<div>Indicator minerals are those minerals that indicate the presence of a specific mineral deposit, alteration or lithology[1]. Their utility to the exploration industry has been demonstrated in a range of environments and across multiple deposit types including Cu-Au porphyry[2], Cu-Zn-Pb-Ag VMS[3] and Ni-Cu-PGE[4]. Recent developments in the field of SEM-EDS analysis have enabled the rapid quantitative identification of indicator minerals during regional sampling campaigns[4,5].</div><div>Despite the demonstrated utility of indicator minerals for diamond and base metal exploration in Canada, Russia and Africa, there are relatively few case studies published from Australian deposits. We present the results of an indicator mineral case study over the Julimar exploration project located 90 km NE of Perth. The Gonneville Ni-Cu-PGE deposit, discovered by Chalice Mining in 2020, is hosted within a ~30 km long belt of 2670 Ma ultramafic intrusions within the western margin of the Yilgarn Craton[6].</div><div>Stream sediments collected from drainage channels around the Gonneville deposit were analysed by quantitative mineralogy techniques to determine if a unique indicator mineral footprint exists there. Samples were processed and analysed for heavy minerals using a workflow developed for the Curtin University-Geoscience Australia Heavy Mineral Map of Australia project[7]. Results indicate elevated abundances of indicator minerals associated with ultramafic/mafic magmatism and Ni-sulfide mineralisation in the drainages within the Julimar project area, including pyrrhotite, pentlandite, pyrite and chromite. We conclude that indicator mineral studies using automated mineralogy are powerful, yet currently underutilised, tools for mineral exploration in Australian environments.</div><div>[1]McClenaghan, 2005. https://doi.org/10.1144/1467-7873/03-066 </div><div>[2]Hashmi et al., 2015. https://doi.org/10.1144/geochem2014-310 </div><div>[3]Lougheed et al., 2020. https://doi.org/10.3390/min10040310 </div><div>[4]McClenaghan &amp; Cabri, 2011. https://doi.org/10.1144/1467-7873/10-IM-026 </div><div>[5]Porter et al., 2020. https://doi.org/10.1016/j.oregeorev.2020.103406 </div><div>[6]Lu et al., 2021. http://dx.doi.org/10.13140/RG.2.2.35768.47367 </div><div>[7]Caritat et al., 2022. https://doi.org/10.3390/min12080961 </div> This Abstract was submitted/presented to the 2023 Australian Exploration Geoscience Conference 13-18 Mar (https://2023.aegc.com.au/)

This report describes the results of an extended national field spectroscopy campaign designed to validate the Landsat 8 and Sentinel 2 Analysis Ready Data (ARD) surface reflectance (SR) products generated by Digital Earth Australia. Field spectral data from 55 overpass coincident field campaigns have been processed to match the ARD surface reflectances. The results suggest the Landsat 8 SR is validated to within 10%, the Sentinel 2A SR is validated to within 6.5% and Sentinel 2B is validated to within 6.8% . Overall combined Sentinel 2A and 2B are validated within 6.6% and the SR for all three ARD products are validated to within 7.7%.

<div>In recent years Geoscience Australia has undertaken a successful continental scale validation program, targeting Landsat and Sentinel analysis ready data surface reflectance products. The field validation model used for this program successfully built on earlier studies and the measurement uncertainties associated with these protocols have been quantified and published. As a consequence, the Australian earth observation community was well-placed to respond to the United States Geological Survey (USGS) call for collaborators with the 2021 Landsat 8 (L8) and Landsat 9 (L9) 6 underfly. Despite a number of challenges, seven validation datasets were captured across five sites. As there was only a single 100% overlap transit across Australia and with the country in the midst of a strong La Niña climate cycle, it was decided to deploy teams to the two available overpasses with only 15% side lap. The validation sites encompassed rangelands, chenopod scrublands and a large inland lake. Apart from instrument problems at one site, good weather enabled the capture of high quality field data allowing for meaningful comparisons between the radiometric performance of L8 and L9, as well as the USGS and Australian Landsat analysis ready data processing models. Duplicate (cross calibration) spectral sampling at different sites provides evidence of the field protocol reliability, while the off-nadir view of L9 over the water site has been used to better compare the performance of different water and atmospheric correction (ATCOR) processing models.&nbsp;</div> <b>Citation: </b>Byrne, G.; Broomhall, M.; Walsh, A.J.; Thankappan, M.; Hay, E.; Li, F.; McAtee, B.; Garcia, R.; Anstee, J.; Kerrisk, G.; et al. Validating Digital Earth Australia NBART for the Landsat 9 Underfly of Landsat 8. <i>Remote Sens.</i> <b>2024</b>, 16, 1233. https://doi.org/10.3390/rs16071233