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Re-Surge
Project details
Programme
Research Cluster
RC14
While connecting cities, regions, and even continents, large Infrastructural systems such as railway lines and highways divide neighbourhoods otherwise connected. This is one of the great paradoxes of contemporary cities around the globe: connection at the large-scale creates fragmentation at the community level. Re-Surge aims to tackle this growing concern around urban fragmentation caused by transportation infrastructure by exploring prototypical urban design strategies that can be implemented in multiple cities across the globe. In this context, the project aims to identify underlying patterns and interactions related to the cause and effect of the fragmentation in order to develop solutions through a structured computational approach driven by collecting, visualising, analysing, and simulating data. The project uses data and machine learning as the primary components informing the design process. Re-Surge aims to be a computational urban model that can be efficiently applied in analysing and designing urban areas affected by fragmentation.
01
Urban Fragmentation
Project Overview
Project Overview
146 Identified Fragments
A matrix illustrating 146 urban sites fragmented by infrastructure.
Impacts of Fragmentation
London Map of Impact
Various impacts resulting from transportation infrastructure are mapped across London.
Data Overlay and Site Identification
London data layers are overlaid (left), and the resultant kernel density values are mapped to identify a site for intervention (right).
02
Micro Analysis
Patch Dynamics
Data Gathering and Generation
Maps, models, and simulations are used to collect and generate data.
Data Re-Mapping
A visualisation illustrating how data is re-mapped on an area of the city.
Data Correlations
Through analysis, correlations are drawn between sites and datasets.
03
Data Re-Writing
The Data Re-Writing Process
The Data Re-Writing Process
Detail View of the Data Re-Writing Process
Re-Writing Data Spatially
Re-Writing Data Spatially
24 Iterations
04
Urban Glacier
Defragmentation Strategy
An illustration of the urban defragmentation strategy for a site in London.
Noise and Visibility Parameters
An illustration of digital analysis of noise and visibility parameters.
Urban Network Integration
Machine Learning Land Use Output
Various land uses are determined through machine learning and mapped on site.
Urban Element Generation
Visualisations of urban elements generated in Re-Surge.
05
Design Visuals
Site Plan
St. Pancras Connection
An aerial view of the design implementation at St. Pancras Station in London.
Arenas and Mixed-Use Buildings
An aerial view of the design implementation across public space.
An exterior view of the implemented design strategy.
An interior view of the implemented design strategy.
The Bartlett
B-Pro & Autumn Shows 2020
27 November – 11 December 2020
B-Pro & Autumn Shows 2020
Explore