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  • Extensive benefits and tools can be gained for mineral explorers, land-users and government and university researchers using new spectral data and processing techniques. Improved methods were produced as part of a large multi-agency project focusing on the world-class Mt Isa mineral province in Australia. New approaches for ASTER calibration using high-resolution HyMap imagery through to testing for compensation for atmospheric residuals, lichen and other vegetation cover effects have been included in this study. . Specialised data processing software capable of calibrating and processing terabytes of multi-scene imagery and a new approach to delivery of products, were developed to improve non-specialist user interpretation and comparison with other datasets within a GIS. Developments in processing and detailed reporting of methodology, accuracies and applications can make spectral data a more functional and valuable tool for users of remote sensing data. A highly-calibrated approach to data processing, using PIMA ground samples to validate the HyMap, and then calibrating the ASTER data with the HyMap, allows products to have more detailed reliable accuracies and integration with other data, such as geophysical and regolith information in a GIS package, means new assessments and interpretations can be made in mapping and characterising materials at the surface. Previously undiscovered or masked surface expression of underlying materials, such as ore-deposits, can also be identified using these methods. Maps and products made for this project, covering some ~150 ASTER scenes and over 200 HyMap flight-lines, provide a ready-to-use tool that aids explorers in identifying and mapping unconsolidated regolith material and underlying bedrock and alteration mineralogy.

  • Displays the coverage of publicly available digital gamma-ray spectrometric data. The map legend is coloured according to the line spacing of the survey with broader line spacings (lower resolution surveys) displayed in shades of blue. Closer line spacings (higher resolution surveys are displayed in red, purple and coral.

  • 2nd edition Available as a GA Library resource.

  • Monitoring changes in the spatial distribution and health of biotic habitats requires spatially extensive surveys repeated through time. Although a number of habitat distribution mapping methods have been successful in clear, shallow-water coastal environments (e.g. aerial photography and Landsat imagery) and deeper (e.g. multibeam and sidescan sonar) marine environments, these methods fail in highly turbid and shallow environments such as many estuarine ecosystems. To map, model and predict key biotic habitats (seagrasses, green and red macroalgae, polychaete mounds [Ficopamatus enigmaticus] and mussel clumps [Mytilus edulis]) across a range of open and closed estuarine systems on the south-west coast of Western Australia, we integrated post-processed underwater video data with interpolated physical and spatial variables using Random Forest models. Predictive models and associated standard deviation maps were developed from fine-scale habitat cover data. Models performed well for spatial predictions of benthic habitats, with 79-90% of variation explained by depth, latitude, longitude and water quality parameters. The results of this study refine existing baseline maps of estuarine habitats and highlight the importance of biophysical processes driving plant and invertebrate species distribution within estuarine ecosystems. This study also shows that machine-learning techniques, now commonly used in terrestrial systems, also have important applications in coastal marine ecosystems. When applied to video data, these techniques provide a valuable approach to mapping and managing ecosystems that are too turbid for optical methods or too shallow for acoustic methods.

  • Data gathered in the field during the sample collection phase of the National Geochemical Survey of Australia (NGSA) has been used to compile the Preliminary Soil pH map of Australia. The map, which was completed in late 2009, offers a first-order estimate of where acid or alkaline soil conditions are likely to be expected. It provides fundamental datasets that can be used for mineral exploration and resource potential evaluation, environmental monitoring, landuse policy development, and geomedical studies into the health of humans, animals and plants.

  • Soil mapping at the local- (paddock), to continental-scale, may be improved through remote hyperspectral imaging of surface mineralogy. This opportunity is demonstrated for the semiarid Tick Hill test site (20 km2) near Mount Isa in western Queensland. The study of this test site is part of a larger Queensland government initiative involving the public delivery of 25,000 km2 of processed airborne hyperspectral mineral maps at 4.5 m pixel resolution to the mineral exploration industry. Some of the mineral maps derived from hyperspectral imagery for the Tick Hill area include the abundances and/or physicochemistries (chemical composition and crystal disorder) of dioctahedral clays (kaolin, illite-muscovite and Al smectite, both montmorillonite and beidellite), ferric/ferrous minerals (hematite/goethite, Fe2+-bearing silicates/carbonates) and hydrated silica (opal) as well as soil water (bound and unbound) and green and dry (cellulose/lignin) vegetation. Validation of these hyperspectral mineral products is based on field soil sampling and laboratory analyses (spectral reflectance, X-ray diffraction, scanning electron microscope and electron backscatter). The mineral maps show more detailed information regarding the surface composition compared with the published soil and geology (1:100,000 scale) maps and airborne radiometric imagery (collected at 200 m line spacing). This mineral information can be used to improve the published soil mapping but also has the potential to provide quantitative information suitable for soil and water catchment modeling and monitoring.

  • Geoscience Australia (GA) is a leading promoter of airborne electromagnetic (AEM) surveying for regional mapping of cover thickness, under-cover basement geology and sedimentary basin architecture. Geoscience Australia flew three regional AEM surveys during the 2006-2011 Onshore Energy Security Program (OESP): Paterson (Western Australia, 2007-08); Pine Creek-Kombolgie (Northern Territory, 2009); and Frome (South Australia, 2010). Results from these surveys have produced a new understanding of the architecture of critical mineral system elements and mineral prospectivity (for a wide range of commodities) of these regions in the regolith, sedimentary basins and buried basement terrains. The OESP AEM survey data were processed using the National Computational Infrastructure (NCI) at the Australian National University to produce GIS-ready interpretation products and GOCADTM objects. The AEM data link scattered stratigraphic boreholes and seismic lines and allow the extrapolation of these 1D and 2D objects into 3D, often to explorable depths (~ 500 m). These data sets can then be combined with solid geology interpretations to allow researchers in government, industry and academia to build more reliable 3D models of basement geology, unconformities, the depth of weathering, structures, sedimentary facies changes and basin architecture across a wide area. The AEM data can also be used to describe the depth of weathering on unconformity surfaces that affects the geophysical signatures of underlying rocks. A number of 3D models developed at GA interpret the under-cover geology of cratons and mobile zones, the unconformity surfaces between these and the overlying sedimentary basins, and the architecture of those basins. These models are constructed primarily from AEM data using stratigraphic borehole control and show how AEM data can be used to map the cross-over area between surface geological mapping, stratigraphic drilling and seismic reflection mapping. These models can be used by minerals explorers to more confidently explore in areas of shallow to moderate sedimentary basin cover by providing more accurate cover thickness and depth to target information. The impacts of the three OESP AEM surveys are now beginning to be recognised. The success of the Paterson AEM Survey has led to the Geological Survey of Western Australia announcing a series of OESP-style regional AEM surveys for the future, the first of which (the Capricorn Orogen AEM Survey) completed acquisition in January 2014. Several new discoveries have been attributed to the OESP AEM data sets including deposits at Yeneena (copper) and Beadell (copper-lead-zinc) in the Paterson region, Thunderball (uranium) in the Pine Creek region and Farina (copper) in the Frome region. New tenements for uranium, copper and gold have also been announced on the results of these surveys. Regional AEM is now being applied in a joint State and Commonwealth Government initiative between GA, the Geological Survey of Queensland and the Geological Survey of New South Wales to assess the geology and prospectivity of the Southern Thomson Orogen around Hungerford and Eulo. These data will be used to map the depth of the unconformity between the Thomson Orogen rocks and overlying sedimentary basins, interpret the nature of covered basement rocks and provide more reliable cover thickness and depth to target information for explorers in this frontier area.

  • Explaining spatial variation and habitat complexity of benthic habitats from underwater video through the use of maps. Different methodologies currently used to process and analyse percent cover of benthic organisms from underwater video will be addressed and reviewed.

  • Abstract The ability of thermal infrared (TIR) spectroscopy to characterise mineral and textural content was evaluated for soil samples collected in the semi-arid environment of north-western Queensland, Australia. Grain size analysis and separation of clay, silt and sand sized soil fractions were undertaken to establish the relationship between quartz and clay emissivity signatures and soil texture. Spectral band parameters, based on thermal infrared specular and volume scattering features, were found to discriminate fine clay mineral-rich soil from mostly coarser quartz-rich sandy soil, and to a lesser extent, from the silty quartz-rich soil. This study found that there was the potential for quantifying soil mineral and texture content using TIR spectroscopy. Key Words Soil composition, quartz, kaolinite, smectite, grain size, Tick Hill