Digital Elevation Model data record the terrain height variations from the processed point-located data recorded on an airborne geophysical survey. The aircraft altimeter data records the height of the aircraft above the ground and the aircraft GPS records the height of the aircraft above the ellipsoid. Subtracting the two values enables the height of the terrain beneath the aircraft relative to the ellipsoid to be calculated. This ellipsoidal terrain height is corrected for the variation between the ellipsoid and the geoid (the n-value correction) to produce terrain heights relative to sea level.

<p>The Geological Survey of South Australia commissioned the Gawler Craton Airborne Survey (GCAS) as part of the PACE Copper initiative. The airborne geophysical survey was flown over parts of the Gawler Craton in South Australia. The program was designed to capture new baseline geoscientific data to provide further information on the geological context and setting of the area for mineral systems (http://energymining.sa.gov.au/minerals/geoscience/pace_copper/gawler_craton_airborne_survey). <p>The survey design of 200 m spaced lines at a ground clearance of 60 m can be compared with the design of previous regional surveys which generally employed 400 m line spacing and a ground clearance of 80 m. The new survey design results in ~2 x the data coverage and ~25% closer to the ground when compared to previous standards for regional surveys in South Australia. <p>Survey blocks available for download include: <p>Streaky Bay, block 5 <p>Gairdner, block 6A <p>Spencer, block 7 <p>Kingoonya, block 9B <p>The following grids are available in this download: <p>• Laser-derived digital elevation model grids (m). Height relative to the Australian Height Datum. <p>• Radar-derived digital elevation model grids (m). Height relative to the Australian Height Datum. <p>• Total magnetic intensity grid (nT). <p>• Total magnetic intensity grid with variable reduction to the pole applied (nT). <p>• Total magnetic intensity grid with variable reduction to the pole and first vertical derivative applied (nT/m). <p>• Dose rate concentration grid (nGy/hr). <p>• Potassium concentration grid (%). <p>• Thorium concentration grid (ppm). <p>• Uranium concentration grid (ppm). <p>• NASVD processed dose rate concentration grid (nGy/hr). <p>• NASVD processed potassium concentration grid (%). <p>• NASVD processed thorium concentration grid (ppm). <p>• NASVD processed uranium concentration grid (ppm). <p>The following point located data are available in this download: <p>• Elevation. Height relative to the Australian Height Datum. Datum: GDA94 <p>• Total Magnetic Intensity. Datum: GDA94 <p>• Radiometrics. Datum: GDA94

Effective correction of remotely sensed data for terrain illumination effects over mountainous areas, requires Digital Elevation Model (DEM) data at an appropriate resolution and quality. Conversely, the performance of terrain illumination correction and scale-based analysis could be used to evaluate the quality of DEM data used for the correction. In this study, TanDEM-X Intermediate DEM (IDEM) data at 12 m resolution and the 1-arc second Shuttle Radar Topography Mission (SRTM) data were used independently to evaluate the relative effectiveness of the terrain illumination correction for Landsat 8 optical data over Tasmania, Australia. Results from the terrain illumination correction and filter bank analysis show that IDEM 12 m data can resolve finer details of terrain shading than the SRTM based DEM and deliver better results in areas with detail-rich terrain. However, in the data available for this study, spikes and other noise artefacts were prevalent, especially over areas covered by water; removal of such noise artefacts would increase the utility of the IDEM for operational correction of terrain illumination effects in optical satellite data. Presented at the TerraSAR-X /TanDEM-X Science Team Meeting 2016, Oberpfaffenhofen, Germany

<div>Intertidal environments contain many important ecological habitats such as sandy beaches, tidal flats, rocky shores, and reefs. These environments also provide many valuable benefits such as storm surge protection, carbon storage, and natural resources.&nbsp;</div><div>&nbsp;</div><div>Intertidal zones are being increasingly faced with threats including coastal erosion, land reclamation (e.g. port construction), and sea level rise. These regions are often highly dynamic, and accurate, up-to-date elevation data describing the changing topography and extent of these environments is needed. However, this data is expensive and challenging to map across the entire intertidal zone of a continent the size of Australia. &nbsp;</div><div>&nbsp;</div><div>The intertidal zone also forms a critical habitat and foraging ground for migratory shore birds and other species. An improved characterisation of the exposure patterns of these dynamic environments is important to support conservation efforts and to gain a better understanding of migratory species pathways. &nbsp;</div><div>&nbsp;</div><div>The <strong>DEA Intertidal </strong>product suite (https://knowledge.dea.ga.gov.au/data/product/dea-intertidal) provides annual continental -scale elevation and exposure products for Australia’s intertidal zone, mapped at a 10m resolution, from Digital Earth Australia’s archive of open-source Landsat and Sentinel-2 satellite data. These intertidal products enable users to better monitor and understand some of the most dynamic regions of Australia’s coastlines.</div><div><br></div><div><strong>Applications</strong></div><div><br></div><div> - Integration with existing topographic and bathymetric data to seamlessly map the elevation of the coastal zone.&nbsp;</div><div>&nbsp;</div><div> - Providing baseline elevation data for predicting the impact of coastal hazards such as storm surges, tsunami inundation, or future sea-level rise.&nbsp;</div><div>&nbsp;</div><div> - Investigating coastal erosion and sediment transport processes.&nbsp;</div><div>&nbsp;</div><div> - Supporting habitat mapping and modelling for coastal ecosystems extending across the terrestrial to marine boundary.&nbsp;</div><div>&nbsp;</div><div> - Characterisation of the spatio-temporal exposure patterns of the intertidal zone to support migratory species studies and applications.&nbsp;</div><div><br></div><div><br></div><div><br></div>

This resource contains a bathymetry compilation prepared by the University of Western Australia for the North West Shelf of Australia, between the Cape Range and the Dampier Peninsula. The compilation includes, by decreasing resolution: - Publicly available MBES datasets, made available by Geoscience Australia by December 2019. - Satellite derived bathymetry produced using 1000+ images acquired between January 2017 and December 2019. - Seismic derived bathymetry extracted from 100+ surveys acquired between 1981 and 2015. - SRTM topography, reprocessed by Galant et al, 2011: https://pid.geoscience.gov.au/dataset/ga/72759 - 2009 Australian Bathymetry and Topography grid: https://pid.geoscience.gov.au/dataset/ga/67703 The Seismic and Satellite derived bathymetry grids are also available as individual layers. The vertical and spatial accuracy of the datasets have been thoroughly assessed using high-resolution datasets including publicly available MBES and LADS surveys. The assessment indicates that the seismic derived bathymetry has a depth accuracy better than 1 m + 2% of the absolute water depths while the satellites derived bathymetry has a depth accuracy better than 1 m + 5% of the absolute water depths. A detailed methodology is provided in: Lebrec et al, 2021. Towards a regional high-resolution bathymetry of the North West Shelf of Australia based on Sentinel-2 satellite images, 3D seismic surveys and historical datasets. (in prep.) This dataset is published with the permission of the CEO, Geoscience Australia. AUTHOR’S NOTICE: This dataset should not be used, under any circumstances, for navigation. When used, the dataset should be referenced as follow: Lebrec, U., Paumard, V., O'Leary, M. J., and Lang, S. C.: Towards a regional high-resolution bathymetry of the North West Shelf of Australia based on Sentinel-2 satellite images, 3D seismic surveys and historical datasets, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2021-128, in review, 2021.

Collection of Geoscience Australia's high-resolution elevation surveys collected using Light Detection and Ranging (LiDAR) and other instrument systems. <b>Value: </b>Describes Australia's landforms and seabed is crucial for addressing issues relating to the impacts of climate change, disaster management, water security, environmental management, urban planning and infrastructure design. <b>Scope: </b>Selected areas of interest around Australia.

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 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 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.