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PolyChora Alpha: a new digital interface for interdisciplinary city design - Dr Ying Jin

The aim of this project is to develop a new digital interface to integrate the data and visualisation of the designs of land use, buildings, transport infrastructure and associated urban services at both the neighbourhood and city scale. The interface can also be used to modify a range of aspects of such designs in the course of visualisations by non-specialists, with underlying building information data stored for feedback to the respective design teams. The focus of the work is the new method and tool for connecting digital data from multiple disciplines including architecture, city planning, transport planning, spatial economic studies and infrastructure investment.

[Final Report]

In the past decade, a variety of data analytics and modelling techniques have been implemented in the planning and design of housing, offices, retail, public spaces, business parks, factories, logistics premises, mixed use neighbourhoods, road and rail projects, traffic control and regulation, emergency responses to events, terror-attack and natural disasters, etc.  Each technique has been defined and applied with a specific disciplinary context.  While BIM and associated standards are being implemented within each of the business sectors and disciplines a new challenge is emerging regarding the lack of connections and interface between the datasets.  This has severely hampered the progress in co-design and coordination among the design disciplines, especially in fast growing cities where it is essential to join up the planning of business premises, housing and transport in the design of specific building or infrastructure. 

The Cities and Transport Research Group led by Ying Jin at the Martin Centre for Architectural and Urban Studies, Department of Architecture is leading the world in connecting data and modelling among economists, transport and traffic engineers, housing and neighbourhood planners, urban designers and infrastructure investors in their integrated computer models of cities.  Their models have been successfully applied around the world for predicting the joint effects of planning, design and infrastructure interventions.  Ying Jin is currently leading a three-year ‘Cambridge Futures 3’ modelling study funded by Cambridgeshire and Peterborough Combined Authority and Cambridge Ahead to design and examine alternative scenarios of workplaces, housing and transport to 2031 and 2051.  He is also an expert adviser for BSi and the International Organization for Standardization (ISO) for data standards including BIM at city scale.

In the existing models it requires specialist knowledge from each of the disciplines to specify and modify data inputs that represent alternative designs, and it is costly to produce 3D visualisation portraying the joined-up city design proposals.  This means that only experts can work with the models at present, whilst the non-specialists are forced to consider the models as black boxes.   Only on some rare occasions in the past (and with considerable expense) the model data was visualised in realistic 3D built form.  Such visualisation that exists had proven extremely effective in helping policy makers and the public understand and contribute.  However, so far there are no easy, repeatable methods and tools to achieve such visualisation or to record feedback during visualisation.      

Ying Image
Mapping of the Land Use Zone Classification based on National Travel Survey Data (Source: Jin et al, 2018)
In this project we have been able to develop a pre-general release, alpha version of the visualisation tool through integrating both (1) data for land use, transport and buildings at the site level) and (2) modelling and visualisation tools for land use, transport and buildings at the site level.  Its first applications in research on the Cambridge Futures 3 project and in MPhil teaching with a student project have proven to reduce the interaction time between the modelling specialists and non-specialists significantly, for data verification, validation, comprehension and scenario development.

In terms of policy impact the first results on the baseline scenarios have been used by the Cambridge and Peterborough Independent Economic Review (CPIER, 2018), with further outputs on radically different, alternative scenarios progressing in review pipeline.

[Final Report]

Researchers:


Department of Architecture

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