The regolith landform maps are drawn at various scales and illustrate the distribution of regolith materials and the landforms on which they occur. Regolith landforms are described using the regolith terrain mapping (RTMAP) scheme developed at Geoscience Australia or the Residual-Erosional-Depositional (RED) mapping scheme developed by the CSIRO Division of Exploration and Mining.

Weathering is an important process of the Earth’s surface that has a major influence on the chemical and physical properties of rock and soil. The intensity of this process largely controls the degree to which primary minerals are altered to secondary components, including clay and oxide minerals. The degree of surface weathering is particularly important in Australia, where variations in weathering intensity correspond to differences in the nature and distribution of regolith (weathered bedrock and sediments), which mantles approximately 80% of the Australian continent. Here, I use a random forest decision tree machine learning algorithm to first establish a relationship between field estimates of the degree of weathering and a comprehensive suite of covariate or predictive datasets. I then apply this relationship to generate an improved national model of surface to near-surface weathering intensity. Covariates include satellite imagery, terrain attributes, airborne radiometric imagery and mapped geology. The model performs very well, with an r-squared correlation of 0.85 based on 5 K-fold cross-validation on the mean and standard deviation of 300 random forest models. This new weathering intensity model has broad utility for mineral exploration in variably weathered landscapes, agricultural mapping of chemical and physical soil attributes, ecology, and advancing the understanding of weathering processes within the upper regolith. <b>Citation:</b> Wilford, J., 2020. Revised weathering intensity model of Australia. In: Czarnota, K., Roach, I., Abbott, S., Haynes, M., Kositcin, N., Ray, A. and Slatter, E. (eds.) Exploring for the Future: Extended Abstracts, Geoscience Australia, Canberra, 1–4.

Australia has a significant number of surface sediment geochemical surveys that have been undertaken by industry and government over the past 50 years. These surveys represent a vast investment and have up to now only been able to be used in isolation, independently from one another. The key to maximising the full potential of these data and the information they provide for mineral exploration, environmental management and agricultural purposes is using all the surveys together, seamlessly. These disparate geochemical surveys not only sampled various landscape elements and analysed a range of size fractions, but also used multiple analytical techniques, instrument types and laboratories. The geochemical data from these surveys require levelling to eliminate, as much as possible, non-geological variation. Using a variety of methodologies, including reanalysis of both international standards and small subsets of samples from previous surveys, we have created a seamless surface geochemical map for northern Australia, from nine surveys with 15,605 samples. We tested our approach using two surveys from the southern Thomson Orogen, which demonstrated the successful removal of inter-laboratory and other analytical variation. Creation of the new combined and levelled northern Australian dataset paves the way for the application of statistical and data analytics techniques, such as principal component analysis and machine learning, thereby maximising the value of these legacy data holdings. The methodology documented here can be applied to additional geochemical datasets as they become available.

Estimating the relative contributions of bedrock geology, mineralisation and anthropogenic contamination to the chemistry of samples collected at the Earth’s surface is critical in research and application fields as diverse as environmental impact studies and regional mineral exploration programs. The element lead (Pb) is a particularly useful tracer in this context, representing a toxin of environmental concern and associated with many other anthropogenic contaminants (e.g. mine wastes, waters, paints, aerosols), as well as with mineralisation. Although Pb concentration data are frequently collected in geochemical studies, isotopic analysis offers an important advantage, allowing discrimination between different sources of Pb. The Pb isotopic composition of regolith is likely to reflect contributions from underlying rock (including Pb-rich mineralisation), wind-blown dust and possibly anthropogenic sources (industry, transport, agriculture, residential, waste handling). Regolith samples collected at different depths may show distinct compositions; bedrock isotopic signatures are expected to dominate in deeper soils, whilst airborne dust and anthropogenic signatures are more important at the surface. Pb isotope ratios in the continental crust show large variations, which will be transferred to the regolith, providing a potentially unique bedrock signal that is easily measured. This research program examines if soil Pb isotope mapping can identify the underlying geology and metallogenic provinces, if different sampling and analytical approaches produce very different results, and how anthropogenic signals vary across the continent. Here, we present our results for the Northern Territory, where single regolith samples from many (not all) catchments define apparently consistent isotopic domains that can be interpreted in relation to the underlying geology (crystalline basement, basins) and mineral deposits. <b>Citation:</b> Desem, C.U., Maas, R., Woodhead, J., Carr, G. and de Caritat P., 2020. Towards a Pb isotope regolith map of the Australian continent: a Northern Territory perspective. In: Czarnota, K., Roach, I., Abbott, S., Haynes, M., Kositcin, N., Ray, A. and Slatter, E. (eds.) Exploring for the Future: Extended Abstracts, Geoscience Australia, Canberra, 1–4.

The results of a pilot study into the application of an unsupervised clustering approach to the analysis of catchment-based National Geochemical Survey of Australia (NGSA) geochemical data combined with geophysical and geological data across northern Australia are documented. NGSA Mobile Metal Ion® (MMI) element concentrations and first and second order statistical summaries across catchments of geophysical data and geological data are integrated and analysed using Self-Organising Maps (SOM). Input features that contribute significantly to the separation of catchment clusters are objectively identified and assessed. A case study of the application of SOM for assessing the spatial relationships between Au mines and mineral occurrences in catchment clusters is presented. Catchments with high mean Au code-vector concentrations are found downstream of areas known to host Au mineralisation. This knowledge is used to identify upstream catchments exhibiting geophysical and geological features that indicate likely Au mineralisation. The approach documented here suggests that catchment-based geochemical data and summaries of geophysical and geological data can be combined to highlight areas that potentially host previously unrecognised Au mineralisation. <b>Citation:</b> M. J. Cracknell, P. de Caritat; Catchment-based gold prospectivity analysis combining geochemical, geophysical and geological data across northern Australia. <i>Geochemistry: Exploration, Environment</i>, Analysis 2017; 17 (3): 204–216. doi: https://doi.org/10.1144/geochem2016-012 This article appears in multiple journals (Lyell Collection & GeoScienceWorld)

<div>Bulk quantitative mineralogy of regolith is a useful indicator of lithological precursor (protolith), degree of weathering, and soil properties affecting various potential landuse decisions. To date, no empirical national-scale maps of regolith mineralogy are available in Australia. Satellite-derived mineralogical proxy products exist, however, they require on-the-ground validation. Catchment outlet sediments collected over 80% of the continent as part of the National Geochemical Survey of Australia (NGSA) afford a unique opportunity to rapidly and cost-effectively determine regolith mineralogy using the archived sample material. This report releases mineralogical data and metadata obtained as part of a study extending a previous pilot project for such a national regolith mineralogy database and atlas.</div><div>The area chosen for this study includes the part of South Australia not inside the pilot project, which focussed on the 2020-2024 Exploring for the Future (EFTF) Darling-Curnamona-Delamerian (DCD) region of southeastern Australia, as well as the EFTF Barkly-Isa-Georgetown (BIG) region of northern Australia. The South Australian part of the study was selected because the Geological Survey of South Australia indicated interest in expanding the pilot (DCD) project to the rest of the State. The BIG region was selected because it is a ‘deep-dive’ data acquisition and analysis area within the EFTF Australian Government initiative managed at Geoscience Australia. The whole study area essentially describes a continuous north-south trans-continental transect spanning South Australia (SA), Queensland (Qld) and the Northern Territory (NT), and is herein abbreviated as SA-Qld-NT.</div><div>Two hundred and sixty four NGSA sites from the SA-Qld-NT region were prepared for X-Ray Diffraction (XRD) analysis, which consisted of qualitative mineral identification of the bulk samples (i.e., ‘major’ minerals), qualitative clay mineral identification of the <2 µm grain-size fraction, and quantitative analysis of both major and clay minerals of the bulk sample. The identified mineral phases were quartz, kaolinite, plagioclase, K-feldspar, nosean (a sulfate bearing feldspathoid), calcite, dolomite, aragonite, ankerite, hornblende, gypsum, bassanite (a partially hydrated calcium sulfate), halite, hematite, goethite, magnetite, rutile, anatase, pyrite, interstratified or mixed-layer illite-smectite, smectite, muscovite, chlorite (group), talc, palygorskite, jarosite, alunite, and zeolite (group). Poorly diffracting material was also quantified and reported as ‘amorphous.’ Mineral identification relied on the EVA® software, whilst quantification was performed using Siroquant®. Resulting mineral abundances are reported with a Chi-squared goodness-of-fit between the actual diffractogram and a modelled diffractogram for each sample, as well as an estimated standard error (esd) measurement of uncertainty for each mineral phase quantified. Sensitivity down to 0.1 weight percent (wt%) was achieved, with any mineral detection below that threshold reported as ‘trace.’ </div><div>Although detailed interpretation of the mineralogical data is outside the remit of the present data release, preliminary observations of mineral abundance patterns suggest a strong link to geology, including proximity to fresh bedrock, weathering during sediment transport, and robust relationships between mineralogy and geochemistry. The mineralogical data generated by this study are downloadable as a .csv file from the Geoscience Australia website (https://dx.doi.org/10.26186/147990).&nbsp;</div>

Satellite imagery provides useful data for mapping the characteristics of exposed rock and soil. However, these materials in many environments are masked by vegetation. To address this the Sentinel-2 Barest Earth thematic product provides a national scale mosaic of the Australian continent with significantly reduced influence of seasonal vegetation cover to support enhanced mapping of soil and geology. The barest earth algorithm, operating on all available Sentinel-2 A and Sentinel-2 B observations up to September 2020, preferentially weights bare ground exposure through time to more directly map the surface mineralogy and geochemistry of soil and rock. The algorithm uses a high-dimensional weighted geometric median approach that maintains the spectral relationships across all Sentinel-2 bands building on a similar approach applied to the deeper Landsat time series archive. Both barest earth products have spectral bands in the visible near infrared and shortwave infrared region of the electromagnetic spectrum. However, the main visible and near-infrared Sentinel-2 bands have a spatial resolution of 10 meters compared to 30m for the Landsat TM equivalents. Furthermore, although the first Sentinel-2 satellite was launched in 2015 the twin orbiting satellite configuration provides shorter revisit times that increase the frequency of observations and probability of observing barer pixels amongst observations obscured by clouds and shadows. The Sentinel-2 satellite has broad application in environmental and geological sciences. The barest earth approach generates a complimentary set of spectral bands with reduced vegetation influence for more directed geological applications. We discuss the barest earth algorithm and compare non-bare and barest earth Sentinel-2 imagery. A series of enhance Sentinel-2 images are used to illustrate the potential of the barest earth datasets for mapping soil and bedrock and we summarise key band ratios that can be used as proxies for mapping surface mineralogy including iron oxides and hydroxyl minerals.

The National Geochemical Survey of Australia (NGSA) provides an internally consistent, state-of-the-art, continental-scale geochemical dataset that can be used to assess areas of Australia more elevated in commodity metals and/or pathfinder elements than others. But do regions elevated in such elements correspond to known mineralized provinces, and what is the best method for detecting and thus potentially predicting those? Here, using base metal associations as an example, I compare a trivariate rank-based index and a multivariate-based Principal Component Analysis method. The analysis suggests that the simpler rank-based index better discriminates catchments endowed with known base metal mineralization from barren ones and could be used as a first-pass prospectivity tool. <b>Citation:</b> Patrice de Caritat, Continental-scale geochemical surveys and mineral prospectivity: Comparison of a trivariate and a multivariate approach, <i>Journal of Geochemical Exploration</i>, Volume 188, 2018, Pages 87-94, ISSN 0375-6742, https://doi.org/10.1016/j.gexplo.2018.01.014

During the last 10-20 years, Geological Surveys around the world have undertaken a major effort towards delivering fully harmonized and tightly quality controlled low-density multi-element soil geochemical maps and datasets of vast regions including up to whole continents. Concentrations of between 45 and 60 elements commonly have been determined in a variety of different regolith types (e.g., sediment, soil). The multi-element datasets are published as complete geochemical atlases and made available to the general public. Several other geochemical datasets covering smaller areas but generally at a higher spatial density are also available. These datasets may, however, not be found by superficial internet-based searches because the elements are not mentioned individually either in the title or in the keyword lists of the original references. This publication attempts to increase the visibility and discoverability of these fundamental background datasets covering large areas up to whole continents. <b>Citation:</b> P. de Caritat, C. Reimann, D.B. Smith, X. Wang, Chemical elements in the environment: Multi-element geochemical datasets from continental- to national-scale surveys on four continents, <i>Applied Geochemistry</i>, Volume 89, 2018, Pages 150-159, ISSN 0883-2927, https://doi.org/10.1016/j.apgeochem.2017.11.010

Mapped and projected extents of geology and geologic features in Australia, including: surface geology, regolith geology, solid geology, chronostratigraphic surfaces, and province boundaries. The database includes igneous, sedimentary and structural characteristics, age limits, parent and constituent units, relations to surrounding provinces, and mineral and petroleum resources. based on field observations interpretations of geophysics and borehole data. <b>Value:</b> Data used for understanding surface and near surface geology. The data can be used for a variety of purposes, including resource exploration, land use management, and environmental assessment. <b>Scope:</b> Australia and Australian Antarctic Territory