The 3 second (~90m) Smoothed Digital Elevation Model (DEM-S) Version 1.0 was derived from resampling the 1 second SRTM derived DEM-S (gridded smoothed digital elevation model; ANZCW0703014016). The DEM represents ground surface topography, excluding vegetation features, and has been smoothed to reduce noise and improve the representation of surface shape. The DEM-S was derived from the 1 second Digital Surface Model (DSM; ANZCW0703013336) and the Digital Elevation Model Version 1.0 (DEM; ANZCW0703013355) by an adaptive smoothing process that applies more smoothing in flatter areas than hilly areas, and more smoothing in noisier areas than in less noisy areas. This DEM-S supports calculation of local terrain shape attributes such as slope, aspect and curvatures that could not be reliably derived from the unsmoothed 1 second DEM because of noise. A full description of the methods is in progress (Gallant et al., in prep) and in the 1 second User Guide. The 3 second DEM was produced for use by government and the public under Creative Commons attribution. The 1 second DSM and DEM that forms the basis of the product are also available as 3 second products (DSM; ANZCW0703014216, DEM; ANZCW0703014182, DEM-S; ANZCW0703014217). <strong>Please note that all 1 second products are available for GOVERNMENT USERS ONLY.</strong>

The Perth 2008 LiDAR data was captured over the Perth region during February, 2008. The data was acquired by AAMHatch (now AAMGroup) and Fugro Spatial Solutions through a number of separate missions as part of the larger Swan Coast LiDAR Survey that covers the regions of Perth, Peel, Harvey, Bunbury and Busselton. The project was funded by Department of Water, WA for the purposes of coastal inundation modelling and a range of local and regional planning. The data are made available under licence for use by Commonwealth, State and Local Government. The data was captured with point density of 1 point per square metre and overall vertical accuracy has been confirmed at <15cm (68% confidence). The data are available as a number of products including mass point files (ASCII, LAS) and ESRI GRID files with 1m grid spacing. A 2m posting hydrologically enforced digital elevation model (HDEM) and inundation contours has also been derived for low lying coastal areas.

The Peel 2008 LiDAR data was captured over the Peel region during February, 2008. The data was acquired by AAMHatch (now AAMGroup) and Fugro Spatial Solutions through a number of separate missions as part of the larger Swan Coast LiDAR Survey that covers the regions of Perth, Peel, Harvey, Bunbury and Busselton. The project was funded by Department of Water, WA for the purposes of coastal inundation modelling and a range of local and regional planning. The data are made available under licence for use by Commonwealth, State and Local Government. The data was captured with point density of 1 point per square metre and overall vertical accuracy has been confirmed at <15cm (68% confidence). The data are available as a number of products including mass point files (ASCII, LAS) and ESRI GRID files with 1m grid spacing. A 2m posting hydrologically enforced digital elevation model (HDEM) and inundation contours has also been derived for low lying coastal areas.

Removing the topographic effect from satellite images is a very important step in order to obtain comparable surface reflectance in mountainous areas and to use the images for different purposes on the same spectral base. The most common method of normalising for the topographic effect is by using a Digital Surface Model (DSM) and / or a Digital Elevation Model (DEM). However, the accuracy of the correction depends on the accuracy, scale and spatial resolution of DSM data as well as the co-registration between the DSM and satellite images. A physics based BRDF and atmospheric correction model in conjunction with a 1-second SRTM (Shuttle Radar Topographic Mission) derived DSM product released by Geoscience Australia in 2010 were used to conduct the analysis reported in this paper. The results show that artefacts in the DSM data can cause significant local errors in the correction. For some areas, false shadow and over corrected surface reflectance factors have been observed. In other areas, the algorithm is unable to detect shadow or retrieve an accurate surface reflectance factor in the slopes away from the sun. The accuracy of co-registration between satellite images and DSM data is crucial for effective topographic correction. A mis-registration error of one or two pixels can lead to large error of retrieved surface reflectance factors in the gully and ridge areas (retrieved reflectance factors can change from 0.3 to 0.5 or more). Therefore, accurate registrations for both satellite images and DSM data are necessary to ensure the accuracy of the correction. Using low resolution DSM data in conjunction with high resolution satellite images can fail to correct some significant terrain effects. A DSM resolution appropriate to the scale of the resolution of satellite image is needed for the best results.

National Elevation Data Audit is a report outlining all elevation data available across all Australian jurisdictions which was identified by the Intergovernment Committee on Surveying and Mapping's (ICSM) Permanent Committee on Topographic Information (PCTI).

This report describes products, outputs and outcomes of the three-dimensional (3D) visualisation component of the Great Artesian Basin Water Resource Assessment (the Assessment). This report specifically encompasses the following topics associated with the 3D visualisation component: - the requirements and potential benefits - the effective datasets - methodology used in content creation - the output datasets - discussions regarding outcomes, limitations and future directions. The Assessment is designed to assist water managers in the Great Artesian Basin (GAB) to meet National Water Initiative commitments. The key datasets of the 3D visualisation component include contact surfaces between major aquifers and aquitards with coverage of significant portions of the GAB, well lithostratigraphic and wire-line data and hydrogeochemistry produced by State and National Agencies. These datasets are manipulated within GOCAD® to develop the 3D visualisation component and communication products for use by end users to assist visualisation and conceptualisation of the GAB. While many options have been investigated for distribution of these 3D products, 2D screen captures and content delivery via the Geoscience Australia (GA) World Wind 3D data viewer will be the most efficient and effective products. Citation: Nelson GJ, Carey H, Radke BM and Ransley TR (2012) The three-dimensional visualisation of the Great Artesian Basin. A report to the Australian Government from the CSIRO Great Artesian Basin Water Resource Assessment. CSIRO Water for a Healthy Country Flagship, Australia

The quality and type of elevation data used in tsunami inundation models can lead to large variations in the estimated inundation extent and tsunami flow depths and speeds. In order to give confidence to those who use inundation maps, such as emergency managers and spatial planners, standards and guidelines need to be developed and adhered to. However, at present there are no guidelines for the use of different elevation data types in inundation modelling. One reason for this is that there are many types of elevation data that differ in vertical accuracy, spatial resolution, availability and expense; however the differences in output from inundation models using different elevation data types in different environments are largely unknown. This study involved simulating tsunami inundation scenarios for three sites in Indonesia, of which the results for one of these, Padang, is reported here. Models were simulated using several different remotely-sensed elevation data types, including LiDAR, IFSAR, ASTER and SRTM. Model outputs were compared for each data type, including inundation extent, maximum inundation depth and maximum flow speed, as well as computational run-times. While in some cases, inundation extents do not differ greatly, maximum depths can vary substantially, which can lead to vastly different estimates of impact and loss. The results of this study will be critical in informing tsunami scientists and emergency managers of the acceptable resolution and accuracy of elevation data for inundation modelling and subsequently, the development of elevation data standards for inundation modelling in Indonesia.

Map is an image of the seafloor and land topograhpy with the seafloor data between latitudes 64 degrees North and 72 degrees South by Smith and Sandwell (1997) with more information from W.H.F Smith and D.T. Sandwell, Global Seafloor Topography from Satellite Altimetry and Ship Depth Soundings, Science, v.277, p. 1956-1962, 26 September 1997. This has been combined with land topography from the Global Land One-km Base Elevation (GLOBE) Project. This image has been modified in ER Mapper to increase the depth perception by chaning the sun angle.

The 2009 National Elevation Audit is a series of maps illustrating the areas where elevation data has been captured or will be completed until the end of 2009 and their relative vertical accuracy.

Elevation data and products such as Digital Elevation Models derived from these data comprise an essential layer within the National Spatial Data Infrastructure. Historically the creation of these datasets has been the domain of National and State mapping agencies. However, in recent years the rapid development of survey technologies and industry capability, the need for high resolution elevation data to meet a range of purposes, and the nature of government funding arrangements has resulted in significant project-based investment.