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Publication Detail
The transfer and persistence of environmental trace indicators, and methods for digital data acquisition from photographs and micrographs: applications for forensic science research
  • Publication Type:
    Thesis/Dissertation
  • Authors:
    Levin E
  • Date awarded:
    2020
  • Pagination:
    1, 300
  • Supervisors:
    Morgan R,Jones V
  • Awarding institution:
    UCL (University College London)
  • Language:
    English
  • Keywords:
    environmental trace evidence, forensic science, image processing, quartz grains, diatoms
Abstract
Environmental forms of trace evidence (such as mineral grains, pollen grains, algae, and sediment) can offer valuable insights within forensic casework. An issue facing forensic science as a whole, and these environmental indicators specifically, is a relative dearth of empirical research which would underpin the interpretation of such indicators when attempting forensic reconstruction. This thesis aims to address this lacuna, undertaking experiments to: (1) Explore variables which affect the rates of transfer and persistence, with specific focus upon quartz grains (a terrestrial indicator) and diatom valves (an aquatic indicator) upon footwear materials (a substrate that has been under-represented in past studies); (2) Conduct research into the effects of particle size and morphology upon transfer and persistence; (3) Develop and adapt methodologies to undertake this research. Accordingly, the outputs of this thesis are: (1) The creation of new datasets which could inform the interpretation of these trace indicators within forensic investigations and crime reconstruction scenarios and (2) The development of novel methodologies which could be employed in future research to attempt to accelerate data collection and analysis, without compromising on accuracy. This research is interdisciplinary, combining theory from forensic science, analytical techniques from the environmental sciences, and some elements of image processing and analysis.This research was funded by the Engineering and Physical Sciences Research Council of the United Kingdom through the Security Science Doctoral Training Research Centre (UCL SECReT) based at University College London (EP/G037264/1).
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