A robust interpolation-based method for forensic soil provenancing. A Bayesian likelihood ratio approach
<div>Soil is a complex and spatially variable material that has a demonstrated potential to be a useful evidence class in forensic casework and intelligence operations. Here, the capability to spatially constrain searches and prioritise resources by triaging areas as low and high interest is advantageous. Conducted between 2017 and 2021, a forensically relevant topsoil survey (0-5 cm depth; 1 sample per 1 km2) has been carried out over Canberra, Australia, with the aims of documenting the distribution of chemical elements in an urban/suburban environment, and of acting as a testbed for investigating various aspects of forensic soil provenancing. Geochemical data from X-Ray Fluorescence (XRF; for total major oxides) and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS; for trace elements) following a total digestion (HF + HNO3) were obtained from the survey’s 685 topsoil samples (plus 138 additional quality control samples and six “Blind” simulated evidentiary samples). Using those “Blind” samples, we document a likelihood ratio approach where for each grid cell the analytical similarity between the grid cell and evidentiary sample is attributed from a measure of overlap between both Cauchy distributions, including appropriate uncertainties. Unlike existing methods that base inclusion/exclusion on an arbitrary threshold (e.g., ± three standard deviations), our approach is free from strict binary or Boolean thresholds, providing an unconstrained gradual transition dictated by the analytical similarity. Using this provenancing model, we present and evaluate a new method for upscaling from a fine (25 m x 25 m) interpolated grid to a more appropriate coarser (500 m x 500 m) grid, in addition to an objective method using Random Match Probabilities for ranking individual variables to be used for provenancing prior to receiving evidentiary material. Our results show this collective procedure generates more consistent and robust provenance maps between two different interpolation algorithms (e.g., inverse distance weighting, and natural neighbour), grid placements (e.g., grid shifts to the north or east) and theoretical users (e.g., different computer systems, or forensic geoscientists).</div>
<b>Citation:</b> Michael G. Aberle, Patrice de Caritat, James Robertson, Jurian A. Hoogewerff, A robust interpolation-based method for forensic soil provenancing: A Bayesian likelihood ratio approach,<i> Forensic Science International</i>, Volume 353, 2023, 111883, ISSN 0379-0738.
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Identification info
- Date (Creation)
- 2022-12-14T07:00:00
- Date (Publication)
- 2023-12-13T04:22:38
- Citation identifier
- Geoscience Australia Persistent Identifier/https://pid.geoscience.gov.au/dataset/ga/147584
- Cited responsible party
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Role Organisation / Individual Name Details Author Aberle, M.G.
External Contact Author de Caritat, P.
Internal Contact Author Robertson, J.
Internal Contact Author Hoogewerff, J.A.
External Contact Publisher Elsevier B.V.
External Contact
- Name
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Forensic Science International
- Issue identification
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Volume 353, December 2023, 111883
- Purpose
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Manuscript for external journal publication
- Status
- Completed
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Role Organisation / Individual Name Details Resource provider Minerals, Energy and Groundwater Division
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))
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Product data repository: Various Formats
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Data Store directory containing the digital product files
Data Store directory containing one or more files, possibly in a variety of formats, accessible to Geoscience Australia staff only for internal purposes
- Keywords
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Soil forensics
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- Keywords
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provenancing
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- Keywords
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forensic science
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- Keywords
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likelihood ratio
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- Keywords
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interpolation
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- theme.ANZRC Fields of Research.rdf
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Soil chemistry and soil carbon sequestration (excl. carbon sequestration science)
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Inorganic geochemistry
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Urban geography
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Published_External
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Australian Government Security Classification System
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- 2018-11-01T00:00:00
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Australian Government Security Classification System
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- Had derivation
- Title
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Australian Capital Territory Geochemical Urban Mapping (ACTGUM): Project Manual 1 – Sample Collection, Preparation and Total Element Content Analysis
- Citation identifier
- 145442
- Citation identifier
- cdbde51b-7027-4e70-ae15-2bee4799b6a1
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Australian Capital Territory Geochemical Urban Mapping (ACTGUM): Atlas Release 1 – Total Element Content, Data Quality Assessment and Geochemical Atlas. Volume 1 of 2
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- Citation identifier
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- Association Type
- Had derivation
- Title
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Australian Capital Territory Geochemical Urban Mapping (ACTGUM): Atlas Release 1 – Total Element Content, Data Quality Assessment and Geochemical Atlas. Volume 2 of 2
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Role Organisation / Individual Name Details Distributor Commonwealth of Australia (Geoscience Australia)
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<div>Derivative product from secondment to the Australian Federal Police by Patrice de Caritat in 2017-2018</div>
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- Title
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Australian Government Security Classification System
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- 2018-11-01T00:00:00
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urn:uuid/1ea25b8b-3a42-463e-b114-75062496d1bf
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Geoscience Australia - short identifier for metadata record with
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- Date info (Creation)
- 2023-12-13T04:12:53
- Date info (Revision)
- 2023-12-13T04:12:53
Metadata standard
- Title
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AU/NZS ISO 19115-1:2014
Metadata standard
- Title
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ISO 19115-1:2014
Metadata standard
- Title
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ISO 19115-3
- Title
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Geoscience Australia Community Metadata Profile of ISO 19115-1:2014
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Version 2.0, September 2018
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- http://pid.geoscience.gov.au/dataset/ga/122551