This research project will see Dr Casaseca leading a strategic partnership with Zhejiang University, one of the top five universities in China. It comes in response to the fact that the incidence of flood events in the UK and globally has increased as a consequence of climate change. Flood events cause serious disruption, enormous financial costs and, in some cases, loss of life.
This two year research project will see the collaborative research team develop efficient Unmanned Aerial Vehicle-based hyperspectral imaging technology for automatic flood monitoring and prevention. Images will be collected across a number of adjacent wavelength bands and automatically processed to maximise the amount of meaningful information for efficient flood management.
The development of this flood response system could have massive benefits not just for society, but also the wider economy, by improving the response rate to floods and in turn significantly reducing the devastating impact floods can have.
This project aims to develop advanced image processing techniques to automatically monitor water level changes using hyperspectral data; propose new strategies for efficient acquisition and management of hyperspectral data; calculate a possible and admissible path for each Unmanned Aerial Vehicle (UAV) to sample the sensing field in an efficient manner so that redundant sensing can be avoided; and define new protocols and communication systems for efficient transmission of hyperspectral image data.
Such a system will improve disaster management planning and deployment with increasing efficiency and decreasing costs. the envisaged strategy imposes a challenging scenario in which hyperspectral data will be efficiently acquired, transmitted, and accurately processed.
Dr Casaseca said: “I am delighted to have been awarded a Royal Society of Edinburgh-National Science Foundation of China Joint Project Grant to undertake this research with colleagues at Zhejiang University. They will complement our multidisciplinary team here at UWS involving colleagues from the University’s Artificial Intelligence, Visual Communications, and Networking Research Centre, and the Institute of Thin Films, Sensors & Imaging.
“This project, which will bring together a unique team composed of Chinese and UK experts, will explore a new strategy for water level monitoring and flood prediction based on automatic analysis of hyperspectral images acquired from UAVs. Such a system will improve disaster management planning and deployment with increasing efficiency and decreasing costs.”
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