Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.696165
Title: Investigating the use of radiometric data in the estimation of peat thickness
Author: Robinson, Martin Charles
ISNI:       0000 0004 5992 6879
Awarding Body: Queen's University Belfast
Current Institution: Queen's University Belfast
Date of Award: 2015
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Abstract:
The aim of this thesis is to investigate the use of Tellus airborne radiometric data in the development of peat thickness models for Northern Ireland. This involved exploring the complex relationships between peat and radiometric levels as well as optimising the modelling of peat and Tellus datasets. Laboratory and field-based experiments were utilised to determine how radiometric values are affected by changes in peat thickness, moisture content and bulk density. The laboratory results indicated an inverse exponential relationship between peat thickness and radiometric values, a general inverse relationship between peat moisture content and radiation levels and no clear relationship between bulk density and radiometric values. The field-based peat thickness experiment, devised to investigate how an active peat bog attenuates radiation, indicated an inverse relationship between the variables. Historical peat thickness measurements, digitised and collated to produce a peat thickness dataset for Northern Ireland, were used, in conjunction with other data, to determine suitable sites for analysis. At each field site, the relationship between peat thickness and radiometric levels was analysed using not only historical peat thickness and Tellus measurements but also newly acquired ground-penetrating radar and ground-based gamma-ray spectrometry data. The analysis indicated that stronger relationships between datasets were observed when data from different sites were not amalgamated. Historical peat thickness and Tellus radiometric data maps were generated using two techniques: inverse distance weighting (IDW) and ordinary kriging (OK). In each case, OK outperformed IDW, with the optimum model being determined using error statistics.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.696165  DOI: Not available
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