Speaker
Description
The spatial distribution of naturally occurring radionuclides (⁴⁰K, ²³²Th, and ²³⁸U) at Sparkle Bay, Western Cape can be investigated with an integrated approach using UAV-based gamma-ray spectrometry, least-squares optimisation, and Geographic Information Systems (GIS). The airborne gamma-ray data were obtained with a sodium iodide (NaI(Tl)) detector attached to an unmanned aerial vehicle (UAV) and enabled fast and high-resolution radiometric surveying of the study area. The reference activity concentrations were obtained through laboratory-based gamma spectrometric analysis of representative granite and dolerite samples. A least-squares optimisation model was used to calibrate the airborne measurements with those obtained in laboratory settings by reducing the Total Sum of Squared Errors (TSSE). This decreased systematic bias and enhanced accuracy and reliability of the field-derived data. The idealised radionuclide concentrations were then analysed in a GIS process including spatial interpolation utilizing the Inverse Distance Weighting (IDW) procedure to obtain continuous distribution maps. The results show that the concentration of radionuclides is closely dependent on lithology, granitic formations show higher concentrations of potassium and thorium than dolerite formations. Uranium has wider spatial variability, which is consistent with its increased geochemical mobility. Optimisation was able to greatly boost agreement between field and laboratory datasets, improving spatial interpretation quality immensely. In this study, we confirm the effectiveness of the joint integration of UAV-based gamma-ray spectrometry, least-squares optimisation and GIS analysis in advancing radiometric mapping in complicated coastal domains and provide valuable baseline values to support environmental monitoring and geological study.
| Apply for student award at which level: | Honours |
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| Consent on use of personal information: Abstract Submission | Yes, I ACCEPT |