complexurban /

Complexity, Planning & Urbanism

New MArch Atelier at the Manchester School of Architecture: Developing new theoretical approaches & computational tools using a complexity science framework (systems, self-organisation, emergence, intelligence, structural change, adaptation) for the design, management, governance and understanding of future cities related to climate change, citizen participation, development strategies, resilient interventions, policy making, urban morphology and capacity management.

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Linking Between Observational Scale & Surveyed Datasets


Determining relationships between a human scale observation (building use) and large scale datasets (national survey at ward level) provides the possibility of a new relational dataset which can be studied over time and involve back-casting for historic trends. In a complex self-organising system there are many interlocking positive and negative feedback loops. This means that behaviours on one side are amplified while behaviours on another side are suppressed. Extrapolating likely future scenarios that can emerge from external stimuli can be invaluable to both stakeholders and government.

Manchester School of Architecture. MArch Program. CPU (Complexity Planning & Urbanism)

Students: Solon Solomou, Odun Oredein

Supervisors: Ulysses Sengupta, Rob Hyde, Deljana Iossifova, Eric Cheung

14 October 2015
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