IsoChronic City is an urban response to the recent predicament of what the process of reurbanization in cities will entail in the post-pandemic era. It 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 the residents. This is accomplished through 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 the physical aspects and spatial characteristics to achieve a sustainable, inclusive and accessible city which repeats itself at regular intervals.
BARTLETT SCHOOL OF ARCHITECTURE
Coursework Cover Sheet
Course title: MArch Urban Design
Project Name: IsoChronic City
Student ID No. 21038745
Deadline: 30 Aug 2022
Date submitted: 30 Aug 2022
IsoChronic City is an urban response to the recent predicament of what the process of reurbanization in cities will entail in the post-pandemic era. The word IsoChronic comes from two terms ‘isos’ and ‘chronos’, ‘isos’ in Greek means equal and ‘chronos’ means time. Prior to 1950, the total world population comprised of 34% of the urban population. Rapid Urbanization due to industrialization led to an increment in the urban population up to 55% by the 21st century. Due the magnitude of population growth, lack of infrastructure and haphazard development, urbanization became the cause of serious socioeconomic problems leading to counter-urbanization. London is one of the prime examples of urbanisation. In the beginning of 1940s, the city underwent counter-urbanization where the population migrated to the suburbs which led to its development. However, in the 1970s, the city underwent re-urbanization i.e., the relative population increase in the inner city amid a context of population decline in the functional urban region up until the recent years. London has been deeply affected on various levels during and after the Covid-19 Pandemic. We observe a spiking increment in the usage of green spaces and reduction of retail and commercial footfall along with people moving back to the suburbs. The close proximity of amenities is now crucial. ‘IsoChronic City’ is a project based on the 15-minute neighbourhood concept which is derived from historical ideas about proximity and walkability. The definition of a 15-minute city can be subjective due to the diversity of people’s needs and the way these needs change during a person’s lifetime. The lives of the ‘Commuter group’ more specifically the age group of 25 to 30 year old have been majorly impacted by the pandemic with their hectic lifestyle taking a backseat and being replaced by work from home culture and increased outdoor activities.
The project utilizes a computational model to evaluate the city based on access to amenities, spatial qualities and commutability. The datasets are extracted from government databases and other sources. The grading system is applied on a focus area around the highstreets of London in the dense urban neighbourhood spatial layer. Each highstreet segments is assigned point scores based on the model calculations and the areas with the least scores are identified as sites of interest. Unsupervised algorithms such as principal component analysis and K-Means clustering are used as machine learning tools to study and compare the sites of interest in detail. Segmentation of the selected site is performed using a spatial computational method to extract segments from angular step depth to create a detailed model of how the definition of a 15 minute city changes as an individual moves through the site. The spatial qualities of the site such as geographical influences, impact of visibility and sound, semantic image segmentation using convolution neural networks, amenity distribution and living environment quality are studied to define the intangible factors affecting the notion of accessibility.
Evolutionary and genetic algorithms are used to select street segments with poor spatial qualities. On the resulted segments, an agent-based simulation is conducted based on pedestrian traffic to further reduce the extent of the site. The segments derived from spatial computational modelling are influenced through an IsoChronic generative loop created on the selected segments coupled with data extracted from traditional data analysis and deep learning networks. The strategy is proposed by evaluating the existing and using the theoretical background of a 15-minute city. The design consists interventions of varying scale; elevated segments, void segments and mobile segments. Congested junctions and streets are intervened with elevated segments which aims to increase the distance travelled in 15 minutes. Void segments are located in residential areas with poor living environment. They act as extension of public spaces and are used to build a sense of community. Mobile segments are designed using portable units and other temporary structures housing amenities for residential utilities, commercial, recreational and retail activities. They can be transported via rail, road or water to fulfil the needs of the people throughout the day. The urban interventions are designed with real-time data like sunlight exposure, visibility area, field of view and GPS for a contextual design approach.
The proposed strategy is applied to the highstreets of London in order to transform London into an IsoChronic City: a 15-minute neighbourhood which is sustainable, inclusive and accessible to all. IsoChronic City is a proposal that effects not only the physical aspects of the site but also the spatial characteristics. It aims to create a neighbourhood that promotes the wellbeing of its citizens.
The design proposal consists of elevated walkways, void segments and mobile segments. The form of the elevated walkway is explored through a generative process using footprint and volume of the hypothetical cubes controlled by visibility and shading factors. Scale of the 2x2m grid is transformed to achieve minimum footprint, high extrusion disparity and maximum heigh difference. The cubes are transformed into shortest path from each end of the junction. The walkways are envisioned to change their form and connections based on real time GPS data and the area of shadow they cast during the day.Void Segments are developed using generative spatial modelling process and data extracted from spatial computational techniques like isovist analysis. These calculative processes help to identify maximum visibility to introduce placemaking elements along with interaction spaces and landscaping in residential neighbourhoods while improving accessibility and spatial quality. It consists of elements like pavilions, paved spaces with raised platforms, junctions to act as focal points and frames with lights, planters and seating.The mobile segment intervention consists of units which move on the various networks on site like railways, waterways and roadways derived from the masterplan. Steady-state island genetic algorithm is applied on site using the datasets of post pandemic footfall trends. The pixels containing residential utilities, commercial, recreational and retail activities are arranged on site using steady-state island genetic algorithm following the intensification of footfall trends. Generative spatial modelling uses the outcome from the genetic algorithm coupled with the typologies of units to create a masterplan for the mobile segment. It consists of elements like viewing platforms, green areas, spaces for outdoor activities, pathways and mobile units.