2A. This product is a single, cohesive Analysis Ready Data (ARD) package, which allows the analysis of surface reflectance data as is, without the need to apply additional corrections. It contains two sub-products that provide corrections or attribution information: - Geoscience Australia Sentinel-2A MSI NBART Collection 3 - Geoscience Australia Sentinel-2A Observation Attributes Collection 3 The resolution is a 10/20/60 m grid based on the ESA Level 1C archive. Applications: - The development of derivative products to monitor land, inland waterways and coastal features, such as: - urban growth - coastal habitats - mining activities - agricultural activity (e.g. pastoral, irrigated cropping, rain-fed cropping) - water extent - The development of refined information products, such as: - areal units of detected surface water - areal units of deforestation - yield predictions of agricultural parcels - Compliance surveys - Emergency management

DEA Surface Reflectance Nadir corrected Bidirectional reflectance distribution function Adjusted Reflectance Terrain corrected (NBART) Sentinel-2B Multispectral Instrument (MSI) is part of a suite of Digital Earth Australia's (DEA) Surface Reflectance datasets that represent the vast archive of images captured by the US Geological Survey (USGS) Landsat and European Space Agency (ESA) Sentinel-2 satellite programs, which have been validated, calibrated, and adjusted for Australian conditions — ready for easy analysis. <b>Background:</b> This is a sub-product of DEA Surface Reflectance (Sentinel-2B MSI). See the parent product for more information. Reflectance data at top of atmosphere (TOA) collected by Sentinel-2B MSI sensors can be affected by atmospheric conditions, sun position, sensor view angle, surface slope and surface aspect. Surfaces with varying terrain can introduce inconsistencies to optical satellite images through irradiance and bidirectional reflectance distribution function (BRDF) effects. For example, slopes facing the sun appear brighter compared with those facing away from the sun. Likewise, many surfaces on Earth are anisotropic in nature, so the signal picked up by a satellite sensor may differ depending on the sensor’s position. These need to be reduced or removed to ensure the data is consistent and can be compared over time. <b>What this product offers:</b> This product takes Sentinel-2B MSI imagery captured over the Australian continent and corrects the inconsistencies across the land and coastal fringe. It achieves this using Nadir corrected Bi-directional reflectance distribution function Adjusted Reflectance (NBAR). In addition, this product has a terrain illumination correction applied to correct for varying terrain. The resolution is a 10/20/60 m grid based on the ESA level 1C archive. <b>Applications:</b> - The development of derivative products to monitor land, inland waterways and coastal features, such as: - urban growth - coastal habitats - mining activities - agricultural activity (e.g. pastoral, irrigated cropping, rain-fed cropping) - water extent - The development of refined information products, such as: - areal units of detected surface water - areal units of deforestation - yield predictions of agricultural parcels - Compliance surveys - Emergency management

DEA Surface Reflectance OA (Sentinel-2B MSI) is part of a suite of Digital Earth Australia's (DEA) Surface Reflectance datasets that represent the vast archive of images captured by the US Geological Survey (USGS) Landsat and European Space Agency (ESA) Sentinel-2 satellite programs, which have been validated, calibrated, and adjusted for Australian conditions — ready for easy analysis. <b>Background:</b> This is a sub-product of Geoscience Australia Sentinel-2B MSI Analysis Ready Data Collection 3 - DEA Surface Reflectance (Sentinel-2B MSI). See the parent product for more information. The contextual information related to a dataset is just as valuable as the data itself. This information, also known as data provenance or data lineage, includes details such as the data’s origins, derivations, methodology and processes. It allows the data to be replicated and increases the reliability of derivative applications. Data that is well-labelled and rich in spectral, spatial and temporal attribution can allow users to investigate patterns through space and time. Users are able to gain a deeper understanding of the data environment, which could potentially pave the way for future forecasting and early warning systems. The surface reflectance data produced by NBART requires accurate and reliable data provenance. Attribution labels, such as the location of cloud and cloud shadow pixels, can be used to mask out these particular features from the surface reflectance analysis, or used as training data for machine learning algorithms. Additionally, the capacity to automatically exclude or include pre-identified pixels could assist with emerging multi-temporal and machine learning analysis techniques. <b>What this product offers:</b> This product contains a range of pixel-level observation attributes (OA) derived from satellite observation, providing rich data provenance: - null pixels - clear pixels - cloud pixels - cloud shadow pixels - snow pixels - water pixels - spectrally contiguous pixels - terrain shaded pixels It also features the following pixel-level information pertaining to satellite, solar and sensing geometries: - solar zenith - solar azimuth - satellite view - incident angle - exiting angle - azimuthal incident - azimuthal exiting - relative azimuth - timedelta