The Secondary Coastal Sediment Compartment data set represents a sub-regional-scale (1:100 000 - 1:25 000) compartmentalisation of the Australian coastal zone into spatial units within (and between) which sediment movement processes are considered to be significant at scales relevant to coastal management. The Primary and accompanying Secondary Coastal Sediment Compartment data sets were created by a panel of coastal science experts who developed a series of broader scale data sets (Coastal Realms, Regions and Divisions) in order to hierarchically subdivide the coastal zone on the basis of key environmental attributes. Once the regional (1:250 000) scale was reached expert knowledge of coastal geomorphology and processes was used to further refine the sub-division and create both the Primary and Secondary Sediment Compartment data sets. Environmental factors determining the occurrence and extents of these compartments include major geological structures, major geomorphic process boundaries, orientation of the coastline and recurring patterns of landform and geology - these attributes are given in priority order below. 1 - Gross lithological/geological changes (e.g. transition from sedimentary to igneous rocks). 2 - Geomorphic (topographic) features characterising a compartment boundary (often bedrock-controlled) (e.g. peninsulas, headlands, cliffs). 3 - Dominant landform types (e.g. large cuspate foreland, tombolos and extensive sandy beaches versus headland-bound pocket beaches). 4 - Changes in the orientation (aspect) of the shoreline.

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 web service contains a selection of remotely sensed raster products used in the Exploring for the Future (EFTF) East Kimberley Groundwater Project. Selected products were derived from LiDAR, Landsat (5, 7, and 8), and Sentinel-2 data. Datasets include: 1) mosaic 5 m digital elevation model (DEM) with shaded relief; 2) vegetation structure stratum and substratum classes; 3) Normalised Difference Vegetation Index (NDVI) 20th, 50th, and 80th percentiles; 4) Tasselled Cap exceedance summaries; 5) Normalised Difference Moisture Index (NDMI) and Normalised Difference Wetness Index (NDWI). Landsat spectral reflectance products can be used to highlight land cover characteristics such as brightness, greenness and wetness, and vegetation condition; Sentinel-2 datasets help to detect vegetation moisture stress or waterlogging; LiDAR datasets providing a five meter DEM and vegetation structure stratum classes for detailed analysis of vegetation and relief.

This service delivers the base of Cenozoic surface and Cenozoic thickness grids for the west Musgrave province. The gridded data are a product of 3D palaeovalley modelling based on airborne electromagnetic conductivity, borehole and geological outcrop data, carried out as part of Geoscience Australia's Exploring for the Future programme. The West Musgrave 3D palaeovalley model report and data files are available at https://dx.doi.org/10.26186/149152.

This web service contains map layers and coverages for machine learning models, using raster datasets which include radiometric grid infill, cover depths and conductivity. All grids have been converted to cloud-optimised GeoTIFF (COG) format for use and delivery from an cloud-based object store (AWS s3).

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

Melbourne Geelong LiDAR 2007

Victoria Coast 2007-2008

These datasets cover all of Redland City and are part of the 2009 South East Queensland LiDAR capture project. This project, undertaken by AAM Hatch 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 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 Purpose: To provide highly accurate elevation data for use in risk assessment, the management of natural disasters, infrastructure planning, developing strategies to support climate change, topographic mapping and modelling. Environment description: Language: eng Character set: unknown

This web service contains a selection of remotely sensed raster products used in the Exploring for the Future (EFTF) East Kimberley Groundwater Project. Selected products were derived from LiDAR, Landsat (5, 7, and 8), and Sentinel-2 data. Datasets include: 1) mosaic 5 m digital elevation model (DEM) with shaded relief; 2) vegetation structure stratum and substratum classes; 3) Normalised Difference Vegetation Index (NDVI) 20th, 50th, and 80th percentiles; 4) Tasselled Cap exceedance summaries; 5) Normalised Difference Moisture Index (NDMI) and Normalised Difference Wetness Index (NDWI). Landsat spectral reflectance products can be used to highlight land cover characteristics such as brightness, greenness and wetness, and vegetation condition; Sentinel-2 datasets help to detect vegetation moisture stress or waterlogging; LiDAR datasets providing a five meter DEM and vegetation structure stratum classes for detailed analysis of vegetation and relief.