The 'Australian Antarctic Territory coastline 2003' dataset is a digital vector representation of the coastline of Antarctica, between 45 to 160 degrees east, based on both the edge of permanent ice and grounding line, derived by means of remote sensing interpretation. A 'proof of concept' methodology over a test area was carried out to compare a number of complementary remote sensing techniques, including interferometry and airborne ice radar profiling, to confirm validation of grounding line as mapped from Landsat 7 ETM+ imagery. This methodology concept then served to validate grounding line locations elsewhere along the coast of the AAT. The National Mapping Division of Geoscience Australia and the Australian Antarctic Division developed this dataset as a joint project. Where available, Australian Antarctic Division supplied large-scale vector data of various areas around the AAT, which were included as part of the main coastline dataset. These included: * Holme Bay 1:25,000 GIS dataset * Larsemann Hills - Mapping from aerial photography captured February 1998 * Rauer Group 1:50000 Topographic GIS Dataset * Vestfold Hills Topographic GIS Dataset * Windmill Islands 1:50000 Topographic GIS Dataset * Cape Denison and McKellar Islands GIS dataset from Ikonos satellite imagery Refer to the metadata record for each of these datasets for further information. The coastline dataset is comprised of three parts: one polygon coverage consisting of ice features, and another one consisting of coastal features. A third coverage consists of only island point features (islands too small to be shown as polygons). This dataset supersedes the Australian Antarctic Territory Coastline 2001 dataset which is also part of SCAR's Antarctic Digital Database (ADD) version 4 and version 5. It replaces data digitised from Landsat 4 and 5, with that from Landsat 7 ETM+, because of its more reliable positional accuracy and more recent acquisition. The Australian Antarctic Territory Coastline 2001 dataset and metadata record have been archived. Please contact the Australian Antarctic Data Centre if you would like a copy of this data and metadata.

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• AAT_Coastline_2003

AU_AADC Short Name: AAT_Coastline_2003 Version ID: 1 Unique ID: C1214305672-AU_AADC

A Digital Elevation Model (DEM) of Heard island, with a 50 metre grid interval, and held in UTM Zone 43(WGS-84) coordinates. Heights are referenced to mean sea level. 50 metre contours (including a coastline) were derived. Elevation range 0 - less than 2800m.

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• heard_dem_radarsat97

AU_AADC Short Name: heard_dem_radarsat97 Version ID: 1 Unique ID: C1214313515-AU_AADC

The aim of the project was to derive a number of control points that could be used to georeference two Radarsat scenes over Heard Island. Control points were derived from aerial photography covering various locations around the island, namely: Cape Gazert, Atlas Cove, Brown Lagoon, Manning Lagoon and Winston Lagoon. ERDAS Imagine with OrthoBase Pro photogrammatric software was used to ortho-rectify the aerial photography and extract values for the derived control points. ERDAS Imagine OrthoRadar was used to georeference the Radarsat images. The measurements taken from the aerial photography have been described in an earlier report.

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• Heard_RadarSat_georef

AU_AADC Short Name: Heard_RadarSat_georef Version ID: 1 Unique ID: C1214313518-AU_AADC

The Heard Island, Laurens Peninsula, Topographic Data was mapped from Ortho-rectified non-metric photography. The data consists of Coastline, Crater, Volcano, Island, Lagoon, Water Storage and Watercourse datasets digitised from the photography.

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• photo_mosaic_laurens_or_TopoMapping

AU_AADC Short Name: photo_mosaic_laurens_or_TopoMapping Version ID: 1 Unique ID: C1214311225-AU_AADC

Measurements of ice velocity and strain rate have been derived by analysis of satellite images for the Lambert Glacier and Amery Ice Shelf system. Two techniques have been applied in the production of the two main sets of velocity values. One technique uses 'feature tracking' in pairs of Landsat TM images. This process uses surface features that persist with time and move with the ice as tracers of the ice motion. The displacement of these features over the time interval between acquisition of the two images in a pair is determined by image correlation. A reference sub-image is extracted from one image and the best correlation is searched for in the other image. The pair of images were registered by comparing fixed features such as rock outcrops or areas of known ice velocity. The analysis is carried at regular increments across and along the images, to produce a regular grid of values. The derived values are edited and accepted according to whether they satisfy certain a priori constraints for the flow in a local region and the statistics of a set of velocity values within a window. The TM images have been pre-processed to project them onto a common reference and projection system, and spliced together, in order to produce a seamless set of velocity values. Many tens of thousands of observations have been extracted along the entire length of the system (about 600+ km). The other technique has been applied to analysis of Synthetic Aperture Radar images. It uses a procedure applied during SAR interferometry [InSAR] to register small sections of the SAR complex image for generation of the phase difference or fringe image. The process we have applied uses maximum coherence as a test for best match or correlation of two image chips extracted from a pair of coherent complex SAR images. This procedure uses the phase information inherent in the SAR data in place of features as used for the TM analysis. From this analysis a set of displacements is derived comparable to the results for feature tracking. The displacements are derived in the range coordinate system of the complex SAR images. The displacements are converted to velocity values in the ground coordinate system. Corrections are also applied at this stage to allow for errors in the satellite orbits for the two sets of SAR acquisitions. One velocity data set derived from analysis of SAR data from the Canadian Space Agency's Radarsat covers an 800 km length of the system. Further data are being extracted by InSAR analysis of SAR data from the European Space Agency's ERS tandem mission. Horizontal components of strain rate are derived from the velocity data using a set of derivative operators in a least-squares solution of an over-constrained set of equations, which uses all velocity values within a computation window. This procedure effectively produces a set of average velocity and strain rate values and accounts for much of the 'noise' in the individual velocity observations. Values of the local longitudinal, transverse and shear strain rate components are derived by rotation of the cartesian values to the local flow direction. This metadata record has been derived from work performed under the auspices of ASAC project 2224 (ASAC_2224).

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• AAD_Ant_LG-AIS_vel_strain

AU_AADC Short Name: AAD_Ant_LG-AIS_vel_strain Version ID: 1 Unique ID: C1214305517-AU_AADC