{"help": "https://data.gov.au/data/api/3/action/help_show?name=package_show", "success": true, "result": {"archived": false, "author_email": null, "contact_point": "clientservices@ga.gov.au", "creator_user_id": "c2fbbe4a-4ba0-4945-808b-67454605a4cf", "duplicate_score": 2, "geospatial_topic": [], "id": "81d5904f-aad5-4717-a49e-79ed02445c76", "isopen": false, "language": "eng", "license_id": "notspecified", "license_title": "notspecified", "maintainer": null, "maintainer_email": null, "metadata_created": "2025-11-18T21:47:43.586734", "metadata_modified": "2025-11-18T21:47:43.586741", "name": "trans-dimensional-bayesian-inversion-of-airborne-electromagnetic-data-for-2d-conductivity-profi1", "notes": "This paper presents the application of a novel trans-dimensional sampling approach to a time domain airborne electromagnetic (AEM) inverse problem to solve for plausible conductivities of the subsurface. Geophysical inverse problems, such as time domain AEM, are well known to have a large degree of non-uniqueness. Common least-squares optimization approaches fail to take this into account and provide a single solution with linearized estimates of uncertainty which can result in overly optimistic appraisal of the conductivity of the subsurface. In this new non-linear approach, the spatial complexity of a 2D profile is controlled directly by the data. By examining an ensemble of proposed conductivity profiles it accommodates non-uniqueness and provides more robust estimates of uncertainties.\nCitation: Hawkins, R., Brodie, R. C., & Sambridge, M. (2018). Trans-dimensional Bayesian inversion of airborne electromagnetic data for 2D conductivity profiles. 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