Data

National ASTER Map of Australia

Geoscience Australia
Cudahy, T. ; Caccetta, M. ; Thomas, M.
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.4225/25/560E19D4926F4&rft.title=National ASTER Map of Australia&rft.identifier=10.4225/25/560E19D4926F4&rft.publisher=Geoscience Australia Geoscience Australia&rft.description=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)Maintenance and Update Frequency: notPlannedStatement: 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);&rft.creator=Cudahy, T. &rft.creator=Caccetta, M. &rft.creator=Thomas, M. &rft.date=2012&rft.coverage=westlimit=111.5; southlimit=-44.5; eastlimit=155; northlimit=-9&rft.coverage=westlimit=111.5; southlimit=-44.5; eastlimit=155; northlimit=-9&rft_rights=Creative Commons Attribution 4.0 International Licence http://creativecommons.org/licenses/&rft_rights=Australian Government Security ClassificationSystem https://www.protectivesecurity.gov.au/Pages/default.aspx&rft_subject=geoscientificInformation&rft_subject=EARTH SCIENCES&rft_subject=HVC_144626&rft_subject=Remote Sensing&rft_subject=Satellite imagery&rft_subject=Earth Observations from Space&rft_subject=mineralogy&rft_subject=NCI&rft_subject=Published_External&rft.type=dataset&rft.language=English Access the data
Cite Saved to MyRDA Save to MyRDA

Licence & Rights:

Open Licence view details
CC-BY

Creative Commons Attribution 4.0 International Licence
http://creativecommons.org/licenses/

Australian Government Security ClassificationSystem
https://www.protectivesecurity.gov.au/Pages/default.aspx

Access:

Open

Full description

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/carbonate
Surface mineral group distribution (relative abundance and composition)

Lineage

Maintenance and Update Frequency: notPlanned
Statement: 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);

Issued: 2012

This dataset is part of a larger collection

Click to explore relationships graph
Help

Related Data

Related People

155,-9 155,-44.5 111.5,-44.5 111.5,-9 155,-9

133.25,-26.75

text: westlimit=111.5; southlimit=-44.5; eastlimit=155; northlimit=-9

Subjects
Earth Sciences | Earth Observations from Space | HVC_144626 | NCI | Published_External | Remote Sensing | Satellite imagery | geoscientificInformation | mineralogy |

User Contributed Tags    

Login to tag this record with meaningful keywords to make it easier to discover

Other Information
Link to data - NCI

url : https://thredds.nci.org.au/thredds/catalogs/wx7/catalog.xml

Link to Digital Earth Australia data page

url : http://data.dea.ga.gov.au

Link to NCI web service

url : https://gsky.nci.org.au/ows/aster

National ASTER Map Regolith Ratios

local : 74349

National ASTER Map green vegetation content

local : 74350

National ASTER Map Ferric oxide content

local : 74351

National ASTER Map Ferric oxide composition

local : 74352

National ASTER Map Ferrous iron index

local : 74353

National ASTER Map Opaque index

local : 74354

National ASTER Map AlOH group content

local : 74355

National ASTER Map AlOH group composition

local : 74356

National ASTER Map Kaolin group index

local : 74357

National ASTER Map FeOH group content

local : 74358

National ASTER Map MgOH group content

local : 74359

National ASTER Map MgOH group composition

local : 74360

National ASTER Map Ferrous iron content in MgOH/carbonate

local : 74361

National ASTER Map TIR Silica index

local : 74362

National ASTER Map TIR Quartz index

local : 74363

National ASTER Map TIR Gypsum index

local : 74364

Identifiers