Marine heat waves (MHWs) have significant ecological and economic impact. Consequently, there is a pressing need to map the temporal and spatial patterns of MHWs, for both historical and near real-time events. Satellite remote sensing of Sea Surface Temperature (SST) provides fundamental data for the mapping of MHWs. This study used high-resolution Himarwari-8 SST and the Sea Surface Temperature Atlas of the Australian Regional Seas (SSTAARS) data, which have a spatial resolution of ~ 2 km, to map recent and near real-time MHW events in waters around Australasia. The high-resolution MHWs mapping has identified two broad areas of MHW hotspots between August 2015 and February 2019. Firstly, the Tropical Warm Pool region (including the GBR and part of the Coral Sea) between the maritime continent and the Australian continent was affected by strong and prolonged MHW conditions for the greater part of 2016. The unusually strong 2015-16 El Niño event was believed to be the primary driver for the MHWs, and the air-sea heat flux rather than the ocean advection was the main local process controlling the heat budget. Secondly, the south-east of the study area (including Australia’s south-east coast, the Tasman Sea and New Zealand’s east coast) suffered severe MHWs in 2015-16, 2017-18 and 2018-19. ENSO played little role in the generation of the MHWs in this region. Instead, the MHWs in the western part of this region were more likely due to the extensive heat transported by the East Australia Current; while in the eastern part, the MHWs were more likely due to more local climate modes such as SAM. This mapping has not only enhanced our understanding of the spatio-temporal characteristics of several previously documented MHWs but also identified and mapped several previously undocumented MHWs. The case study in the Beagle Marine Park proved the values of Himawari-8 SST and SSTAARS data in mapping fine details of MHWs in a small area, which are not possible for broad-scale SST data such as the Optimal Interpolated SST (OISST) which has a spatial resolution of ~ 25 km. The case study revealed much stronger MHW influence in the shallow waters east of the marine park where most of the important rocky reef habitats exist. The near-real time MHWs mapping shows that both the GBR and the Coral Sea marine parks were experiencing MHW conditions in early March 2020, with most affected areas having strong MHW class.

This job was part of the Coastal capture program. It captures from the coast to the 10m contour interval.

These datasets cover approximately 2250 sq km in the central sector of the Cassowary Coast Regional Council and over all of Dunk and Hinchinbrook Islands and are part of the 2009 Tropical Coast LiDAR capture project. This project, undertaken by Fugro Spatial Solutions Pty Ltd on behalf of the Queensland Government captured highly accurate elevation data using LiDAR technology. Available dataset formats (in 2 kilometre tiles) are: - Classified las (LiDAR Data Exchange Format where strikes are classified as ground, non-ground or building) - ASCII xyz dataset of LiDAR ground returns - ASCII xyz dataset of LiDAR ground returns - 1 metre Digital Elevation Model (DEM) in ASCII xyz - 1 metre Digital Elevation Model (DEM) in ESRI ASCII grid - 1 metre Digital Elevation Model (DEM) in ESRI binary grid - 0.25 metre contours in ESRI Shape

Melbourne 2007-2008

These datasets cover approximately 743 sq km over Atherton, Biboohra-Koah, Chillagoe, Dimbulah, Herberton, Irvinebank, Kairi-Tinaroo, Malanda, Mareeba, Millaa-Millaa, Millstream, Mt Carbine, Mt Garnet, Mt Molloy, Mutchilba, Rangeview-Tolga, Ravenshoe, Speewah, Walkamin, Watsonville and Yungaburra in the Tablelands Regional Council and were captured as part of the 2011 Tablelands LiDAR project. This project, undertaken by Terranean Mapping Technologies on behalf of the Tablelands Regional Council captured highly accurate elevation data using LiDAR technology. Available dataset formats (in 1 kilometre tiles) are: - Classified las (LiDAR Data Exchange Format where strikes are classified as ground, vegetation or building) - 1 metre Digital Elevation Model (DEM) in ASCII xyz - 1 metre Digital Elevation Model (DEM) in ESRI ASCII grid - 0.25 metre contours in ESRI Shape

These datasets cover approximately 2290 sq km in the eastern and southern sectors of the Cairns Regional Council and were captured as part of the 2010 Cairns LiDAR project. This project, undertaken by Terranean Mapping Technologies on behalf of the Queensland Government captured highly accurate elevation data using LiDAR technology. Available dataset formats (in 1 kilometre tiles) are: - Classified las (LiDAR Data Exchange Format where strikes are classified as ground, vegetation or building) - 1 metre Digital Elevation Model (DEM) in ASCII xyz - 1 metre Digital Elevation Model (DEM) in ESRI ASCII grid - 0.25 metre contours in ESRI Shape

Here we present the surficial geology map for the Vestfold Hills, East Antarctica. On the coast of Prydz Bay, the region is one of the largest ice-free areas in Antarctica. Surficial geology mapping at 1:2000 was undertaken with field observations in the 2018/19 and 2019/20 summer seasons as well as aerial photography and satellite imagery interpretation. Units are based on the Geological Survey of Canada Surficial Data Model Version 2.4.0 (Deblonde et al 2019).

These datasets cover approximately 514 sq km over the Towns of Esk, Kilcoy and Toogoolawah and over Lockyer Creek Gap in the Somerset Regional Council and are part of the 2011 Inland Towns Stage 3 LiDAR capture project. This section of the project, undertaken by AAM Pty Ltd on behalf of the Queensland Government captured highly accurate elevation data using LiDAR technology. Available dataset formats (in 1 kilometre tiles) are: - Classified las (LiDAR Data Exchange Format where strikes are classified as ground, non-ground, vegetation or building) - 1 metre Digital Elevation Model (DEM) in ASCII xyz - 1 metre Digital Elevation Model (DEM) in ESRI ASCII grid - 0.25 metre contours in ESRI Shape

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.

This job is part of the Town capture program as prioritized by the SES