ETD Collection

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Author: search.filters.author.Hunt, Hugh Gordon Patrick

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    A Bayesian framework for forensic investigations involving lighting location system data
    (2018) Hunt, Hugh Gordon Patrick
    The work presented in this thesis extends and contributes to research into the forensic use of Lightning Location Systems and the uncertainty present due to location errors. While previous work in this area has produced some approaches that can be used in forensic investigations, there has not been a consistent, standardised approach to presenting Lightning Location System stroke reports as evidence in a legal environment. In the research presented, a Bayesian framework for representing Lightning Location System data as likelihood ratios and posterior probabilities is developed. The statistical models necessary for use of the framework are discussed and verified through groundtruth events and bivariate statistical analysis. Photographs of multiple lightning events to the Brixton tower in South Africa and current measurements at the Gaisberg tower in Austria are used as ground-truth data and bivariate statistical techniques are used to fit and evaluate different statistical models. It is shown that the bivariate Students’ t-distribution is the best fit for Lightning Location System location errors, rather that the commonly assumed bivariate Gaussian distribution and that a bivariate Gaussian Mixture Model can be used to describe the prior probability of lightning occurrence in a region. It is demonstrated how the Bayesian framework can be used to present Lightning Location System data as evidence in a court of law. This represents a unique and valuable contribution to those working in the field of lightning location and, in particular, in forensic situations.
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    A methodology for matching lightning detection network data with ground-truth records
    (2012-07-19) Hunt, Hugh Gordon Patrick
    In this dissertation a methodology of matching external ground-truth records of lightning events with data reported by a Lightning Detection Network (LDN) is investigated. The methodology allows for matching events where the time of the ground-truth record is unknown. It is shown that the location accuracy of an LDN is a ected by the number of sensors that are able to detect lightning strokes and this observation is then used to de ne criteria for matching lightning strokes with LDN data. An evaluation of the methodology is presented in which the results of applying the methodology are compared with the results of a known methodology (time correlation) to determine if the same data is extracted. Photographs of lightning attachment to the Brixton tower in Johannesburg, South Africa are used as ground- truth events and LDN data is obtained from the South African Lightning Detection Network (SALDN). A practical application, in the context of an insurance claim scenario, is also presented in which the methodology is used to determine whether lightning is the cause of damage to a tree and when this may have occurred. It is found that the methodology extracts many of the possible strokes but that it also returns false positive results and makes some false exclusions. It is concluded that the proposed methodology should be used as a \ lter" to reduce a dataset of LDN records but that corroborating evidence is required if the methodology is to be used as intended.