MOOD-ULATED SUBTOPIA JIWEN BIAN 20052180 RAJITA JAIN 21129920 TRISHLA CHADHA 21034236 ZHAOYI WANG 20117826 THE BARTLETT SCHOOL OF ARCHITECTURE, UCL MARCH URBAN DESIGN B-PRO, RC14
RESEARCH CLUSTER 14: MACHINE LEARNING URBANISM MOOD-ULATED SUBTOPIA
MARCH URBAN DESIGN, 2022 BARTLETT SCHOOL OF ARCHITECTURE, UCL LONDON, UNITED KINGDOM TUTORS ROBERTO BOTTAZZI, TASOS VAROUDIS EIRINI TSOUKNIDA, MARGARITA CHASKOPOULOU, VASILEIOUS PAPALEXOPOULOS, PROVIDES NG GROUP MEMBERS JIWEN BIAN, RAJITA JAIN TRISHLA CHADHA, ZHAOYI WANG
SYNOPSIS
To identify the aspects of attention economy in de tail, we traced back and explored the historical timeline of London and studied the relevant theories and historical events that lead to the shaping of the city. To increase the attention economy of a space, an increase in the level of engagement needs to be made. Humans get more engaged with non-monot onous spaces which offer instances to evoke differ ent emotions. A perceivable distance by the human brain being about 50m, the study focuses on modu lating the existing stagnant mood of the place into a more dynamic space to foster social interactions and enhance engagement with the built environ ment. Thus with the introduction of light, colour, na ture, sound and visual interventions, this project aims to modulate the mood of the space to give rise to a ‘MOODULATED SUBTOPIA’.
HSBC History Wall @Flickr
The built environment has the power to actually ma neuver a person’s emotions through its spatial con figurations and other atmospheric features. A public space might evoke different emotions depending on the lighting, sound and other ambience related pa rameters. This research, Moodulated subtopia delves on the need to modulate the mood and emotions of the built environment to accentuate the economy and development of the city.
CONTENTS INTRODUCTION SITE RESEARCH DATA ANALYSIS AND MACHINE LEARNING SITE DATA ANALYTICAL SIMULATIONS SECTION 1 SITE STRATEGY DESIGN STRATEGY ANDVISUALISATIONSECTION2SECTION 3 SECTION 4 SECTION 5 SECTION 6
PART 01 : PROJECT BACKGROUND
12 | Introduction Mood-ulated Subtopia MArch Urban Design - Term 03 | 13 Part 01: Project Background
London before the houses @Edward Stanford
Humans traverse various spaces in day to day lives and the level of engagement with the surroundings is something that decides the success of a place. The relatability, identity, immediacy, personalisation, interpretation, authenticity, accessibility of the space are determinants of the level of engagement that space offers. In short the attention a space is able to capture decides the engagement of the user with it. Attention economy is a method of information management that treats human attention as a scarce resource and employs economic theory to tackle a variety of information management issues. “Attention is a resource—a person only has so much of it,” Matthew Crawford Accordingsays.toThomas H. Davenport and John C. Beck, the idea of attention is defined as “focused mental involvement on a specific item of information.” Items enter our awareness, we pay attention to them, and then we decide whether or not to act. (Davenport & Beck 2001, p. 20)
Introduction to Attention Economy
BACKGROUND THEORY
INTRODUCTION
Early Cultures of Gentrification ‘Attentional Transactions’ by Georg
14 | Introduction Mood-ulated Subtopia MArch Urban Design - Term 03 | 15 Part 01: Project Background
INTRODUCTION
Mass migration and growth of Financial and Commercial Services Theory of Experimental Psychology by Wilhelm Wundt
The Principles of Psychology and aspects of Attention by William James Introduction of Railways
Micheal Goldhaber defined the sufield of Internet Economics
Introduction of ‘Attention Economy’ by Herbert A. Simon
The Era of ‘Cyberculture’
Historical Timeline of Attention Economy
London declared as the Trade and Financial Capital
The Industrial Revolution
The period of the 1750s saw the Industrial revolution which brought about a major change in the economy and production of the city. The period till mid-18th century saw a mass migration which led to the growth of the financial and commercial services.
Old and New Attention Economies in London @Flickr
Attention economy was introduced as an approach to the management of information that treats human attention as a scarce commodity and applies economic theory to solve various information management problems.
During this time there was an increasing focus on psychology related to the built environment and the 1850 saw the introduction of the theory of experimental psychology by William Wunt which further related to the concept of attention by William James in 1890. In 1971, the concept of ‘attention economy’ came into existence introduced by Herbert A Simon.
Attention economy focuses on the interface between cities, people and technologies and investigates the ubiquity of digital devices and the various telecommunications networks that augment our cities and thus impact urban living.
MArch Urban Design - Term 03 | 17
ATTENTION ECONOMY
MArch Urban Design - Term 03 | 19
Canary Wharf Built Environment @Flickr
HOW CAN THE MODULATION OF THE EXISTING THEATRICAL MOOD OF THE BUILT ENVIRONMENT ACCENTUATE THE ATTENTION ECONOMY OF THE URBAN SETTING?
20 | Introduction Mood-ulated Subtopia MArch Urban Design - Term 03 | 21 Part 01: Project Background INTRODUCTION Identification of Attention Economies
22 | Introduction Mood-ulated Subtopia MArch Urban Design - Term 03 | 23 Part 01: Project Background INTRODUCTION Factors Affecting Attention Economies
Oxford Bristol
Leeds Aberdeen Glasgow Edinburgh NewcastleYork Preston Norwich Birmingham BrightonLondonGlasgowCardiff Dorchester Plymouth
24 | Introduction Mood-ulated Subtopia Part 01: Project Background INTRODUCTION Identification of Attention Economies UK LEGENDRoad Network Rail IntensificationNetwork Lines Attention economy depends on factors related to demographics, economy, transportation, and the percentage of attractiveness of the city. It further relates to the spatial characteristics of the attention islands drawing relations to the city as a theatre and overall mood of the city. In order to get the complexity and the network of attention economies, it is imperative to have a multi scaler approach and analyze the impact of these spaces at the national, city and a macro level before narrowing down to a micro scale. At the national scale, the measure of population and commercial activity is unevenly distributed leading to intensification points in UK. These intensification points are the foundations of the attention economy and drive the economic aspect of that area.
Birmingham Portree
Glasgow Manchester London Chemsford
26 | Introduction Mood-ulated Subtopia MArch Urban Design - Term 03 | 27 Part 01: Project Background INTRODUCTION Identification of Attention Economies London London, being the capital of UK, captures the major attention in all major fields as compared to other cities. It serves as the business, retail and the cultural hub of the country with several spots within the city accommodating the facilities. LEGENDAccessibility Levels Land AttentionPricesEconomies Focus Location 01 Canary Wharf Site Central Business District 0 2.5 5
PART 02 : Data Crossing
30 | Site Research - Mood-ulated Subtopia MArch Urban Design - Term 03 | 31 Part 02: Data Crossing SITE RESEARCH Macro-Scale Analysis LEGENDHigh Population Density Medium Population Density Low Population Density Rail Network 0 2.5 5 Focus Area
Macro-Scale Analysis | Grid Selection
In London, the central part comprises of the main retail, residential and business areas. These areas serve as the main revenue generating part of the city.
34 | Site Research - Mood-ulated Subtopia MArch Urban Design - Term 03 | 35 Part 02: Data Crossing SITE RESEARCH Macro-Scale Analysis I Space Syntax LEGEND23.9 - 31.2 Choice R1500 31.2 - 41.4 Choice R1500 41.4 - 209.5 Choice R1500 The first step to identify sites within a macro scale was the angular segmentation maps produced by depthmaps. These reveal the primary and secondary streets, the junctions, the most traversed paths and the most integrated parts of the urban built environment of the central London area. To identify the centrality of the areas, the choice and integration maps have been studies to identify the attention islands with maximum integration and choice values. Our potential sites of development with be adjoining these attention islands to desaturate them. Integration R1500 Choice R1500 Choice R500 Camden Town BethnalIslington Green Canary VauxhallSouthwarkWharf Vauxhall Camden Town Islington Bethnal Green Canary Wharf Southwark 1 - 17.2 Choice R1500 17.2 - 23.9 Choice R1500 0 2.5 5
36 | Site Research - Mood-ulated Subtopia MArch Urban Design - Term 03 | 37 Part 02: Data Crossing SITE RESEARCH LEGENDRail Network Low Economic Density Medium Economic Density High Economic Density Macro-Scale Analysis | Economic Development Camden Town Canary SouthwarkWharf0 2.5 5
38 | Site Research - Mood-ulated Subtopia MArch Urban Design - Term 03 | 39 Part 02: Data Crossing SITE RESEARCH LEGENDHigh Pedestrian Density Low Pedestrian Density Rail Macro-ScalePublicNetworkAmenitiesAnalysis | Pedestrian Density and Transportation Camden Town Canary SouthwarkWharf0 2.5 5
40 | Site Research - Mood-ulated Subtopia MArch Urban Design - Term 03 | 41 Part 02: Data Crossing SITE RESEARCH LEGENDCycle Network High Permeable Neighbourhood Score Medium Permeable Neighbourhood Score Low Permeable Neighbourhood Score Macro-Scale Analysis | Permeable Neighbourhood Density Camden Town Canary SouthwarkWharf0 2.5 5
PART 03 : DATA ANALYTICS AND MACHINE LEARNING
44 | Data Disribution - Mood-ulated Subtopia MArch Urban Design - Term 03 | 45 Part 03: Data Analytics and Machine Learning DATA DISTRIBUTION Macro-Scale Analysis | Data Resampling Population 2021 Population 2004 British Origin Economic Activity Gentrification Index Recreational Area Footfall Internet Performance Transport Station Footfall Twitter Data Bored Emotion Calm Emotion Love Emotion Population 2013 Non British Origin Household Income Economic Activity Flat Type Dwelling House Median Price 2010 House Median Price 2014 Points of Interest Residential Area Transport Station Areas Pleasant Emotion Sad Emotion Serene Emotion Retail Area Footfall PTAL Levels Happy Emotion Economic Activity Places of HouseholdPopulationInterest2013IncomeActivityEconomicEmotionHappyFootfallActivityRetaiilPTALLevels
46 | Data Disribution - Mood-ulated Subtopia MArch Urban Design - Term 03 | 47 Part 03: Data Analytics and Machine Learning DATA DISTRIBUTION Macro-Scale Analysis | Principal Component Analysis The set of data sets chosen are on the basis of attention economy islands and the attention economy attractors. Machine learning algorithms like PCA, Kmeans, pair plot and scatter plots help reduce the dimensionality of the data Thesesets. algorithms also enable in deriving behavioral correlations between the various data sets. The retail and commercial activity of the areas is closely related to the points of interest and the presence of efficient transport network around. It also depends largely on the deprivation score and the gentrification index of the areas. These data sets seem related to the moods of the people as registered in twitter, but the correlation is Thefaint.diagram shows the three principal components on the chosen macro scale. 2013Population OriginBritish Bunglow-TypeDwelling 2014PriceMeanHouse ActivityEconomic IncomeHousehold LevelsPTAL IndexGentrification R1500Choice R500Choice R1500Integration R500Integration DepthStep FootfallAreaRetail FootfallAreaRecreational FootfallStationTransport TwitterEmotionHappy TwitterEmotionGoMust TwitterEmotionSad AreaCommercial InterestofPoints AreaResidential AreaStationTransport -404210 The reduced dimentionality of data depicted by the 3 components mapped on the map. PCA Component 1 PCA Component 2 PCA Component 3 LEGEND
48 | Data Disribution - Mood-ulated Subtopia MArch Urban Design - Term 03 | 49 Part 03: Data Analytics and Machine Learning DATA DISTRIBUTION PCA Component 1 PCA Component 2 PCA Component 3 LEGENDMacro-Scale Analysis | Principal Component Analysis 0 2.5 5 PCAPCAPCAComponent3Component2Component1
50 | Data Disribution - Mood-ulated Subtopia MArch Urban Design - Term 03 | 51 Part 03: Data Analytics and Machine Learning DATA DISTRIBUTION Cluster 1 Cluster 2 Cluster 3 LEGENDMacro-Scale Analysis | K-Means Analysis 1Cluster 2Cluster 3Cluster 0 2.5 5 The kmeans clustering created clusters of the various data sets chosen and condensed them. This clustering helped identify related data sets, the dominant data sets of a cluster, the data set dominant in a specific area and most importantly reducing the dimensionality of the data in a more comprehendible format.
52 | Data Disribution - Mood-ulated Subtopia MArch Urban Design - Term 03 | 53 Part 03: Data Analytics and Machine Learning DATA DISTRIBUTION Macro-Scale Analysis | Pairplot and Coorelation Heatmap The pairplot and heatmap corelations enable in decoding the overall dominant data sets and their behaviour in reference to each other. The economic activity and the population data sets are in coherence with each other but the transport data sets and the economic activity does not seem related. 1. Population 2013 2. British Origin 3. House Price Mean 2014 4. Economic Activity 5. Household Income 6. Gentrification Index 7. Choice R1500 Metric 8. Choice R1000 Metric 9. Choice R500 Metric 10. Integration R1500 Metric 11. Integration R1000 Metric 12. Integration R500 Metric 13. Retail Area Footfall 14. Recreational Area Footfall 15. Transport Station Footfall 16. Happy Emotion Twitter 17. Must Go Emotion Twitter 18. Sad Emotion Twitter 19. Commercial Areas 20. Points of Interest 21. Residential Areas 22. Transportation Areas 23. Public Transport Access Levels 24. Noise Pollution Level 25. Noise Pollution Road
54 | Data Disribution - Mood-ulated Subtopia MArch Urban Design - Term 03 | 55 Part 03: Data Analytics and Machine Learning DATA DISTRIBUTION Population Density Economic ActivityLEGENDPTALMacro-Scale Analysis | Dimentionality Reduction Population Density Economic Activity PTAL PedestrianEthnicityPointsLevelsofInterestFootfall0 2.5 5
56 | Data Disribution - Mood-ulated Subtopia MArch Urban Design - Term 03 | 57 Part 03: Data Analytics and Machine Learning
DATA DISTRIBUTION
The results from the detailed machine learning algorithms helped in identifying the dominant and most influential data sets in the prominent areas of the macro scale. These data sets were then mapped on the macro scale on a grid so as to thoroughly analyse the variation among them within the chosen macro area. This catalysed the selection of micro level sites. The micro level areas chosen were on the areas which potrayed a high population of mixed origin. The public transport activity levels are optimum which enabled a high economic activity in the area. Also the footfall of the areas are increased by the presence of several retail outlets and points of interests catering to different age groups and cultural backgrounds.
Macro-Scale Analysis | Data Resampling
PART 04 : MICRO SCALE SITE SIMULATIONS
Micro-Scale Analysis | Site Selection
CANARY WHARF
Three sites namely – Camden, Southwark and Canary Wharf have been narrowed down as a result of the datasets chosen and patterns observed. These micro scale sites will form the basis of running further analysis to finally conclude to a specific site for design intervention.
CAMDEN TOWN
SOUTHWARK
ANALYTICAL SIMULATIONS Analysis | Light Simulation
Micro-Scale
62 | Analytical Simulations - Mood-ulated Subtopia MArch Urban Design - Term 03 | 63 Part 04: Micro Scale Site Simulations
Various layers of light combine to produce the character and identity of a place. These include spill light from buildings, street and amenity lighting, the floodlighting of both public and private buildings, landscape lighting and illuminated media and signs. These coalesce not only to meet visual needs but also to create ambience and Theatmosphere.studyof light is crucial as light plays an important role in altering the mood of the city and the areas of Camden, Canary Wharf and Southwark have different types of lights to change the ambience of the place. Consistent lighting helps in emphasizing the retail frontages and billboards whereas the considered lighting on the river bridges enhances the Southwark Inexperience.CanaryWharf, the street lights keep the otherwise dead space alive. LEGENDHighNoLowMediumIntensityIntensityIntensityIntensity Camden Town Canary SouthwarkWharf Camden Town Canary SouthwarkWharf
LEGENDMedium Frequency Noise Low Frequency Noise High Frequency Noise Camden CanarySouthWarkTownWharf
64 | Analytical Simulations - Mood-ulated Subtopia MArch Urban Design - Term 03 | 65 Part 04: Micro Scale Site Simulations
The aim of sound simulations was to identify and differentiate between thwe various urban fabric environments. the behaviour of a sound source is dependent on the surrounding urban built settings.
ANALYTICAL SIMULATIONS
Micro-Scale Analysis | Sound Simulation
By performing sound simulations and analyzing the bounces of the sound rays, we have tried to identify the spatial character of the city. Identiacal sound sources potrayed varied complexities within the area. By studying the type and intensity of bounces, we were able to differentiate between narrow streets, public plazas and the junctions.
66 | Analytical Simulations - Mood-ulated Subtopia MArch Urban Design - Term 03 | 67 Part 04: Micro Scale Site Simulations ANALYTICAL SIMULATIONS Micro-Scale Analysis | Visibility Graph Analysis Among all the senses bestowed to humans, vision serves to be a major deciding factor and the most dominating sense of perception. The visual depth and the range of vison has been analysed for the three sites with the help of depthmaps. The visibility of spaces from the street help in deciphering the attention that the place has as a LEGENDresource.Highest Visibility High LessOptimumVisibilityVisibilityVisibility Sectional representation of Visibility Analysis
The river being the most visible part of the Canary Wharf, it serves as a tieing element of the built fabric of London to the central business district area of the Canary Wharf area. LEGENDHighest Visibility High LEGENDLessOptimumVisibilityVisibilityVisibilityMicro-ScaleAnalysis | Visibility Graph Analysis
Canary Wharf - Night Movement Road
Micro-Scale Analysis | GPS Movement Simulation
flow across
70 | Analytical Simulations - Mood-ulated Subtopia MArch Urban Design - Term 03 | 71 Part 04: Micro Scale Site Simulations
and
sites during
and direction
and highlights
high
The GPS data of the Southwark area depicts movement patterns the traffic intesity of highlighting the most to least
LEGENDDirectionNetworkFlow
grocery stores, clothing stores, restaurants and
The aim of the GPS movement analysis is to highlight the intensity of movement of pedestrians vehicular the three the day main intensity of movement the camden street the other
The Gps data of the Canary Wharf depicts high intensity of movement during the day time the opposite case during the night time. This is primarily to the business oriented
is observed around
ANALYTICAL SIMULATIONS
flow thus
due
Camden Town - Day Southwark - Day
LEGENDPedestrian Movement Vehicular
with
Canary Wharf - Day Camden Town - Night Southwark - Night
and night Intime.camden, the
which houses
spaces in these areas.
retail areas.
integrated streets and areas.
72 | Analytical Simulations - Mood-ulated Subtopia MArch Urban Design - Term 03 | 73 Part 04: Micro Scale Site Simulations ANALYTICAL SIMULATIONS The isovist analysis focuses on the angles of vision. The fundamental parameters of the visual field are measured at regular intervals on the most traversed paths of the micro scale sites. This analysis aims to visualise the vision fields from various points of the area. This helps in getting a sense of the narrow roads, the height of the built structures and the number of turns in turn giving an insight to the built fabric of the place. LEGENDIsovist Line Most LEGENDNotOptimumVisibleVisibleVisibleMicro-ScaleAnalysis | Isovist Simulation Isovist Area Line of BuildingsSelectedSightRoutes
CANARY WHARF
CAMDEN TOWN
SOUTHWARK
The isovist visual field is spread in the area taken from the poiints on the busy streets of the zones, highlighting the most visible areas of the
Micro-Scalesites.Analysis | Isovist Analysis
Micro-Scale Analysis Google Street Image Analysis
Micro-Scale Analysis Street
Image Analysis
The google street images of all four directions were extracted of these points across all the sites. To then study them in detail, colour analysis and semantic segmentation was performed on these images.
CAMDEN TOWN
CANARY WHARF
SOUTHWARK
Micro-Scale Analysis | Google Street Image Analysis
Analysis | Google Street Colour Analysis LEGENDRelaxStunningCalmOptimisticDisciplineWeperformed
Micro-Scale
Areas like camden have been observed to have bright colours like red, purple blue which increases the excitement factor and thus draws more movement.
the colour analysis for the areas to decipher the overall colour pattern of the city with hue shades that ultimately defined the mood of the city and its effects on the human mind.
84 | Analytical Simulations - Mood-ulated Subtopia MArch Urban Design - Term 03 | 85 Part 04: Micro Scale Site Simulations ANALYTICAL SIMULATIONS Semantic segmentation was performed on the extracted images by using python algorithms to get a billboard to image percentage. The images show a process of the same. The images were analysed using semantic segmentation to segregate different elements such as sky, trees, buildings. Micro-Scale Analysis | Image Segmentation Training Set 25,574 images All images are fully anno tated with objects and, many of the images have parts Validationtoo. Set 2,000 images Fully annotated with ob jects and parts Test Fully1,000Setimagesannotated with ob jects and parts Convolutional Neural Network Output[0][0] = (9*0) + (4*2) + (1*4) + +(1*1) + (1*0) + (1*1) + (2*0) + (1*1) = 0 + 8 + 1 + 4 + 1 + 0 + 1 + 0 + 1 = 16 Training Machine Learning DepthwiseModelConvolution Pointwise Convolution Colour Analysis Image Segmentation PhotoBuildingRealisticPercentage
In order to understand the importance advertisements, we have also calculated the percentage ratio of to the buildings for all the three These analysis helped us distinguish multiple of to the building an to the building A area would have a higher billboard to building as compared to the commercial counterparts.
LEGENDBillboardsExistingBuildings Four DIrections BillboardBuilt-FormBillboardsResult
billboards
retail
ratio
86 | Analytical Simulations - Mood-ulated Subtopia MArch Urban Design - Term 03 | 87 Part 04: Micro Scale Site Simulations
gives
activity driven areas including commercial, rescreational, river oriented Thespaces.percentage or ratio
billboard
ANALYTICAL SIMULATIONS
use.
insight
Micro-Scale Analysis | Billboard Analysis
or residential
sites.
CAMDEN TOWN
This suggested a differential use of advertisement and attention as a resource depending on the function of the
Micro-Scalearea. Analysis | Billboard Analysis
SOUTHWARK
CANARY WHARF
The ratio of billboard to a building was found to be different in Camden town, Canary Wharf and Southwark.
90 | Analytical Simulations - Mood-ulated Subtopia MArch Urban Design - Term 03 | 91 Part 04: Micro Scale Site Simulations ANALYTICAL SIMULATIONS Micro-Scale Analysis | Semantic Segmentation Sections The process of semantic segmentation was performed through a procedural approach by the help of python algorithms to carefully train the model. The model thus differentiated between the pavements, roads, buildings, greens, people, billboards, cars, etc. These images were then projected back on their respective street sections to analyse the street view and visualise a segemented percieved image of the city. Camden Town Canary SouthwarkWharf U-Net Source:ArchitectureROlafetal, U-Net: Convolutional Networks for Biomedical Image Segmentation conv 3x3, ReLU copy and crop max pool 2x2 up-conv 2x2 convMapSegmentationOutput1x1ImageInputTile
92 | Analytical Simulations - Mood-ulated Subtopia MArch Urban Design - Term 03 | 93 Part 04: Micro Scale Site Simulations ANALYTICAL SIMULATIONS
94 | Analytical Simulations - Mood-ulated Subtopia MArch Urban Design - Term 03 | 95 Part 04: Micro Scale Site Simulations ANALYTICAL SIMULATIONS
PART 05 : Site Strategy
Site Strategy | Site Image
LEGENDResidential Area Business Area Railway Stations
also has residential and retail areas.
and
Primarily a business Wharf
via rail and road
LEGENDSiteStrategy
| Site Analysis
area, Canary
space with high end cafes and restaurants.
Being well connected to the other parts of London network, it serves to be the central business district of London also as a
Green Spaces Figure Ground Land Use
area serves as the Central Business District of London housing all the major office buildings. To decode the dynamics of the area, a study of the transportation system, built fabric, green areas, public ammenities and the land use pattern was mapped. This potrayes the Canary Wharf to be a highly commercialised zone with good accessibility and connectivity to the other parts of London. LEGENDRoad LEGENDGreenAmmenitiesNetworkSpaces StreetRiver
area of Canary Wharf is like a peninsular landmass, surrounded by the Thames on three sides. It is located on the Isle of Dogs in the London Borough of Tower Hamlets.
DECODING SITE DYNAMICS
The Network Public Amenities
102 | Decoding Site Dynamics Mood-ulated Subtopia MArch Urban Design - Term 03 | 103 Part 05: Site Strategy
The
Site Analysis | Site Conditions
Canary
DECODING SITE DYNAMICS
To understand the Wharf detail, it is imperical to is clearly Iterations
deeply analyse the built fabric of the area. By analysing the bounces generated by a source and the intensity of the network lines, it
Site Analysis | Built Unbuilt Relationship
area in
evident that the Canary Wharf potrays a highrise narrow street typology with increased road width and decreased building heights as one proceeds towards the river on either sides. SECTIONPLAN Built-Unbuilt Relationship
104 | Decoding Site Dynamics Mood-ulated Subtopia MArch Urban Design - Term 03 | 105 Part 05: Site Strategy
106 | Decoding Site Dynamics Mood-ulated Subtopia MArch Urban Design - Term 03 | 107 Part 05: Site Strategy DECODING SITE DYNAMICS To get an indepth analysis of the Canary Wharf Area, the visual field surface and lines are mapped. The analysis of the visual field helps in understanding the built fabric of the area, differentiating between narrow streets, high rise built structures and the number of nodes on the LEGENDLEGENDstreet.IsovistLineMostVisibleOptimumVisibleNotVisibleIsovistAreaLineofSightSelectedRoutesBuildingsSiteAnalysis|Isovist Analysis
108 | Decoding Site Dynamics Mood-ulated Subtopia MArch Urban Design - Term 03 | 109 Part 05: Site Strategy DECODING SITE DYNAMICS Site Analysis | Wallacie To identify the potential zones of intervention in the Canary Wharf area, we generated regular lattices within the site, removed buildings and waters, set different rules for the remaining lattices, and selected a certain number of points to generate heat maps to determine which area had the most potential to become the place we finally designed in both the day and night modes. In daytime, we hope there is low accessibility, low visibility, low tree/grass Atpercentagenight,we hope there is low light , low visibility and low accessibility. Optimum Visible Not Visible LEGEND Rules Generation 10 Rules (Accessibility) Generation 100 Rules (Sound) Generation 1000
110 | Decoding Site Dynamics Mood-ulated Subtopia MArch Urban Design - Term 03 | 111 Part 05: Site Strategy
DECODING
SITE DYNAMICS Site Analysis | Design Strategy
Lovely Mood Calm Mood Mood Mood
Boring Mood Angry mood Happy
DECODING SITE DYNAMICS
The are Mood keywords used to grab the mood data from twitter are boring, happy, excited, awful, lovely, calm, angry and sad. These presented a range of four positive and four negative moods. Then images from the points were studied to decode the various moods in relation to the visual perception. Each color represents a specific mood.
112 | Decoding Site Dynamics Mood-ulated Subtopia MArch Urban Design - Term 03 | 113 Part 05: Site Strategy
To modulate the mood of a place, understanding the existing pattern is Thecrucial.Factors that affect mood are Light Sound Movement and Visibility and an alteration in these values is what modulates the mood.
Awful Mood Sad Mood
Site Analysis | Existing Mood Analysis
Overlaying all the mood data, the shape and position of each rectangle represents hue and saturation of the four Onimages.combination, the existing mood masterplan showed a variation in terms of the moods present.
Excited
A city is an amalgamation of various spaces, colors and spatial characteristics which evoke different emotions and moods in people. This graphic is a depiction of the many moods evoked in people by the area of Canary Wharf as registered in twitter.
Site Strategy | Mood Visualisation
PART 06 : Design Strategy
118 | Modulating the Site Mood-ulated Subtopia MArch Urban Design - Term 03 | 119 Part 06: Design Strategy MODULATING THE SITE To increase the attention economy and enhance the quality of a space for its users, the level of engagement with the surroundings needs to be emphasized upon. An environment with repetition and monotony reduces the involvement of the users thus to increase the attention, a modulation needs to be incorporated into the space to keep the users engaged. 8 - 3 Mood Score 0 Mood Score LEGENDBoost Attention Economy Increase level of engagement Break the monotony Increase modulation of mood Design Concept | Mood Design Strategy Study actual mood Identify areas with monotony Introduce light and colours Modulate the environment 2 - 1 Mood Score >10 Mood Score Monotonous Mood Mood ModulatedVariationMood Existing Mood Score
120 | Modulating the Site Mood-ulated Subtopia MArch Urban Design
Design Concept | Step Depth Analysis
Take 3 points per path
Distance is comprehendable
Study the step depth
According to Edward T Hall, the father of proxemics, 50m is an easily comprehendible visual field by the human mind. Anything larger can make the humans feel dislocated and lost. So to enhance the engagement, the area was divided into subparts of 50m and the mood for each individual part was most traversed paths
- Term 03 | 121 Part 06: Design Strategy
MODULATING THE SITE
50m for the analysis
considered.Selectthe
122 | Modulating the Site Mood-ulated Subtopia MArch Urban Design - Term 03 | 123 Part 06: Design Strategy
Optimum Visible Not Visible
MODULATING THE SITE
Design Concept | Existing Mood Analysis
Regions with lower rates of mood
LEGEND
The center of the grid is a representative of its own value and the surrounding data points. A vertical upward ray is drawn from the center point of each grid, and the ray touching the mood data is scored. Scores are added for positive mood, and are deducted for negative mood, thus obtaining the first parameter: mood index. Then, by calculating the difference between the mood index of the central point and it’s surrounding’s, the second parameter is obtained: the mood difference rate.
variance also happen to be regions with lower mood indices. That is to say, the mood of people in these areas is negative and does not change in a large area. So these are the areas where a modulation in mood needs to be incorporated.
Light on Horizontal Surfaces Sound in Space Light on Vertical Surface
Design Proposal
Disruptive Nature Atmospheric Variation Intangible Cultural Intervention
Considering the importance and relevance of light in the modulating the engagement of people, several iterations for the placement of light within the site were considered. The improved connectivity network and the increased attention was analyzed for each case to finally get on to the proposed light masterplan.
126 | Modulating the Site Mood-ulated Subtopia MArch Urban Design - Term 03 | 127 Part 06: Design Strategy
Design Concept | Light Iterations
MODULATING THE SITE
Concept | Proposed Light Masterplan Light
relationship
of each iteration was studied and simulated the possible
Proposed Masterplan
were then distributed and configured to get the maximum possible
Point cloud of light of the areas Area selection Light intensification
High Intensity Light Light
To get onto the final
MODULATING THE SITE light masterplan point cloud light intensity with lights light lighting
the help of contours. The
Optimum Intensity
LEGENDDesign
Connection
distribution. Based on this, the different types of lights and their intensities were figured out to refine the
128 | Modulating the Site Mood-ulated Subtopia MArch Urban Design - Term 03 | 129 Part 06: Design Strategy
Low Intensity
after several iterations, the
analysis in our area.
Light Masterplan
This graphic is a representation of the variation in light that could possibly increase the engagement of people in the Canary Wharf area. This takes into account the variation in colours and intensities of the lights.
Design Concept | Proposed Light Section Existing ProposedSectionSection
Design Concept | Proposed Light Section
Design Concept | Proposed Light Section
a
suitable for the people or
Design Concept | Proposed Humidity Masterplan
would
138 | Modulating the Site Mood-ulated Subtopia MArch Urban Design - Term 03 | 139 Part 06: Design Strategy
propose
High Intensity Light Optimum Intensity LightLEGENDLow Intensity Light
MODULATING THE SITE Considering the closeness to the river and the built fabric of the area, we an alteration in the humidity or water levels of the area. This create micro climate the of the arrea.
atmospheric
users
This graphic is a depiction of the many humidity levels in the area of CanaryHumidityWharf. Masterplan
142 | Modulating the Site Mood-ulated Subtopia Urban Design
MODULATING THE SITE
Design Concept | Ray Casting Technique
- Term 03 | 143 Part 06: Design Strategy
Ray tracing is a technique to project the information of an area to a larger area. We employed this ray tracing to project the colors of the google street images to the building facades and onto the ground to get a sense of the perception of people regarding the Thespace.google street images were taken and placed at the position from where they were taken. Considering a point at a human eye level, a ray was projected onto the façade carrying the color code of the image where the ray hit it to finally project the same color onto the façade.
MArch
144 | Modulating the Site Mood-ulated Subtopia MArch Urban Design - Term 03 | 145 Part 06: Design Strategy MODULATING THE SITE Design Concept | Ground Ray Casting The ground forms a considerable portion of vison hence projecting the google street images onto the ground to get a view of the city as perceived by the people is crucial. Angry Mood Calm Mood Aweful Mood Excited Mood Bored Mood Lovely Mood Sad Mood Happy Mood Geo-locate the google images Change the Colour Project color on ground Define Interventions Design modulation
By projecting the google street images onto the facade and the ground, the area is restudied to identify the possible areas of design modulation. The projection of mood onto the area enables in reading the area as a modulated area with various emotions and moods.
Design Concept | Ground and Facade Ray Casting
we grabbed 1.5 million points in this area, and each point has information about its position, normal vector, and the mood represented
Based
MODULATING THE SITE on ray casting, by
148 | Modulating the Site Mood-ulated Subtopia MArch Urban Design - Term 03 | 149 Part 06: Design Strategy
the results of the
its ten closest points. By iterating over this information, we deform the points from the original cube. The methods of deformation include scale up and down, moving and rotating and adding light sources.
Design Concept | Ray Casting Rules
The generated output obtained by performing ray casting and data projection on to the surfaces of the built environment were then transformed further by procedural and systemic set of rules dependent on the scraped data to reshape and rewrite the selected area of intervention into a modulated space.
Ray Casting Tranformation
152 | Design Visualisation - Mood-ulated Subtopia MArch Urban Design - Term 03 | 153 Part 07: Design Visualisation MOODULATED SUBTOPIA Design Proposal | The Interventions
PART 07 : The Mood-ulated Subtopia: Design Visualisation
This time dynamics is dependent on the GPS data of the people moving throughout the day.
As people traverse during the day, the intensity of lights, their colors and the other interventions undergo a transition.
Design Visualisation | The Mood-ulated Subtopia
158 | Design Visualisation - Mood-ulated Subtopia | 159 Part 07: Design Visualisation MOODULATED SUBTOPIA To accomplish the atmospheric interventions, light, and sound sources of varied characteristics along with other features capable of altering the atmospheric conditions are being proposed whose spatial configurations will have an impact on the intangible aspects of the space. This spatial design output generated is the light intervention in the form of modulated cubes of different materials. The vari ation in these cubes represents differential intensities of light over the façade.Cubes/ Point with light Cubes/ Point with tranparent material Cubes/ Point with frosted glass Cubes/Point with semi frosted glass Cubes/Point with colours Design Interventions | Light on Facade Cube Modulation Vertcal Light Projections Point Modulation Vertcal Light Projections
Lights on ground
Light with transparent material
semi
interventions
Light with Horizontal Light ProjectionsLight Modulation
Light with frosted glass
colours
MOODULATED SUBTOPIA Design Interventions | Light on Ground
modulation
Light with frosted
160 | Design Visualisation - Mood-ulated Subtopia MArch Urban Design - Term 03 | 161 Part 07: Design Visualisation
The third is in the form of cube on the ground. The modulated cubes represent spatial dividing the public sphere into different modular spaces.
glass
162 | Design Visualisation - Mood-ulated Subtopia MArch Urban Design - Term 03 | 163 Part 07: Design Visualisation MOODULATED SUBTOPIA Design Interventions | Sound in Space Next is the intervention of sound in the form of pavilions with sound modulations along the path. Sound sources on ground Sound Platformspavillionsforsound performances Landscaped platforms with sound sources Sound with light modulation Sound Modulation Horizontal Sound Projections
With our design interventions, we have been able to modulate the ground to create interactive zones and spaces within the existing spatial structure.
There are physical interventions in the form of public seating ranging from 200400mm arranged in levels.
Also, there are design interventions in the form of installations and lastly the pavilions that are accessible to the public.
The light installations in the form of frames direct the pedestrian movement across the site.
With our design we aim to create a space which is accessible by all and inclusive in nature by taking informed decisions fed by the machine learning processes and data handling algorithms throughout the process.
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Part 07: Design VisualisationDesign Interventions | Dynamicity With Time
As people traverse during the day, the intensity of lights, their colors and the other interventions undergo a transition.
This time dynamics is dependent on the GPS data of the people moving throughout the day.
MOODULATED SUBTOPIA
As the design project is based on the emotional projection from a human point of view, he best way to experience it is to observe the changes of the city in virtual reality (VR).
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The designed model is imported into the game engine Unity3D and simulates buildings, environments, lights, etc. Players can visit the design venue through VR devices and rerecognise the area in different ways. You can even manipulate drones in virtual reality to observe and evaluate the design from the sky to the ground.
Virtual Reality Data Visualisation
