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IsoChronic City

Project details

Programme

Cluster RC14

IsoChronic City is an urban response to the recent predicament of reurbanisation in the post-pandemic era. The project is based on the 15-minute neighbourhood concept, which is derived from historical ideas about proximity and walkability.

The project aims to increase the reach of a 15-minute city and bring amenities closer to residents. This is accomplished by utilising datasets interpreted by machine learning algorithms like principal component analysis, K-Means clustering and convolutional neural networks along with spatial computational methods to create an IsoChronic Generative Loop. The proposal consists of restructuring existing network centrality, fabricating responsive public spaces using topo-geometrical interventions and transforming unused open areas into interactive spaces with required amenities. The design alters physical aspects and spatial characteristics to achieve a sustainable, inclusive and accessible city.

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Project Overview

Project Background

Historical Background

Rapid urbanisation due to industrialisation led to an increase in urban populations. Due to the magnitude of population growth, lack of infrastructure and haphazard development, urbanisation became the cause of serious socioeconomic problems.

Formation and Selection of Spatial Signature

Spatial signatures are created based on parameters such as population density, landuse, accessibility, deprivation and connectivity. The dense urban signature is selected as it is predominantly residential in nature with access to jobs and services.

Urban Decay

Various layers of datasets are examined indicating the areas affected by re-urbanisation. By overlaying these layers a correlation is established between datasets from the 2010/15/19 thus analysing the parts of London facing urban decay.

Design Goals

The design intends to achieve a sustainable, inclusive and accessible city. A 15-minute neighbourhood is defined by identifying the amenities required in a certain radius and mode of transport.

Grading the City

A computational model is devised to evaluate the city. The process of grading shows the various stages of identifying the number of and distance to amenities to determine areas with the least scores.

Data Collection

Datasets sourced from government databases and other sources are arranged into three categories: demographic data, spatial quality data and commutability data.

Analysis and Strategy

Space Syntax Method: Angular Step Depth

The segmentation of the site network is performed using angular step depth to create a detailed model of how the definition of a 15-minute city changes as an individual moves along the streets.

Visibility and Sound Analysis

The impact of visibility and sound on the site are studied using algorithmic simulations. The simulations help examine the way that isovist rays and sound propagate into the urban fabric.

Cellular Automata

The areas for intervention are identified using a computation model of cellular automata on a grid containing extracted datasets. The outcome is intensification on the cells with poor spatial qualities and few number of amenities in vicinity.

Optimisation Algorithm

An optimization algorithm is used to select segments based on multi objective approach. Four street segments with poor spatial characteristics are identified as the areas of interests.

IsoChronic Generative Loop

The 20 segments derived from spatial computational modelling are influenced by an IsoChronic generative loop created on the selected four segments coupled with data extracted from traditional data analysis and deep learning networks.

Masterplan

A strategy is proposed by evaluating the existing theoretical background of a 15-minute city.

Design Proposal

Emplacement of Interventions

The design consists interventions at varying scales: elevated Segments, void Segments and mobile segments.

Void Segments

Void segments are developed using a spatial modelling process.

Mobile Segments

Mobile segments consist of units which are designed with adaptability and are positioned using a steady state island generative algorithm based on footfall trends. These modules are arranged on site to serve as pop up markets containing amenities.

Elevated Segment

Elevated segments reduce the time it takes to travel in the city. This links together the built environment while distancing the pedestrian from vehicular pollution and congestion.

Void Segment Walkthrough

Void segments encourage spaces for social interaction and reduce angular steps.

Mobile Segment Walkthrough

Mobile segments provide better connectivity and accessibility to amenities while promoting local businesses, thus building the economy.

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The Bartlett
B-Pro Show 2022

27 September – 7 October

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