This is the parent datafile of a dataset that comprises a set of 14+ geoscience products made up of mosaiced ASTER (Advanced
Spaceborne Thermal Emission and Reflection Radiometer) scenes across Australia. The individual geoscience products are a combination
of bands and band ratios to highlight different mineral groups and parameters including: False colour composite CSIRO Landsat
TM Regolith Ratios Green vegetation content Ferric oxide content Ferric oxide composition Ferrous iron index Opaque index
AlOH group content AlOH group composition Kaolin group index FeOH group content MgOH group content MgOH group composition
Ferrous iron content in MgOH/carbonateSurface mineral group distribution (relative abundance and composition)
For detailed product notes and history please see associated "NATIONAL ASTER MAP PRODUCT NOTES" More accurate mapping of land
surface composition at a continental-scale for improved resource exploration is becoming possible through a new generation
of remote sensing technologies. These include the multi-spectral Japanese ASTER sensor onboard the US TERRA satellite which
was launched in December 1999 and has now collected an image archive that effectively covers the Earth's land surface three
times over. ASTER calibration, processing and standardisation approaches have been produced as part of a large multi-agency
project to facilitate uptake of these techniques and make them easily integrated with other datasets in a GIS. Collaborative
research, undertaken by Geoscience Australia, the Commonwealth Scientific Research Organisation (CSIRO) and state and industry
partners, on the world-class Mt Isa mineral province in Queensland was completed in 2008 as a test-case for these new methods.
The project demonstrated that geochemical information about alteration chemistry associated with footprints of mineral systems
can be acquired by analysing spectral ground response, particularly in short-wave infra-red. Key materials that can be identified
include clays and magnesium/iron/ aluminium oxyhydroxides, as well as information on mineral composition, abundance and physicochemistry
(including crystallinity) for minerals such as kaolinite, which can be used as a surrogate for identifying transported versus
in situ regolith material. High resolution mineral maps, from instruments such as HyMap, and Hyperion allow the recognition
of various types of hydrothermal alteration, and can map and distinguish between distinct geochemical and mineralogical alteration
halos and fluid pathways. The techniques and applications applied in the Mount Isa program were extended into a similar study
for the eastern Gawler and Curnamona Cratons in South Australia, and now into the National ASTER mosaic and maps of Australia,
using Hyperion satellite data as a means to calibrate the lower resolution ASTER data The following is a summary of the ASTER
image processing procedure: Details will be provided in related publications currently in preparation. 1. Acquisition of the
required ASTER L1B radiance@sensor data with SWIR cross-talk correction applied (www.gds.aster.ersdac.or.jp). Note that ASTER
L2 "surface radiance" or "surface reflectance" can also be used; 2. SWIR Cross-talk correction (ERSDAC GDS software); 3. Geometric
correction; 4. Converting the three 15 m VNIR bands to 30 m pixel resolution; 5. Generating a single nine band VNIR-SWIR image
file (L1B) for each ASTER scene; 6. Solar irradiance correction; 7. Masking clouds and green vegetation; 8. Generation of
ERMapper headers; 9. Calculation of statistics for masked-image overlaps and global scene response; 10. Scene ordering (best
scenes up front in the mosaic); 11. Application of gains and offsets to cross-calibrate all images to a global response; 12.
Reduction to "surface" reflectance using independent validation data (e.g. satellite Hyperion data). This requires selecting
overlapping "regions of interest" (ROI) and calculating statistics to generate regression coefficients (gains and offsets).
Alternatively, if independent EO data are not available then an estimate of the additive component (Equations 1 and 2) can
be measured using a "dark-pixel" approach. The "dark pixel" can be estimated using: (1) deep water (very effective for SWIR
bands away from sun glint angle); or (2) extrapolation to the dark-point using at least different materials illuminated under
a range of different topographic conditions; 13. Application of the correction data (offset +/- gain for each band per scene/mosaic);
14. Geoscience information extraction: Application of "normalisation" scripts (see Tables 1 and 2 for product details);
Metadata hierarchy level name:
dataset - GIS Dataset - National
Metadata language
eng
Metadata character set encoding:
utf8
Metadata standard for this record:
ANZLIC Metadata Profile: An Australian/New Zealand Profile of AS/NZS ISO 19115:2005, Geographic information - Metadata
standard version:
1.1
Metadata record identifier:
c3e62161-0fd4-2149-e044-00144fdd4fa6
URI for dataset described:
> http://www.ga.gov.au/metadata-gateway/metadata/record/74347/
Metadata record format is ISO19139-2 XML (MI_Metadata)