In response to the United Kingdom’s housing pressures, the requirement for a low cost, alternative housing scheme with sustainability as a core value has never been greater. The University of Brighton’s BrightNest project was designed to these meet these requirements. It’s recycled shipping container structure, coupled with a self-sustaining solar power design, allows for fast construction upon the rooftops of Brighton. With BrightNests proof of design nearing; the next big question for the project is its application potential. Analysis of physical and social criteria central to the success of the project would quantify BrightNest’s development potential within Brighton. This will be achieved through a two phased methodology; firstly, remotely sensed LIDAR and photogrammetry datasets will be used to determine rooftops with the physical capacity for BrightNest construction. These identified sites were then ranked against 6 criteria in the second Phase of assessment, allowing the most favourable sites for BrightNest development to be determined. Phase One of the project identified 255 separate rooftops with an area suitable for development. In Phase Two these sites scored relatively well, with a positively skewed distribution and 8 sites classified within the highest suitability grouping. Upon assessment of these results, it was apparent that the modelling methodology employed was liable to processing based errors which had a notable impact upon site identification. A Sensitivity Analysis also determined that the site rankings were stable under input parameter adjustment, acting to reassure future developments to the BrightNest project. This project acts as a high-level initial investigation to the potential of the BrightNest project, whilst project feasibility was demonstrated, further detailed assessments would be required by specialists within urban planning and design. The application of this methodology to the BrightNest project has also facilitated an important contribution to the literature, with no previous work applying Multi Criteria Decision Making processes to urban airspace development.
Date of Award | 1 Feb 2020 |
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Original language | English |
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Awarding Institution | |
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Supervisor | Matthew Brolly (Supervisor) |
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- LIDAR
- Rooftop development
- Site Analysis
A Multi-Criteria Decision Making Framework for Airspace Development opportunities: The BrightNest Project
Williams, M. (Author). 1 Feb 2020
Student thesis: Master's Thesis