RB 2023/00030 A user’s guide to the Gawler Craton Airborne Survey magnetic field datasets. Visualisation and interpretation.
Published: 01 Mar 2023 Created: 29 May 2025 Revised: 30 May 2025

The Gawler Craton Airborne Survey (GCAS) was completed in July 2019 and provides detailed airborne magnetic, radiometric, and digital elevation coverage across approximately 30% of South Australia and 55% of the Gawler Craton. The GCAS was a...

The Gawler Craton Airborne Survey (GCAS) was completed in July 2019 and provides detailed airborne magnetic, radiometric, and digital elevation coverage across approximately 30% of South Australia and 55% of the Gawler Craton. The GCAS was a significant improvement on previous regional geophysical surveys and thus represents a valuable resource for geoscientists; particularly in areas of extensive Cenozoic sedimentary cover such as the western Gawler Craton. A wide range of enhanced and derivative products were delivered as part of the GCAS project, and the technical aspects of the different data enhancements has been well documented in previous publications. The GCAS magnetic field data enhancements include several commonly used derivatives, such as the reduced-to-pole TMI and the first vertical derivative of the TMI; in addition to several less commonly used data enhancements. However, the geological utility of these analytical products has not been examined in detail. This report book provides a summary of the geological benefits and potential drawbacks of different magnetic field transformations and enhancements. These datasets are critical for the new interpretation of the Gawler’s craton basement geology, which is being undertaken as part of the SA Discovery Mapping project (SADM). It should be noted that the magnetic field enhancements are not viewed in isolation, but rather multiple filters / derivatives are considered during the geological interpretation of magnetic data (and other geophysical datasets). The differences between filtered datasets can be subtle but their comparison leads to the recognition and refinement of interpreted geological features. A coherent geological interpretation also depends on appropriate data visualisation to minimize visual anomalies and avoid the misinterpretation of geological features. Modern GIS software allows geoscientists to customise the visualisation of their raster datasets. Unfortunately, data can be misrepresented if not visualised correctly, particularly if an inappropriate colour map is used. Scientifically derived colour maps help resolve this issue by providing truer representations of the data and minimising visual distortion. This report book provides advice on how to visualise magnetic field datasets to avoid misinterpretation of geological features and aid with their ‘correct’ geological interpretation. Appropriate data visualisation and the comparison of a variety of different datasets will ensure that the resulting interpretative map is as close as possible to reality.

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About this record

Record No 2023d025277
Topic Geoscientific Information
Type of Resource Document
Category Type
Document Type Departmental Publication - Geological Survey Geoscience Publication
Contributor Geological Survey of South Australia
Sponsor
Tenement
Tenement Holder
Operator
Geological Province
Mine Name
Stratigraphy
Commodity
    Notes
    Doc No: RB 2023/00030

    Doc No: RB 2023/00030

    Language English
    Metadata Standard ISO 19115-3

    Citations

    Use constraints License
    License Creative Commons Attribution 4.0
    Persistent identifier https://pid.sarig.sa.gov.au/document/2023d025277
    Citation McMaster, M.;Pawley, M.;Katona, L.;Irvine, J.;Jones, T.;Gouthas, G.;Keeping, T. 2023. RB 2023/00030 A user’s guide to the Gawler Craton Airborne Survey magnetic field datasets. Visualisation and interpretation. Departmental Publication - Geological Survey Geoscience Publication. Government of South Australia.
    https://pid.sarig.sa.gov.au/document/2023d025277

    Technical information

    Status
    Maintenance and Update Frequency
    Geographic Reference GDA2020 (EPSG:7844)
    Geo bounding box {"type":"Polygon","coordinates":[[[131,-34],[138,-34],[138,-27],[131,-27],[131,-34]]]}
    Purpose
    
                        
                        
    
                        
                      
    Lineage