Harmful exposure to erythemally-effective solar ultraviolet radiation in the UVA and UVB categories pose high health risks to humans with skin based malignant keratinocyte cancers and eye-related diseases.
Near real-time simulations and smart forecasting of global solar ultraviolet index (UVI) using accurate predictive models is a promising tool to implement sun-protection behaviour to mitigate such health risks in both developed and remote locations. Thus, this PhD project investigates novel predictive techniques that employs sky image and cloud chromatic properties based deep learning and machine learning modelling systems to estimate and forecast global solar UVI for various locations in Australia. The study adopts seasonal based modelling of UVI for effective public health advocacy.
For more information, please contact the Graduate Research School.