The uranium squared over thorium grid is a derivative of the 2019 radiometric or gamma-ray grid of Australia. The radiometric, or gamma-ray spectrometric method, measures the natural variations in the gamma-rays detected near the Earth's surface as the result of the natural radioactive decay of potassium (K), uranium (U) and thorium (Th). The data are collected on airborne geophysical surveys conducted by Commonwealth, State and Northern Territory Governments and the private sector. The 2019 uranium squared over thorium was derived by seamlessly merging over 600 airborne gamma-ray spectrometric surveys. The final grid has a cell size of about 100m (0.001 degrees) and is derived from the filtered uranium and thorium grids.

The thorium over potassium grid is a derivative of the 2019 radiometric or gamma-ray grid of Australia. The radiometric, or gamma-ray spectrometric method, measures the natural variations in the gamma-rays detected near the Earth's surface as the result of the natural radioactive decay of potassium (K), uranium (U) and thorium (Th). The data are collected on airborne geophysical surveys conducted by Commonwealth, State and Northern Territory Governments and the private sector. The 2019 thorium over potassium was derived by seamlessly merging over 600 airborne gamma-ray spectrometric surveys. The final grid has a cell size of about 100m (0.001 degrees) and is derived from the filtered thorium and potassium grids.

The filtered potassium grid is a derivative of the 2019 radiometric or gamma-ray grid of Australia. The radiometric, or gamma-ray spectrometric method, measures the natural variations in the gamma-rays detected near the Earth's surface as the result of the natural radioactive decay of potassium, uranium and thorium. The data are collected on airborne geophysical surveys conducted by Commonwealth, State and Northern Territory Governments and the private sector. The 2019 filtered potassium grid has a cell size of about 100m (0.001 degrees) and shows potassium element concentrations of the Australia region. It was obtained by applying a low-pass filter to the original potassium grid. Potassium is the seventh most abundant element in the Earth's crust. This potassium concentration grid can be used to locate minerals and compounds containing potassium.

The complete infilled K, eTh and eU grids are based on the Radiometric Map of Australia (radmapv4) 2019 (Poudjom Djomani and Minty, 2019a, b, c) with gaps in coverage infilled using environmental correlation machine learning prediction. The radiometric, or gamma-ray spectrometric method, measures the natural variations in the gamma-rays detected near the Earth's surface as the result of the natural radioactive decay of potassium (K), uranium (U) and thorium (Th). However because Uranium and Thorium abundances are calculated by measuring gamma emission associated with their daughter radionuclides they are typically expressed as equivalent eU and eTh. The 2019 radiometric grid is compiled from airborne geophysical surveys conducted by Commonwealth, State and Northern Territory Governments and the private sector. Over 600 airborne gamma-ray spectrometric surveys were merged and gridded to a cell size of approximately 100m (0.001 degrees) to produce the Radiometric Map of Australia (radmapv4) 2019. Gamma-rays emitted from the surface mainly relate to the mineralogy and geochemistry of the bedrock and weathered materials or regolith. To infill gaps in the national gamma-ray grid (radmapv4 -2019) we have compiled a set of national covariates or predictive datasets that capture landscape processes, regolith and geology that are likely correlated to the distribution of K, eTh and eU at the surface. These datasets include satellite imagery (to map surface mineralogy and vegetation), terrain attributes (e.g. slope, relief), gravity (Lane et al, 2020) and surface geology. A boosted regression tree algorithm called XGBoost (open-source software library for gradient boosting machine learning) was used to train relationships between airborne estimates of K, eTh and eU with the covariate datasets. The training set used the Australia Wide Airborne Geophysical Survey (AWAGS) (Milligan et al., 2009). Local model predictions were generated for gaps in the 2019 version of the national grid by clipping subsets of the AWAGS survey lines and in places extracting additional training survey sites from nearby surveys. The strength of the correlations between the training observation and the covariates were highest in semi-arid areas with decreasing correlations from K through to eTh and eU. Modelled grids of K, eTh and eU were merged with the Radiometric Map of Australia (radmapv4 -2019) using the grid merge module in Intrepid Geophysics software. The first step was to scale the modelled dataset to the reference dataset, then apply a DC shift. The second step was to surface adjust the grid, which computes a two dimensional surface calculated from the differences in its value between the reference grid, it then fits a difference surface with the largest mean signal value and reiterates this process until the difference is within a pre-defined threshold. The third step is to merge the modelled dataset with the Radiometric Map of Australia (radmapv4) 2019, using a feathering process where measured radiometric values are ranked higher over the modelled data. The complete infill radiometric grids have been generated for regolith (including soils) and geological mapping and can be used as a seamless dataset for predictive modelling using machine learning. The product can be seen as an interim dataset until the gaps are filled in through new airborne survey acquisition. It is important to recognise that the infill grids are based on correlations between airborne flight-line estimates of the radioelements and covariate thematic datasets. Responses and patterns observed within these gap areas are therefore not reflecting measurements using the airborne spectrometry. Equally, the covariate approach should not be expected to confidently identify gamma-ray ‘outliers’ or anomalies that have been used in other geophysical survey approaches. Lane, R. J. L., Wynne, P. E., Poudjom Djomani, Y. H., Stratford, W. R., Barretto, J. A., and Caratori Tontini, F., 2020, 2019 Australian National Gravity Grids: Geoscience Australia, eCat Reference Number 133023, https://pid.geoscience.gov.au/dataset/ga/133023 Milligan, P., Minty, B., Richardson, M and Franklin, R. 2009 The Australia-Wide Airborne Geophysical Survey - accurate continental magnetic coverage, ASEG, Extended Abstracts, 2009:1, 1-9 Poudjom Djomani, Y., Minty, B.R.S. 2019a. Radiometric Grid of Australia (Radmap) v4 2019 unfiltered pct potassium. Geoscience Australia, eCat reference number 131978. http://dx.doi.org/10.26186/5dd4a7851e8db Poudjom Djomani Y., Minty, B.R.S. 2019b. Radiometric Grid of Australia (Radmap) v4 2019 unfiltered ppm thorium. Geoscience Australia, ecat reference number 131988. http://dx.doi.org/10.26186/5dd4a821a334d Poudjom Djomani, Y., Minty, B.R.S. 2019c. Radiometric Grid of Australia (Radmap) v4 2019 filtered ppm uranium. Geoscience Australia, eCat reference number 131974. http://dx.doi.org/10.26186/5dd48ee78c980

This grid is derived from gravity observations stored in the Australian National Gravity Database (ANGD) as at February 2016 as well as data from the 2013 New South Wales Riverina gravity survey. Out of the approximately 1.8 million gravity observations 1,371,998 gravity stations in the ANGD together with 19,558 stations from the Riverina survey were used to generate this image. The grid shows isostatic residual gravity anomalies over onshore continental Australia. The data used in this grid has been acquired by the Commonwealth, State and Territory Governments, the mining and exploration industry, universities and research organisations from the 1940's to the present day. The isostatic corrections were based on the assumption that topographic loads are compensated at depth by crustal roots following the Airy-Heiskanen isostatic principle. A crustal density of 2670 kg/m3 was used for the isostatic correction, with an assumed density contrast between the crust and mantle of 400 kg/m3. An initial average depth to Moho at sea level of 37 km was used in the calculation. The isostatic corrections were then applied to the Complete Bouguer Gravity Anomaly Grid of Onshore Australia 2016 to produce the Isostatic Residual Gravity Anomaly Grid of Onshore Australia 2016.

This gravity anomaly grid is derived from observations stored in the Australian National Gravity Database (ANGD) as at February 2016 as well as data from the 2013 New South Wales Riverina gravity survey. Out of the almost 1.8 million records in the ANGD approximately 1.4 million stations together with 19,558 stations from the Riverina survey were used to generate this grid. This product shows spherical cap Bouguer anomalies over onshore continental Australia. The data used in this grid has been acquired by the Commonwealth, State and Territory Governments, the mining and exploration industry, universities and research organisations from the 1940's to the present day. The spherical cap Bouguer anomalies in this grid are the combination of Bullard A and B corrections to the Free Air anomaly values using a density of 2670 kg/m^3.

The uranium over potassium grid is a derivative of the 2019 radiometric or gamma-ray grid of Australia comprising over 600 airborne gamma-ray spectrometric surveys. The radiometric, or gamma-ray spectrometric method, measures the natural variations in the gamma-rays detected near the Earth's surface as the result of the natural radioactive decay of potassium (K), uranium (U) and thorium (Th). The data are collected on airborne geophysical surveys conducted by Commonwealth, State and Northern Territory Governments and the private sector. The 2019 uranium over potassium grid has a cell size of about 100 m (0.001 degrees) and is derived from the filtered uranium and potassium grids.

The unfiltered thorium grid is a derivative of the 2019 radiometric or gamma-ray grid of Australia which is a merge of over 600 individual gamma-ray spectrometric surveys. The radiometric, or gamma-ray spectrometric method, measures the natural variations in the gamma-rays detected near the Earth's surface as the result of the natural radioactive decay of potassium (K), uranium (U) and thorium (Th). The data are collected on airborne geophysical surveys conducted by Commonwealth, State and Northern Territory Governments and the private sector. The 2019 unfiltered thorium grid has a cell size of about 100 m (0.001 degrees) and shows thorium element concentrations of the Australia region.

Total magnetic intensity (TMI) data measures variations in the intensity of the Earth magnetic field caused by the contrasting content of rock-forming minerals in the Earth crust. Magnetic anomalies can be either positive (field stronger than normal) or negative (field weaker) depending on the susceptibility of the rock. A variable reduction to Pole is aimed at locating magnetic anomalies exactly above their source bodies and without any distortion. The 2019 Total magnetic Intensity (TMI) grid of Australia with variable reduction to pole (VRTP) has a grid cell size of ~3 seconds of arc (approximately 80 m). This grid only includes airborne-derived TMI data for onshore and near-offshore continental areas. The VRTP processing followed a differential reduction to pole calculation up to 5th order polynomial. Magnetic inclination and declination were derived from the IGRF-11 geomagnetic reference model using a data representative date of January 2005 and elevation 300 m.

Total magnetic intensity (TMI) data measures variations in the intensity of the Earth magnetic field caused by the contrasting content of rock-forming minerals in the Earth crust. Magnetic anomalies can be either positive (field stronger than normal) or negative (field weaker) depending on the susceptibility of the rock. The 2019 Total magnetic Intensity (TMI) grid of Australia has a grid cell size of ~3 seconds of arc (approximately 80 m). This grid only includes airborne-derived TMI data for onshore and near-offshore continental areas. Since the sixth edition was released in 2015, data from 234 new surveys have been added to the database, acquired mainly by the State and Territory Geological Surveys. The new grid was derived from a re-levelling of the national magnetic grid database. The survey grids were levelled to each other, and to the Australia Wide Airborne Geophysical Survey (AWAGS), which serves as a baseline to constrain long wavelengths in the final grid. It is estimated that 33 500 000 line-kilometres of survey data were acquired to produce the 2019 grid data, about 2 000 000 line-kilometres more than for the previous edition.