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Estimating the height of buildings and vegetation in single aerial images is a challenging 12 problem. A task-focused Deep Learning (DL) model which combines architectural features from 13 successful DL models (U-NET and Residual Networks) and learns the mapping from single aerial 14 imagery to a normalized Digital Surface Model (nDSM) is proposed. The model is trained on aerial 15 images whose corresponding DSM and Digital Terrain Maps (DTM) are available and is then used 16 to infer the nDSM of images with no elevation information. The model is evaluated with a dataset 17 covering a large area of Manchester, UK, as well as the 2018 IEEE GRSS Data Fusion Contest LiDAR 18 dataset. The results suggest that the proposed DL architecture is suitable for the task and surpasses 19 other state-of-the-art DL approaches by a large margin. ; This work has been partly supported by the project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 739578 (RISE – Call: H2020-WIDESPREAD-01-2016-2017-TeamingPhase2) and the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy.

Blockchain is an emerging digital technology allowing ubiquitous financial transactions among distributed untrusted parties, without the need of intermediaries such as banks. This chapter examines the impact of blockchain technology in agriculture and food supply chain, presents existing ongoing projects and initiatives, and discusses overall implications, challenges and potential, with a critical view over the maturity of these projects. Our findings indicate that blockchain is a promising technology towards a transparent supply chain of food, with many ongoing initiatives in various food products and food-related issues, but many barriers and challenges still exist, which hinder its wider popularity among farmers and systems. These challenges involve technical aspects, education, policies and regulatory frameworks. ; This work has been partly supported by the project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 739578 (RISE – Call: H2020-WIDESPREAD-01-2016-2017-TeamingPhase2) and the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy.

This paper uses the twin metaphors of 'gatekeeper' and 'gateway constructor' as devices to explore the role of Credit Rating Agencies (CRAs) as intermediaries between global corporate finance and specific institutions – housing associations in England. The analysis utilises a financialisation framing, whereby the practices, logics and measurements of finance capital, increasingly permeate government, institutional and household behaviour and discourse. This paper examines how housing associations have increasingly resorted to corporate bond finance, partly in response to reductions in government funding, and in the process engaged with CRAs. Surprisingly little research has been undertaken on the role and function of CRAs, and their impact on the organisations they rate. The case of housing associations (HAs) is of particular interest, given their historical social mission to build and manage properties to meet housing need, rather than operate as commercial private landlords conversant with market-based rationales. A case study of the large London-based HAs draws on a narrative and financial analysis of annual reports, supplemented by semi-structured interviews with senior HA finance officers to explore how CRA methodologies have been internalised and have contributed to changes in strategic and operational activities. We conclude that CRAs act both as a gatekeeper to the financial markets but also as a gateway constructor for the financial markets to enter new arenas, such as the HA sector. This dual nature of CRAs is intended as our contribution to emerging debates about the nature, the practice and the impact of financialisation on public services.

The term 'Generation Rent' has gained currency in recent years to reflect the fact that more 25 to 34 year olds in Britain now live in rented accommodation rather than owner-occupation. The term also conveys the extent to which age-related divisions in the housing market are becoming as significant as longer standing tenure divisions. However, this portmanteau term covers a wide array of different housing circumstances - from students, young professionals and transient households to the working and non-working poor. This paper focuses on the position of a specific category of this age cohort - those 25 to 34 year olds living in self-contained accommodation in the private rented sector who are in receipt of Housing Benefit. On the basis of survey evidence and qualitative interviews with landlords and housing advisers, the paper considers how the marginal economic and housing market position of this age group is being reinforced by the stigmatising attitudes of landlords which formerly applied to tenants in their late teens and early 20s and are now being extended further along the age band. The paper suggests that the use of a 'housing pathways' approach to signify the housing transitions of young adults needs to be revisited, to give greater weight to collective and creative responses to constraints in the housing market and to recognise the key role played by gatekeepers such as landlords in stigmatising groups according to assumed age-related attributes.