Submarine landslides can be far larger than terrestrial landslides, and many generate destructive tsunamis. The Storegga Slide offshore Norway covers an area larger than Scotland and contains enough sediment to cover all of Scotland to a depth of 80 m. This huge slide occurred 8,200 years ago and extends for 800 km down slope. It produced a tsunami with a run up >20 m around the Norwegian Sea and 3-8 m on the Scottish mainland. The UK faces few other natural hazards that could cause damage on the scale of a repeat of the Storegga Slide tsunami. The Storegga Slide is not the only huge submarine slide in the Norwegian Sea. Published data suggest that there have been at least six such slides in the last 20,000 years. For instance, the Traenadjupet Slide occurred 4,000 years ago and involved ~900 km3 of sediment. Based on a recurrence interval of 4,000 years (2 events in the last 8,000 years, or 6 events in 20,000 years), there is a 5% probability of a major submarine slide, and possible tsunami, occurring in the next 200 years. Sedimentary deposits in Shetland dated at 1500 and 5500 years, in addition to the 8200 year Storegga deposit, are thought to indicate tsunami impacts and provide evidence that the Arctic tsunami hazard is still poorly understood. Given the potential impact of tsunamis generated by Arctic landslides, we need a rigorous assessment of the hazard they pose to the UK over the next 100-200 years, their potential cost to society, degree to which existing sea defences protect the UK, and how tsunami hazards could be incorporated into multi-hazard flood risk management. This project is timely because rapid climatic change in the Arctic could increase the risk posed by landslide-tsunamis. Crustal rebound associated with future ice melting may produce larger and more frequent earthquakes, such as probably triggered the Storegga Slide 8200 years ago. The Arctic is also predicted to undergo particularly rapid warming in the next few decades that could lead to dissociation of gas hydrates (ice-like compounds of methane and water) in marine sediments, weakening the sediment and potentially increasing the landsliding risk. Our objectives will be achieved through an integrated series of work blocks that examine the frequency of landslides in the Norwegian Sea preserved in the recent geological record, associated tsunami deposits in Shetland, future trends in frequency and size of earthquakes due to ice melting, slope stability and tsunami generation by landslides, tsunami inundation of the UK and potential societal costs. This forms a work flow that starts with observations of past landslides and evolves through modelling of their consequences to predicting and costing the consequences of potential future landslides and associated tsunamis. Particular attention will be paid to societal impacts and mitigation strategies, including examination of the effectiveness of current sea defences. This will be achieved through engagement of stakeholders from the start of the project, including government agencies that manage UK flood risk, international bodies responsible for tsunami warning systems, and the re-insurance sector. The main deliverables will be: (i) better understanding of frequency of past Arctic landslides and resulting tsunami impact on the UK (ii) improved models for submarine landslides and associated tsunamis that help to understand why certain landslides cause tsunamis, and others don't. (iii) a single modelling strategy that starts with a coupled landslide-tsunami source, tracks propagation of the tsunami across the Norwegian Sea, and ends with inundation of the UK coast. Tsunami sources of various sizes and origins will be tested (iv) a detailed evaluation of the consequences and societal cost to the UK of tsunami flooding , including the effectiveness of existing flood defences (v) an assessment of how climate change may alter landslide frequency and thus tsunami risk to the UK.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Colour Imaging is part of every day life. Whether we watch TV, browse content on our tablets or phones or use apps and software in our work the content we see on our screens is the result of decades of colour & imaging research. In the future, the challenge is to understand more about the content images. As an example, in autonomous driving we wish to build a platform that sees the road independent of the atmospheric conditions, we don't want to crash when we are driving in fog. It is well known that an image that records the near-infrared signal is much sharper (compared to RGB) in foggy conditions. What is near infrared? The visible spectrum has a natural rainbow order: Violet, Indigo, Blue, Green, Yellow Orange and Red. Infrared is the 'next colour' after red that we can't quite see. Image fusion can be used to map the RGB+NIR signal to a fused RGB counterpart, that we can see. Through image fusion the same detail will be present in foggy or non-foggy conditions. Advantageously, Image Fusion is a tool that will allow non visible information to be incorporated and deployed in existing RGB-based AI scene interpretation systems with minimal retraining. Our project begins with the Spectral Edge Image fusion method, the current leading technique. This method - and most image fusion algorithms - works by combining edges from the 4 images (RGB+NIR) to make a fused RGB-only 3-channel edge map. The edges are then transformed (the technical term is reintegrated) back to form a colour image. Unfortunately, and necessarily, the reintegrated images often have defects such as bright halos round edges or smearing. We argue that the defects are a direct consequence of how 'edges' are defined. In our research we will - based on a surprising mathematical insight - develop a new definition of edge, quite a bold thing to do after 50 years of image processing research! By construction the reintegrated new edges will have much less halo and smearing artefacts. We will then use our improved edge representation and improved image fusion algorithm to make better looking images. These might be the fused images themselves: wouldn't it be great to have smart binoculars that allow us to see more detail in images when it is rainy or a landscape that is blurred by distance. However, we also believe the future of photography, in general, is content-based and that image fusion will help us determine the content in an image. As an example, when we take a picture at sunset, the shadows in the scene are very blue. But, outside of the shadow the light is very warm (orangish). The best image reproductions for these scenes involves manually and differentially processing shadow and non shadow regions. Here, we seek to find the illumination content in image automatically. Then in a second step we will develop a new content-based framework for manipulating images so that, for this sunset example, we don't need to edit the photos ourselves. In complementary work, we are also interested in helping people see better. Indeed, there is a lot of research that demonstrates that coloured filters can help mitigate visual stress. Coloured filters are used in Dyslexia (sometimes leading to dramatic improvements in reading speed) and there is now blue absorbing glass which will reduces the blue light coming from a tablet display (since blue light at night tends to keep you awake). Much of the prior art in this area is 'direct'. We find a filter to directly impact on how we see (simply, if we put a yellow filter in front of the eye then everything looks more yellow). Our idea is to deign filters that are related to the tasks we need to solve. For the problem of matching colours we will design filters so that if you suffer from colour-blindness you will be able to colour match as if you had normal colour vision. We will also develop indirect solutions for the 'blue light' problem and visual stress.

Increasing concerns over the environmental impact of plastic single-use packaging have reached a critical juncture. Mumbai-one the largest cities in India-implemented a ban on single-use plastic bags, plastic cups and plastic bottles, with a stiff penalty (5000 rupees) or up to three months in jail for those vendors caught selling these products (Dhillon, 2018). From a corporate initiative, IKEA, has recently adopted biodegradable packaging made from mycelium (mushroom), which mimics the texture of polystyrene (Lempert, 2018). With growing awareness of the negative environmental impacts of petroleum-based packaging, the trend towards adopting bio-based products has increased. Currently, the highest demand for bio-based packaging is situated within the food industry. In a recent meeting of the World Economic Forum, it is claimed that biodegradable packaging is good for the economy and the environment. However, while bio-based packaging may be seen as a "disruptive innovation", there is a lack of studies exploring the social and environmental implications of this product. For example, bioplastic packaging is hard to distinguish from its plastic counterpart, resulting in contamination and waste management issues at a municipal level (UNEP, 2015). As such, the adoption of this product becomes a "wicked problem" as it is seemingly impossible to solve due to the numerous interdependent factors that simultaneously impact solutions. To address this issue, four research partners consisting of the UK, Canada, Brazil and Poland, will implement four collaborative social innovation labs. A social innovation methodology is critical to better understand how bio-based packaging innovation will impact the environment and diverse stakeholders across the supply chain, especially as it relates to food security, waste infrastructure, formal and informal waste collectors, consumers, vendors, food producers, and policymakers.

As people across the world live longer, there is a growing need to support active ageing so that the extra years of life can be lived as well as possible. The potential of technology to assist people in all aspects of their lives is increasingly being recognised. Ambient Assistive Living (AAL) technologies refer to items that people can use in their everyday lives to make life easier and help them manage their daily activities. To enable the maximum number of people to benefit from current and future AAL technologies requires not only a good understanding of the needs of older adults but also a comprehensive analysis of how they view technology, their attitudes towards using it and how they make decisions about purchasing and using technology. Social and cultural factors can influence these issues and so this project aims to work with older adults across three different countries to explore their needs, attitudes and behaviour towards novel technologies. The project team brings together experts in gerontology, engineering, occupational therapy and psychology from the UK, Canada and Sweden to work with older adults to address their current and future needs for technology to support them to live their lives as well as possible. The project comprises several complementary elements that will be carried out in parallel within the three countries. The first element is a user needs analysis to examine the older adults' requirements in relation to AAL technologies, including those people who need support with cognitive activities, physical activities or motor activities. The findings from this stage will determine the development of novel AAL technologies in the next stage to address various aspects of daily life, such as shopping or cooking, supporting people with activities they need to remember, such as taking medication and keeping in touch with people. These novel technologies will be piloted with older adults in each of the three countries to examine how they respond to and explore them to inform future developments. Additionally, we will look at how to support people to learn to use new technologies and incorporate them into their lives to help them live as well as possible.