Human observers move their eyes in order to direct their attention to important aspects of a visual scene. There are models called salience maps; they predict where the eyes will move to when looking at a scene. At present, these models do not deal with video input, nor do they predict how an observer's task will affect where they look. In other words, there are no models for real-life viewing situations, where an observer has a specific task.We are proposing a new approach to this problem. We have access to video information from cameras used in urban surveillance, and to the operators whose job it is to spot abnormal behaviour in such video inputs. We shall obtain (previously unseen) video recordings of events in UK urban streets, and display them in a simulated control room to operators familiar with the town in question. We shall monitor where they look on the bank of video screens, and also when they decide that an event is abnormal and/or requires some form of intervention, e.g. calling the police. We shall use the record of eye fixations to teach a computer system to distinguish between normal and abnormal events. In this way, we shall be able to learn what is important for humans to do such surveillance by observing their eye fixation behaviour, for a realistic (and difficult) task and set of real-life video sequences. The project is important for four reasons. First, this will be the first attempt to develop a model of human attention/eye movements which will be firmly based on realistic video input and a real task. Second, this will be the first time that a computer system is able to learn from human behaviour in this way. Third, we will learn much about the ability of trained observers to cope with a demanding task as the number of TV monitors increases. Finally, we will develop an automated system which will be able to analyse the input from any urban CCTV camera in order to alert operators to look at that video stream - at present, most CCTV video streams are not observed by anyone since there are too many cameras for the number of human observers. Therefore, an automated alerting system is greatly neeeded and this project constitutes the best attempt to date to produce one.

Greater Manchester (GM), far from being a historically unified whole, is made up of ten boroughs, each with its own unique character. The Manchester Voices project investigates the ways in which people in the city-region position themselves locally, regionally and nationally, and the role of language in enacting social and regional identities. The project is structurally organised around three core strands: language use, language attitudes, and regional and social identities. It addresses a number of issues relating to the academic and non-academic treatment of regional and social varieties of language in the UK, and the role of such language varieties in the construction of identity: 1. Lack of detailed linguistic descriptions of regional variation across GM. Previous research has tended to view 'Manchester English' as a monolithic entity or has focused on specific areas within GM, thus not acknowledging the wide linguistic variation that exists. This project provides a rich and full description of language use across the region's ten boroughs, thus ensuring an accurate contemporary record of developing and changing regional varieties of language. 2. Societal and institutional disregard for regional accents and dialects. 'Regional' language varieties are often perceived in a negative way, with speakers being stigmatised. This project explores and challenges those perceptions by promoting and celebrating the linguistic and cultural heritage of GM, thereby advancing our understanding of the social, cultural, and historical factors that continue to shape the language, places, and people of the region. 3. Lack of attention to attitudes as factors mediating the relationship between language and identity. By exploring people's feelings towards their own speech and towards that of others, the project seeks to uncover deeply embedded and widely held beliefs regarding the status and value of regional accents and dialects. This attitudinal data will serve to challenge perceptions of regional accents and dialects and to promote linguistic equality and diversity as a means of nurturing a sense of social and regional pride. 4. Lack of sociolinguistic insight into existing cultural, historical, and literary resources relating to regional identity. GM, like many regions across the UK, has a wealth of resources relating to past and present society, much of which is collected by Manchester Libraries. However, the extent to which this material has been explored from a sociolinguistic perspective is minimal, despite language being at the heart of the available resources. By partnering with librarians, poets, literary specialists and cultural historians, the project will reach a fuller understanding of the linguistic context, contributing to a fuller understanding of the historical and literary landscape of GM. 5. Lack of community access and engagement in sociolinguistic research. Sociolinguistic data tends to be collected during pre-arranged meetings in neutral locations and formal contexts. To counter this, we will take our research into the community in the form of a mobile interview booth, allowing us to access groups who might otherwise be unaware of, or unwilling to be involved in, the project. In addition to majority populations, we will seek the voices of specific groups, such as young people and GM's multilingual/multicultural communities. The primary spoken data will be collected in the Accent Van, which will travel the ten boroughs of GM gathering speech and insights from people across the region. In addition, creative poetry and history workshops will gather further data and explore themes around regional identities. Dialect maps will be collected online, and attitude tests will take place online and at the University. Finally, existing audio recordings being digitised as part of the Save Our Sounds project will be housed with our data in a Voices resource area at Manchester Central Library.

The public realm is a place where urban stakeholders interact and sometimes come into conflict. Symptoms such as traffic congestion, street safety and air pollution are difficult to tackle, as they involve multiple stakeholders. Planning and implementation to improve public space can be enhanced through co-creation, but examples of co-creation approaches and tools that overarch the full planning cycle are rare. The aim of the LOOPER is to build a participatory co-creation methodology and platform, to demonstrate 'learning loops' i.e. new ways of decision-making which bring together citizens, stakeholders and policy-makers to iteratively learn how to address urban challenges. A typical loop starts with debate on topical issues, then frames the problem and collects data using participatory sensing. The platform then visualizes the data, and enables the co-design and evaluation of solutions. The selected solutions are then implemented, and the results are monitored with a second loop learning from the first. LOOPER will produce a prototype platform with demonstrations in three Urban Living Labs with different spatial, cultural and thematic contexts: traffic calming and pedestrianisation in Brussels; street safety and security in Manchester; environmental pollution in Verona. It will also provide guidance, available for to enable any city to improve its decision-making.

Numerous research studies use commuting data, collected through the Census of Population, to understand social, economic and environmental challenges in the UK. This commuting data has been used to understand patterns; answer questions regarding the relationship between housing and labour markets; and to see if travel behaviour is becoming more or less sustainable over time. However, there is lots of untapped potential for such data to be used to evaluate transport policy and investment decisions so resources are more effectively and efficiently targeted to places of need. In applied public policy a major shortcoming has been a lack of use of this data to support investment in transport which has major implications for economic growth. If transport investments are inefficiently targeted, this restricts the capacity of places to grow economies to their full potential. This wastes their resources by over investing in transport capacity in areas where it is not needed. Equally, it has long been argued that efficient investment in transport is crucial if labour market exclusion, particularly the case of deprived communities, is to be tackled. The aim of the research is to inform community transportation policy and investment and the socio-spatial dimensions of travel to work flows over time (2001-2011). Our research develops a toolkit to help decision-makers better target investment in transport capacity and infrastructure. The toolkit includes a series of new classifications of commuting flows from the 2001 and 2011 Censuses. It will include a classification of newly developed official Workplace Zones for England to complement official residential population-based classifications alongside various population, deprivation, investment and infrastructure data. The toolkit will bring these classifications and datasets together online through various mapping and analysis tools to understand the dynamics of commuting between different types of residential and workplace locations over time and combine these datasets and analyses with locally-specific transport investment data. The methodology developed will be applied to England as a whole but we will use the Manchester as a test-case for our analysis and for development of the toolkit. The use of open source approaches to build the toolkit means that other locations will have the framework to develop their own toolkit. The flow and area-based (Workplace Zones) classifications for England will complement official ONS residential-based output area classification and existing indices of deprivation. This will be mapped in relation to key transport investments made in Manchester, using local administrative data and overlay these with the results of commuting analysis to support decision-making regarding future targeted public transport infrastructure investment. The toolkit will be interactive so users can pose policy questions to explore commuting relationships between different places. The strength of this approach is that it will enable policy and decision-makers to test various scenarios for future transport investment depending on problems they have posed. In a hypothetical situation, a policymaker in might ask the question of whether a specific deprived community in their city is more or less connected into a major employment centre than another equally deprived community. The evidence can be used to target funding for an 'into-work-scheme' to help the most disconnected community. The toolkit allows the policymaker to explore levels of commuting and compare the level of connectivity of each neighbourhood to major employment centres. The underlying rationale for the research is that the toolkit will help deliver efficiencies in public and private sector investment. This is crucial at a time when the government is promoting the need for smarter economic growth but doing so in a challenging context in which public sector resources are scarce and the private sector is risk averse.

RELEVANCE & SCIENTIFIC VALUE Green roofs can provide important ecosystem services within the urban environment from biodiversity, climate change adaptation, air quality management, environmental performance of buildings, aesthetic/recreational value, to economic value through local food growing and public health benefits. In spite of this there is currently a lack of formalised guidance or policy provision, particularly in the UK, due in part to the lack of scientific research which attempts to explicitly quantify the environmental benefits of green roofs. Green roof installation can form part of a wider strategy towards achieving National Indicator performance targets, in addition to complementing ongoing priorities for the region, such as the Manchester Climate Change and Biodiversity Strategies and the GM Air Quality Action Plan, and this has provided the motivation for Manchester City Council (MCC) to fund the CASE element of the studentship. Key issues are what role do green roofs play in climate change adaptation? What is a best practice green roof for the Greater Manchester region (size, type of vegetation)? What are the longer term implications of green roof installation (e.g. level of maintenance required, performance under future climate scenarios)? AIM The project aim is to quantitatively establish the role of green roofs in improving the local environment using the case study area of Greater Manchester. The specific emphasis of the project will be on climate feedbacks which affect the role of green roofs as a mechanism for delivering climate change adaptation. The work will also have relevance for a fuller assessment of ecosystem services building on existing and proposed work by MCC and the University of Manchester. The research will use a combination of experimental monitoring and climate modelling to assess the environmental performance of green roofs, which offers a stimulating and feasible PhD topic. RESEARCH QUESTIONS 1. What is the local context in terms of biodiversity, flood risk, temperature, air quality, under current and future climate conditions? 2. How can green roofs be classified? 3. How can green roofs be monitored and what type of quantitative index is appropriate for describing the environmental implications of green roofs? 4. What climate change adaptation role could green roofs play, under current and future climate conditions? 5. Does the size and type of green roof effect the capacity of the green roof for climate change adaptation? 6. What are the environmental barriers to implementation and limitations for green roof performance (e.g. drought limiting the cooling benefits of green roofs)? 7. What is a 'best practice' green roof for the local context? BENEFITS OF THE COLLABORATION MCC will benefit from scientific supporting evidence to promote green roofs in the region. The studentship will assess feasibility for green roof development in the region and provide best practice guidelines for green roofs in Manchester. For the student, the policy-relevance of their work will be implicit. MCC will provide expertise in biodiversity in the region, access to key databases and contacts at the Green Roof Centre in Sheffield, and excellent opportunities for knowledge transfer through the Green Roof Guidance Document and training events (run jointly with Red Rose Forest). The studentship will further strengthen existing links between the University and the council, which were established through the EPSRC ASCCUE and SCORCHIO projects. EQUIPMENT Equipment provision will be via related research projects at the University. Available equipment includes: Rotronics Air Temperature & RH sensors, Gill Sonic Anemometer for windspeed and direction, Delta-T BF3 Radiation and Sunshine Sensor, tipping rain gauge, Vaisala portable weather station, soil moisture theta probe. The student will also have access to appropriate software such as ArcGIS, MapInfo, Mathematica and MATLAB.