Grace Cumming's research while affiliated with Geological Survey of South Australia and other places

This Record documents the efforts of Mineral Resources Tasmania (MRT) and Geoscience Australia (GA) in compiling a geochronology (age) compilation for Tasmania, describing both the dataset itself and the process by which it is incorporated into the continental-scale Isotopic Atlas of Australia. The Isotopic Atlas draws together age and isotopic data from across the country and provides visualisations and tools to enable non-experts to extract maximum value from these datasets. Data is added to the Isotopic Atlas in a staged approach with priorities determined by GA- and partner-driven focus regions and research questions. This Tasmanian compilation represents the second in a series of compilation publications (Records and Datasets) for the southern states of Australia, which are a foundation for the second phase of the Exploring for the Future initiative over 2020–2024. It was compiled primarily from data, reports, journal articles and theses provided to GA by MRT. The most current data can be accessed and downloaded from GA’s EFTF Geochronology and Isotopes Data Portal and MRT’s LISTmap.

The Heazlewood-Luina-Waratah area is a prospective region for minerals in northwest Tasmania, Australia, associated with historically important ore deposits related to the emplacement of granite intrusions and/or ultramafic complexes. The geology of the area is poorly understood due to the difficult terrain and dense vegetation. We construct an initial high-resolution 3D geological model of this area using constraints from geological maps, and geological and geophysical cross sections. This initial model is improved upon by integrating results from 3D geometry and physical property inversion of potential field (gravity and magnetic) data, petrophysical measurements, and updated field mapping. Geometry inversion reveals that the Devonian granites in the south are thicker than previously thought, possibly connecting to deep sources of mineralization. In addition, we identified gravity anomalies to the northeast that could be caused by near-surface granite cupolas. A newly discovered ultramafic complex linking the Heazlewood and Mount Stewart Ultramafic Complexes in the southwest has also been modeled. This implies a greater volume of ultramafic material in the Cambrian successions and points to a larger obducted component than previously thought. The newly inferred granite cupolas and ultramafic complexes are targets for future mineral exploration. Petrophysical property inversion reveals a high degree of variation in these properties within the ultramafic complexes indicating a variable degree of serpentinization. Sensitivity tests suggest maximum depths of 2-3 km for the contact aureole that surrounds major granitic intrusions in the southeast, while the Heazlewood River complex is likely to have a deeper source up to 4 km. Our case study illustrates the value of adding geological and petrophysical constraints to 3D modeling for the purpose of guiding mineral exploration. This is particularly important for the refinement of geological structure in tectonically complex areas that have lithology units with contrasting magnetic and density characteristics.

The Tonian to Ediacaran geology of Tasmania, Australia preserves an extensive record of continental rifting related to the Neoproterozoic opening of the Pacific Ocean. We integrate new and previously published structural, stratigraphic, sedimentary provenance, age, and geochemical data to establish four tectonostratigraphic stages in Tasmania that formed during three episodes of Neoproterozoic rifting. Rift Event 1 initiated with Tonian (780—750 Ma) intraplate magmatism and clastic sedimentation and was followed by deposition of an eastward thickening and deepening succession of ≤ 780 Ma—730 Ma locally sourced siliciclastic strata and carbonate (tectonostratigraphic stage 1). Cryogenian glaciogenic strata and thick successions of mafic volcaniclastic turbidites (tectonostratigraphic stage 2) contain unimodal 670—640 Ma detrital zircon age populations and may record a second rift event (Rift Event 2). Final rifting (Rift Event 3) involved voluminous ca. 580 Ma basaltic volcanism and active extensional faulting (tectonostratigraphic stage 3) and was followed by latest Ediacaran to early Cambrian sag-phase deposition (tectonostratigraphic stage 4). Neoproterozoic rifting in Tasmania is broadly contemporaneous with punctuated Tonian to Ediacaran rifting along the paleo-margins of the Pacific Ocean in southeast Australia, East Antarctica, and western Laurentia. Rift Event 1 in Tasmania may record the rifting of Australia-Antarctica from western Laurentia to form the nascent Pacific Ocean. Geological correlations are consistent with models in which Tasmania remained attached to either eastern Australia-Antarctica or western Laurentia during the late Tonian and Cryogenian before being isolated as a microcontinent in the late Ediacaran during Rift Event 3.

Mineral exploration and geological mapping of highly prospective areas in western Tasmania, southern Australia, is challenging due to steep topography, dense vegetation, and limited outcrop. Synthetic aperture radar (SAR) can potentially penetrate vegetation canopies and assist geological mapping in this environment. This study applies manual and automated lithological classification methods to airborne polarimetric TopSAR and geophysical data in the Heazlewood region, western Tasmania. Major discrepancies between classification results and the existing geological map generated fieldwork targets that led to the discovery of previously unmapped rock units. Manual analysis of radar image texture was essential for the identification of lithological boundaries. Automated pixel-based classification of radar data using Random Forests achieved poor results despite the inclusion of textural information derived from gray level co-occurrence matrices. This is because the majority of manually identified features within the radar imagery result from geobotanical and geomorphological relationships, rather than direct imaging of surficial lithological variations. Inconsistent relationships between geology and vegetation or geology and topography limit the reliability of TopSAR interpretations for geological mapping in this environment. However, Random Forest classifications, based on geophysical data and validated against manual interpretations, were accurate (∼90%) even when using limited training data (∼0.15% of total data). These classifications identified a previously unmapped region of mafic–ultramafic rocks, the presence of which was verified through fieldwork. This study validates the application of machine learning for geological mapping in remote and inaccessible localities but also highlights the limitations of SAR data in thickly vegetated terrain.

Gaps in the geological knowledge of Tasmania are in large part due to the inaccessibility and forested nature of large areas. Remote sensing methods have provided datasets useful in producing interpretive maps for field checking but are less useful in areas that lack rocks with contrasting geophysical properties. LiDAR has the capability of providing a DEM in remote and forested areas that is rich in geological information, revealing bedding traces and folds. LiDAR surveys in the lightly forested north east of Tasmania proved to be successful in revealing enough mappable micro-topographic bedding features to produce geological maps. However similar surveys in more heavily forested areas produced relatively poor DEMs, characterised by poor ground point density, high noise and numerous classification errors. Recent advances in LiDAR instrumentation, including increased power, increased pulse frequency, decreased echo separation and faster detection electronics had the potential to improve the resulting DEMs in rain forested areas. Experimental surveys in western Tasmania aimed to find the LiDAR survey specifications that maximises returns from the ground through thick forest. The most efficient survey specification is that which maximises the number of LiDAR pulses emitted, but sufficient ground returns from beneath tall trees could only be achieved by increasing the spot diameter. A variety of interpolation methods were tested to produce a 2m DEM that maximises geologically related micro-topography. The minimum curvature (i.e. thin plate spline) method with small tension (lambda) was found to be optimal. A 5m 2 nd derivative (curvature) image was most useful in identifying bedding traces. GIS tools have been developed to mark bedding traces traversing topography and calculate strike and dip using the moment of inertia method. In the Mathinna area in northeast Tasmania 1150 structural measurements were interpreted from 40 km 2 , improving mapping efficiency by 40% and providing important constraints on structural interpretation. At Waratah in western Tasmania, LiDAR is being used to interpret the structural geology of remote areas covered by rain forest. Stratigraphic units assumed to be continuous are actually highly segmented, with blocks entrained in structurally complex zones. LiDAR remote sensing using appropriate survey specifications and effective GIS tools to aid interpretation has delivered the ability to efficiently build reconnaissance geological maps rich in structural information. The technique promises to deliver a step change in geological mapping and structural interpretation of forested terrain.