InterCITY by Tejas Sidnal

Mehnaj

Tabassum,

Tejas

Sidnal,

Nicolas

Cabargas,

Ulises

Juliao

Core studio 2: Isle of Dogs, Urban Development

i n t e r C I T Y

2012 - 2013 Architectural

EmTech: Emergent Technologies Association School of

and Design Architecture

Contents

Vocabulary 4

Hierarchy of Roads 52

Network 78

Abstract 5

Height Towards Network Type 54

Geometry 79

Logic 6

GEOMETRY: Chapter 5

PERSONAL ANALYSIS: Chapter 7

WORKFLOW: Chapter 1

Patch Selection 58

Morphology 84

Cell Formation 59

Branching City 85

Start Point 22

Density 61

Topological optimization of cities with L-System 86

Definition 26

Height 62

Integration 88

Objectives 27

Geometry 63

THE SITE: Appendix

Setup 28

Library 64

Land Use 92

Optimization of the system 29

Local Green Space 66

Existing Roads 94

Determining Density 35

CRITICAL ANALYSIS: Chapter 6

Networks 95

OPEN SPACE: Chapter 3

Starting point 71

Samples Boundary Condition 98

Green Areas 42

Distribution 72

Samples Network 102

NETWORK: Chapter 4

L-System 73

Samples Open Space 108

Network points and Block formation 48

Connection 74

Sources 112

Network Type 50

Programme 76

L-SYSTEM: Chapter 2

Vo c a b u l a r y L-System: An L-system or Lindenmayer system is a parallel rewriting system, namely a variant of a formal grammar, most famously used to model the growth processes of plant development, but also able to model the morphology of a variety of organisms.[1] An L-system consists of an alphabet of symbols that can be used to make strings, a collection of production rules that expand each symbol into some larger string of symbols, an initial “axiom” string from which to begin construction, and a mechanism for translating the generated strings into geometric structures.1 Delaunay and Voronoi: The Delaunay triangulation is a triangulation which is equivalent to the nerve of the cells in a Voronoi diagram, i.e., that triangulation of the convex hull of the points in the diagram in which every circumcircle of a triangle is an empty circle (Okabe et al. 1992, p. 94).2 Galapagos: Evolutionary solver for Grasshopper. based on genetic or evolutionary algorithm that applies the principles of evolution found in nature to the problem of finding an optimal solution to a problem.3

1 Wikipedia: https://en.wikipedia.org/wiki/L-system 2 Weisstein, Eric W. “Delaunay Triangulation.” From MathWorld-A Wolfram Web Resource. http://mathworld.wolfram.com/ DelaunayTriangulation.html 3 http://www.solver.com/genetic-evolutionary-introduction

Abstract Following our analysis of the existing site, it was important for the group to create an environment in which walkability and green spaces became the primary drivers. The intent was to have high connectivity within a high density city, in which people would be able to access the existing public transit system, as well as incorporation of walking paths for pedestrians. In studies of tissue samples from other cities, an interest emerged from the utilization of public green spaces, primarily driven from the WHO standard for a healthy city [9 m. sq.]. Densification was critical in the way a city could be analyzed at the building, the block and the neighborhood levels. At each stage. the relationship between programmes changes in their connection and proximity to each other. Certain rules were established in order to control these neighbour relationships. In order to generate growth, a branching system [L-system] was utilized for the purpose to distributing programmes on the site. From our primary analysis of the site, certain existing factors helped to control the growth of the city, including higher concentrations at determined residential and office centres. Usage of the L-system established a hierarchy of flow within programmes as well as allowing for the implementation of geometry based on positioned neighbours. 5

Logic The main ambition was to have an integrated, interconnected and dense city, having a mix-use programmeme allowing the habitants to reach all their necessities in a walkable distance. At the local hierarchy, the primary cells were defined by different typologies. R: residential, O: offices, C: commercial, A: amenities, N: networks, G: Open space. The spreading of cells in the selected patch was using a L-System, which defined its initial location. At regional level, the cluster formation (Blocks) was defined by the network analysis. In deed, all the network cells were connected using a Delaunay technique that defined the roads. To define buildingâ&#x20AC;&#x2122;s plot, the Voronoi technique was used for every cell. Furthermore, the site existing conditions were considered to set attractors points, which according to the distance to each block determined the density of the programmemes. In addition, the height and density of every cell were determined by the category of the nearest road (primary, secondary or tertiary). At global hierarchy, a library based on relation rules, was applied to define the interaction between the neighbour programmemes. This defined the final location of the typologies. All this hierarchies defined the spatial arrangement of the new patch in the Isle of Dogs.

Ambitions InterCITY

Integrated, interconnected, dense City Walkable Distance

Local Green

25% of open space

100.000 per

Increase xx%

Typologies (ROCANG)

Cluster Formation

Topological Rules

Network Analysis

L-System / Recursive Branch System

Delaunay / Veronoi

Typo Init. Location

Angles

Distance

Building

Footprint

Height

Roads

Profiles

Mix-Use

Neighbourhood

Relations rules

Library / Calibration system

Block

Density

Green Space

Height

%Person

Typo Fin. Location

Distance

Site Conditions

Attractor points

Density

Spatial Arrangement

Local Hierarchy

Regional Hierarchy

Global Hierarchy

WORKFLOW: Chapter 1

Network

Site conditions

Chapter 1 : Workflow

Start points

L System

R O C A N G

Axiom = O

Offices

Tube Stations

Boundary condition Road connections Axiom = R

EXISTING CONDITIONS

Main elements of the site are retained

START POINTS

Existing network nodes for growth

L-SYSTEM

Programmes distributed from start points

Patch Morphology R O C A N

Chapter 1 : Workflow New Network

Delaunay edges

Primary

Secondary

POINT DISTRIBUTION

Network nodes selected for triangulation

PRIMARY ROADS

Located per existing site conditions

Block Tertiary

SECONDARY ROADS

Connections between primary roads

BLOCK FORMATION

Tertiary connections for network on site

NETWORK SYSTEM

Width determined by typology of network

Network

Chapter 1 : Workflow

N N R

G G

N C

A A O

A O

A O O

G N

INITIAL NETWORK CONNECTION

The block is formed with programmes distributed within.

STREET TYPOLOGY

Primary, secondary and tertiary roads are given widths.

STREET TYPOLOGY

Sidewalk offset distances are established at each block.

Patch Morphology

Chapter 1 : Workflow

G G

C O

A A O

O C

A O

A O O G

VORONOI

Programmes are allocated space through voronoi patterning.

BLOCK

The voronoi is formatted to the new workable block area.

Programme AREA MORPHOLOGY

Programme voronoi cells are offset for distance between buildings.

Patch Morphology

Chapter 1 : Workflow

LARGE AREA if area of voronoi cell > 1000 sq.m:

1 midpoint of longest edge

AREA REDISTRIBUTION

Areas larger than 1000 sq. m. are reduced.

RULES

2 perpendicular edge

3 select larger area

Patch Morphology

Chapter 1 : Workflow

INSUFFICIENT AREA if area of voronoi cell < 200 sq.m:

1 find nearest neighbor

AREA REDISTRIBUTION

Areas smaller than 200 sq. m. are joined with a neighbor, then offset.

2 group areas together

3 determine hierarchy

RULES

Patch Morphology

Chapter 1 : Workflow

PROGRAM OUTLINE MANIPULATION

1 initial voronoi cell

CELL FORM

The angular geometry of the voronoi cells are interpolated into curves.

RULES

2 interpolated curve (D:2)

3 reduction of area + angles

4 maximum footprint

RESULT: INTERPOLATED CURVES

Reduction of extreme angles allows for more dynamic spaces.

Patch Morphology

Chapter 1 : Workflow

HIERARCHY OF PROGRAMS [in group] R O C A

ground

HEIGHT GENERATION FOR GROUPED PROGRAMS

max. height

PROXIMITY

Each programme locates the distance to the closest network.

HEIGHT + PROXIMITY

Ratios for each network type are applied to achieve programme heights.

3/4 of max. height

1/4 of max. height

grouped programs

RULES

Patch Morphology

FINAL AREAS

Workable area that can be used for height ratios.

Chapter 1 : Workflow

HEIGHT + PROXIMITY

Ratios for each network type are applied to achieve programme heights.

BUILT FORM

Maximum height that can be achieved within programme areas.

growth on site

branching system

L-System angle

15째

30째

gen 1

length gen 1

type

R O C A G N

residential office commercial amenities green space network

45째

L-SYSTEM: Chapter 2

Start Point

Chapter 2 : L-System Angles in Branching

RULES 1. Length [consistent] = 10 m

Angles within the branching system were tested along

2. Kill strategy = clash

with the clash strategy in order to locate the branches that would be killed off. The node diagram at the bottom of each test notes how many continuous branches occur with the maximum amount of connection points.

Left branch continues and right branch dies

For instance, the 45/30/15 angles allow for 9 nodes before the kill strategy comes into effect and one of the branches dies. This is crucial in terms of the L-system in that having 3 parameters [angle, length, type] creates for many instances of clashing and dying off of branches. As the L-system works heirarchically, the more continuous the branch, the more consistent the distribution of types.

ANGLES: 15 / 30 / 45

ANGLES: 45 / 30 / 15

ANGLE: 45

ANGLE: 30

ANGLE: 15

R= 37.96m R= 12.14m

Nodes = 4

Nodes = 9

Nodes = 6

R= 18.66m

Nodes = 6

Start Point

Chapter 2 : L-System START POINT

The start point for the L-system is an important factor in the types of growth that can be formed. On the site, existing conditions were used as start points with a controlled angle and length. A single start point was used to note the amount of generations the L-system needed to reach the extents of the site boundaries. Distribution of the amount of programme nodes were also calculated.

West DLR stop

The third row showing diagrams for Organization, represent two types of classication of the branches: major and minor paths. A major branch divided the organization systems, for instance, as noted in dramatic shifts in curvature as well as the branch outling the periphery. Minor branches were established if the branch continued along for 6 generations without dying. The start point was also tested as a multiple, in that two or three start points determined growth of the L-systems

Center Site division

on the site. The positions for these start points were located either through a division of the site longitudinally, usage of the existing DLR stops at the west boundary and usage of the two primary roads and where they connect to the site. It is important to note that where the single point only clashes with itself, the multiple start point is considerably more complicated as with increased generations, the clashing of the branches are unexpected. Two start points were located for the to continue further experiments. 23

Single Starting Point

Chapter 2 : L-System

START POINT

West DLR stop

Center Area centroid

East Site division

G20 Nodes:

479

G40 Nodes:

721

G20 Nodes:

524

G35 Nodes:

800

major minor

2 8

major minor

1 13

major minor

6 12

major minor

5 20

DISTRIBUTION

G27 Nodes:

737

ORGANIZATION

major minor

5 18

Multiple Starting Point

Chapter 2 : L-System

START POINT

West / Center DLR stops

Center Site division

East / West Site division

West / East Site division

North / South Existing roads

DISTRIBUTION 282

129

138

195 257 228

272

221

220 131 196

Nodes:

673

226

269

488

Nodes:

547

Nodes:

670

Nodes:

592

Nodes:

770

major minor

7 12

major minor

9 18

major minor

9 15

major minor

5 15

ORGANIZATION

major minor

7 11

Definition

Chapter 2 : L-System

L-systems were developed in 1968 by the Hungarian theoretical biologist and botanist, Aristid Lindenmayer, from the University of Utrecht. It was primarily used to model the growth processes of plant development, but also was able to be utilized in modeling the morphology of a variety of organisms1. Its formal grammar that could be used to understand morphology was based on a small set of rules to locally add details to a structure (for instance, the rule could be that at every end point on a tree branch, add two branches)2. The L-System starts with a axiom or seed, and with the set of rules, defines the next generation. On one hand, the system can be seen like a set of strings; where a collection of production rules can

Variables: A B

define the geometry (Diagram 1). On another level, the

Axiom: A

L-System acts as a branching network (Diagram 2),

Rules: (A = AB), (B = A)

were the angle and the length of the branches determine

Result:

the physical relationship and hierarchies between the

n=0:A

cells, like the anatomical organization of a tree. “Branch

n = 1 : AB

angles and the ratios of the length in sequential ‘mother

n = 2 : ABA

to daughter’ branches determine the effective leaf area,

n = 3 : ABAAB

and constraint the overall morphology of a tree.

n = 4 : ABAABABA

Within the project, this last method was used as a digital

n = 5 : ABAABABAABAAB

tool, to spread programmes and define its initial location.

n = 6 : ABAABABAABAABABAABABA

1 http://en.wikipedia.org/wiki/L-system 2 Cornell University, L-Systems 3 Michael Weinstock, The Architecture of Emergence. p.124

n = 7 : ABAABABAABAABABAABABAABAABABAABAAB Diagram 1: L-System as a set of strings

L-System herarchical relationship

Diagram 2: L-System as a branching network

Objectives

Chapter 2: L-System

The L-System was utilized mainly to spread and define the initial location for the different programmess: residential (R), offices (O), commercial (C), amenities (A), greenspace (G). In addition, a network cell (N) was added to the system to define the roads, ensuring continuity and connectivity within the site. The main reasons driving the the use of the L-System were: the capacity to control the flow of information, therefore its faculty to maintain the relations between the programmes; and its capacity to generate a complete mix of use (with some level of concentration), allowing the integration of the city. The topological relationship between the programmes was defined by a set of rules for the branching system, which in turn determined the programmes that generated the following two branches. In addition, the length and angle of the branches defined the distribution and the initial location for the typologies (Diagram 1).

Rules

Topological relationship

Angles

L-System

Distance

Initial Location Diagram 1: L-System logic

Setup

Chapter 2 : L-System

Rules The rules were defined according the relation of the typologies and possible interactions between them. - Offices generate two branches: (1) a new cell of offices to cluster the typology; (2) amenities, because can attract people during hours that offices are not used, avoiding zones without use at certain parts of the day. - Residential nodes create a Commercial cell, allowing the habitants to reach necessities within a walkable distance, and have proximity to other residential units. - Commercial nodes produce a Network cell, to ensure the connection with the users and a residential unit. grid, and an Office unit that needs to be connected.

- Networks generate a new cell to have a continuous

- Amenities create a Commercial and an Office cell to

generate services areas. - Green spaces produce a Residential cell allowing the inhabitants to reach green areas in a walkable distance and produce positive externalities to the dwellings. Length and Angle

R C

N N

Diagram 2: Rule set

The length of the branching system define the distance between the points A-B and A-C (Diagram 3), therefore, determined the distance and relation between B-C.

15o -15o

B A C

30O

-30O C

Diagram 3: Rule set

45O

X+2

X+1

the relation between them. On the other hand, the angle

30O

-45O C

Optimization of the system

Chapter 2: L-System

The optimization of the L-System was the main focus after

distance that enable users to reach every typology. The

the studying the results of the first experiments in order

angles were managed individually and with a range

to achieve coherent results. The set of rules was modified

between 0 and 45 degrees according to the relation

several times with differential weighting of parameters

between the origin and resultant typologies. A wider

until a final one was achieved. The logic was to have a

angle meant a larger separation between the resultant

proper proportion of each programme according to the

cells. For this reason each cell was considered a different

standards of the cities studied in the tissue samples.

branch angle according to its relation to the resultant unit.

Furthermore, the axiom (starting cell) was considered

The lengths of the branches followed a similar logic to

as the main unit of the branching network; if the system

analyse the relationship between the original cell and

began with a Residential or an Office cell, the growth

the resultant one. The distance was defined between

should have a bigger proportion of that typology. This is

0-200m, the maximum distance between 2 cells, in order

in reference to having a relation to the existing conditions

to achieve walkable distances.

of the site and the non-intervened patch of the Isle of

To evaluate the Galapagos result the distribution in the

Dogs (the left portion). For instance, as the north part of

site was analysed with the main ambition to achieve

the site was mainly offices, an Office axiom allowed for a

the spread of programmes with minimal distance

higher percentage of offices in this zone.

between network cells. Considering the high demand

To find the optimized configuration of angles and

of computational resources needed for the evolutionary

length for the L-System, an evolutionary algorithm was

algorithm the variables were constrained. Consequently,

used (Galapagos)1. The idea was to find the optimum

the angles were defined as 0, 15, 30 or 45 degrees,

branching system using the fitness criteria as the

and the length as 25, 50, 75, 100, 125, 150, 175 or 200

distance between the network cells. To evaluate this the

meters. A set of experiments with different variables

Delaunay Triangulation formed the connections between

was produced in order to optimize the system, with

all the network units, thus creating the blocks.

an emphasis on different axioms, angles, length, and

The Galapagos simulation permitted positioning of the

distances between N cells (fitness criteria). In the next

initial location for the programmes, prioritizing a walkable

pages its possible to see a summary of experiments with

1â&#x20AC;&#x201A; See vocabulary page for references

the different results and variables considered.

Axiom

Selected L-System

Optimization of the system

Chapter 2: L-System

Axiom

AXIOM R

O R C A N G ANGLES

15 15 30 45 30 X

DISTANCES

50 200 175 75 100 X

MINIMUN DISTANCES

MAXIMUN DISTANCES

202.96

RATIO

2.96

*Lack of points and non-uniform dispertion of programme over the entire plot

Axiom

Galapagos Test 01

Optimization of the system

Chapter 2: L-System

Axiom

AXIOM R

O R C A N G ANGLES

15 15 30 15 30 30

DISTANCES

100 125 50 50 100 125

MINIMUM DISTANCES

17.97

MAXIMUM DISTANCES

472.29

RATIO

272.29

*Non-uniform dispertion of programme over the entire plot

Axiom

Galapagos Test 02

Optimization of the system

Chapter 2: L-System

Axiom

AXIOM N

O R C A N G ANGLES

30 15 15 30 30 30 UPPER SIDE

DISTANCES

MINIMUM DISTANCES

25 50 75 50 50 50

12.42

MAXIMUM DISTANCES

728.95

RATIO

MANUAL

*Uniform distribution of programmes over the entire plot

O R C A N G ANGLES

30 15 15 30 30 30 LOWER SIDE

DISTANCES

75 50 25 50 50 50

Axiom MINIMUM DISTANCES

Selected configuration / L-System

6.06

MAXIMUM DISTANCES

519.74

RATIO

MANUAL

Optimization of the system

Chapter 2: L-System After several experiments the optimum configuration was

residences.

selected to develop the rest of the process. The axioms

The final fitness criteria used in the evolutionary solver,

used for both starting points were N to have a continuous

was optimized to find a distance of 125M between the

network with the existing site roads. The angles and

N cells. In this experiment a uniform distribution in the

length in both sides of the plot are different according

entire plot was found, however, the final evaluation was

to the main use in that area, thus the upper part of the

made quantifying the number of programmes per block.

site was focused in offices, therefore have more quantity

In cases where the number was below 3, new branches

of â&#x20AC;&#x2DC;Oâ&#x20AC;&#x2122; cells. The lower part was targeted to have more

were generated in problematic areas to continue growth.

Delaunay Triangulation Length

Fitness Criteria Formula

Ratio

Max. Min. N A

125

B Variable

Target ÂˇAprox. amount of points = 700 min. *Required distance between points = 100m

Calibration of the network cells (N)

Selected configuration / Delaunay

Optimization of the system

Chapter 2: L-System

Galapagos Distance Experiment Galapagos Distance 1

Fitness Criteria Dist. Between N (max:200)

Minimum Maximum 75

Axiom

2.968563

O 50

R 200

C 175

N 75

A 100

G x

O 15

R 15

C 30

N 45

A 30

Observations

Fix angles optimized by thinking relation between programs

Non uniforms distribution of N. All collected in East side

Evaluation

303.6

200 Distance 150 50

125

15 Angles 15 15

Fix minimum angles

High ratio and Non uniforms distribution of N. All collected in East side

Ratio 55.02

Axiom R

O 150

R 150

C 50

N 50

A 50

G x

O 45

R 45

C 45

N 45

A 45

G X

Observations Fix maximum angles

Medium ratio, low minimum dist. Spreading in 3/4 of the Evaluation patch.

202.96 305.46

2.968563 105.46

50 75

200

175 100

75 50

100 50

15 30

45 30

Fix angles optimized by thinking relation between programs Fix medium angles

High ratio, low minimum dist, high maximum dist, Non uniforms distribution of N. spreading: 1/2 ofAll thecollected patch in East side

50 9.84

503.6 358.8

303.6 158.8

200 50

150 50

125 50

15 45

15 30

15 45

15 30

X x

Fixminimum minimumdistance angles Fix

High ratio, ratio and uniforms distribution of N. Spreading All collected High HighNon maximum dist, low minimum, in in East side all the plot with gaps in the border

Dist. Between N (max:200)

16.6 85.1

255.02 338.47

55.02 138.47

150 100

50 100

45 30

45 15

45 30

X x

maximumdistance angles Fix medium

Medium ratio, low minimum dist. Spreading in 3/4 of the patch. Spreading good but almost without points

Distance 4 Dist. Between N (max:200) Angle&Distance (max:100)

14.14 19.52

305.46 297.96

105.46 197.96

75 100

200 50

100 50

50 75

30 15

X x

Fix&medium angles(50-200) Free angle free distance

High ratio, low minimum dist, high maximum dist, 1/2with of the patch Spreadingspreading: in all the plot gaps in the border

Angle 1 Angle&Distance Dist. Between N (max:200)

9.84 12.19

358.8 270.9

158.8 70.9

50 75

50 100

30 15

45 15

30 45

Fix minimum distance Free angle & free distance (50-200)

High ratio, High maximum dist, low minimum, Spreading in all the plot gapspoints in the border Notwith enough

Angle 2 (max:200) Angle&Distance Dist. Between N (max:125)

85.1 5.41

338.47 321.23

138.47 196.23

100 50

100 25

100 75

100 50

45 30

30 15

Fixlimitated medium between distance 25-175 Distances

Spreading butenough, almost without Minimum distancegood not big Spread points in all the site

Distance 2

Dist. Between N (max:200)

Experiment Distance 3

Fitness Criteria Maximum Dist. Between N (max:200) Minimum 16.6 255.02

1 Distance 4

Dist. Between N (max:200)

75 14.14

Distance Angle 1 2

Dist. Between N (max:200)

Distance Angle 2 3

503.6

Angle&Distance (max:100) Distance 5 Dist. Between N (max:125)

19.52 40.54

297.96 412.91

197.96 212.91

100 125

50 125

75 50

x 50

30 15

15 30

x 30

angle free distance (50-200) Fix Free angles, free&distances between 50-125

Spreading in only east part of the site, without points in the Spreading in all the distance plot with between gaps in the border west side. Good points

Angle&Distance Distance 6 Dist. Between N (max:200)

12.19 17.971

270.9 472.29

70.9 272.29

R N

75 125

100

100 50

50 100

x 125

45 15

15 30

45 30

x 30

angle free distance (50-200) Fix Free angles, free&distances between 50-125

good distribution, butNot notenough enoughpoints points

(max:125) Angle&Distance Dist. Between N (max:100)

5.41 8.44

321.23 283.23

196.23 183.23

R N

50 75

25 50

75 50

x 50

30 15

15 30

x 30

Distances between(50-125) 25-175 Free anglelimitated & free distance

Distance 5 Dist. Between N (max:125) Angle&Distance (max:200)

40.54 6.57

412.91 254.57

212.91 54.57

R N

125 50

50 75

15 45

15 30

30 45

Fix Free angles, free&distances between 50-125 angle free distance (50-125)

Spreading in only east part of the site, without points in the distance points spreadingwest in allside. the Good plot, some gapsbetween in the border

17.971

472.29

272.29

125

100

125

Fix angles, free distances between 50-125

good distribution, but not enough points

Table / experiments Distance 6 Dist. Between N (max:200)

Minimumindistance not big enough, Spread in all the site spreading all the plot, some gaps in the border

Angle&Distance (max:100) Lower Patch Dist. Between N (max:125)

8.44 6.06

283.23 519.74

183.23

N N

7575

5050

5025

5050

5050 30 30 15 15 15 15 30 30 30 30 30 30 Selected Free angle & free distance (50-125)

spreading in all the plot, some gaps in the border

Angle&Distance (max:200) Upper Patch Dist. Between N (max:125)

6.57 12.42

254.57 728.95

54.57

N N

5025

5050

7575

5050

5050 45 45 15 15 30 30 30 30 45 45 30 30 Selected Free angle & free distance (50-125)

spreading in all the plot, some gaps in the border

Whole Patch

Dist. Between N (max:125)

221.92

Lower Patch

Dist. Between N (max:125)

6.06

519.74

30 Selected

Upper Patch

Dist. Between N (max:125)

12.42

728.95

30 Selected

Whole Patch

Dist. Between N (max:125)

221.92

Table / evaluation of the results

202.96

Ratio

Angles

Determining Density

Chapter 2: L-System

One of the main ambitions of the project was to achieve a density of 100,000 persons in a patch of 1.030.895 square meters. To distribute the population and define the density of each cell, the population was divided according to the ground area of each block. In addition,

Boundary Offices area

important points in the actual site were selected recognizing some main condition (site attractors). For

Boundary

each of these selected points, an attraction factor per typology was added. This factor determined the density (number of people) for every cell in each block.

DLR Station

In the Northern part of the site the high concentration of

Boundary

offices act as an attractor point, therefore has a higher office factor which would attract mainly offices. In the West side, the DLR stations emerge as main connection

Boundary

points, attracting commercial and offices cells. In the South part a main residential point was recognised according to the existing site conditions there and has a

DLR Station

higher factor for R units. In the east side, the boundary Boundary

condition to the Thames river was divided in 6 points and considered as a positive externality for dwellings.

DLR Station

For each block the 3 closest attractors were considered,

Boundary

the summation of its factors determined the amount of people for every cell. This process can be seen in the

Residential Area

following diagrams that show the situation for three selected blocks.

SITE ATTRACTORS

Defining key points from the site to be used as main attractors.

Determining Density

Chapter 2: L-System

R:1.0 C:1.5 O:2.5 A:0.7

All existing site conditions to influence density.

6 96

102

143

151 144

101 100

149

150

162 163 30 161160

98 99

152 146

38 147

36 39 42

R:2.5 C:0.5 O:0.5 A:0.2

34 35

105

SITE ATTRACTORS

R:2.5 C:0.5 O:0.5 A:0.2

37 41 40

R:2.5 C:0.5 O:0.5 A:0.2

Mapping programme density factors based on site attractors.

8 5

R:2.5 C:0.5 O:0.5 A:0.2

102

101 100

104

105

106 126

143

151 144

98 99

142

149

150

162 163 30 161160 34

29 27 28 32 31

24 23

172

R:2.5 C:0.5 O:0.5 A:0.2

172 11

45 46 148 44 153 145 154 49 106 155 3 125 124 47 142 73 48 2 134 126 135 141 43 72 50 51 103 127 71 121 120 80 75 119 79 166 164 74 118 76 81 82 53 123 122 165 130 137 77 167 83 156 157 136 117 169 131 128 84 54 129 78 52 168 110 109 107 171159 158 170 112 55 56 133 85 108 115 132 111 87 88 139 61 57 89 140 116 91 138 60 90 58 R:2.5 86 114 93 94 113 59 C:0.5 R:1.0 92 95 0 62 64 O:0.5 C:1.5 63 67 70 1 A:0.2 O:2.5 69 68 104

A:0.7

SITE ATTRACTORS

8 5

R:1.0 C:1.5 O:2.5 A:0.7

29 27 28 32 31

172

24 23

172 11

R:0.5 C:1.5 O:3.0 A:1.0

152 146

38 147

153 145 154 155 3 73 2

141

36 39

41 40

42 148

125 43

124

135

134

46 49 48

50 51 121 120 75 119 79 166 164 74 118 76 81 82 53 123 122 165 130 137 77 167 83 156 157 136 117 169 131 128 84 54 129 78 52 168 110 107 171159 158 109 170 112 55 56 133 85 108 115 132 111 87 88 139 61 57 89 140 116 91 138 60 90 58 86 114 93 94 113 59 0 62 92 95 64 63 67 70 1 69 68 103 127

BLOCK EXAMPLES

Mapping programme density percentages based on site attractors.

Determining Density

5 97

104

101 100 105

149 143

151 144

98 99 102

4 150

162 163 30 161160

8 7

29 27 28 32 31

172

24 23

172 11

R:0.5 C:1.5 O:3.0 A:1.0

152 146

38 147

36 39 42 148

Chapter 2: L-System R:2.5 C:0.5 O:0.5 A:0.2

34 35

BLOCK 1 [green]

41 40 45

Defining the three attractors to determine programme density factors.

R:1.0 C:1.5 O:2.5 A:0.7

6 96

102 104

101 100 105

126

143

151 144

98 99

106

R:1.0 C:1.5 O:2.5 A:0.7

150

142

152 146

38 147

153 145 154 155 3 73 2

103 127

141

A:0.7

72 80

37 41

148

125

124

135

134

101 100

104

49 48

50 51 121 120 119 118 122 123 137 156 157 136 117

Defining the three attractors to determine programme density factors.

105

106 126

143

151 144

98 99

142

149

150

102

162 163 30 161160 34

13 7

29 27 28 32 31

24 23

172

75 79 166 164 74 76 81 82 53 165 130 77 167 128 83 131 169 84 54 129 78 52 168 110 107 109 171159 158 170 112 55 56 133 85 108 115 132 111 87 88 139 61 57 89 140 116 91 138 60 90 58 86 114 93 94 113 59 R:1.0 92 95 0 62 64 C:1.5 63 67 70 1 O:2.5 69 68

BLOCK 2 [blue]

172 11

149

162 163 30 161160

29 27 28 32 31

24 23

172

R:2.5 C:0.5 O:0.5 A:0.2

153 145 154 49 106 155 3 125 124 47 142 73 48 2 134 126 135 43 50 51 103 127 141 72 71 121 120 80 75 119 79 166 164 74 118 76 81 82 53 123 122 165 130 137 77 167 83 156 157 136 117 169 131 128 84 54 129 78 52 168 110 107 109 171159 158 170 112 55 56 133 85 108 115 132 111 87 88 139 61 57 89 140 116 91 138 60 90 58 86 114 93 94 113 59 0 62 92 95 64 63 67 70 1 69 68 65

172 11

152 146

38 147

153 145 154 155 3 73 2

103 127

141

A:0.7

36 39

R:2.5 C:0.5 O:0.5 A:0.2

41 40

42 148

125 43

124

135

134

46 49

50 51 121 120 75 119 79 166 164 74 118 76 81 82 53 123 122 165 130 137 77 167 83 156 157 136 117 169 131 128 84 54 129 78 52 168 110 107 109 171159 158 170 112 55 56 133 85 108 115 132 111 87 88 139 61 57 89 140 116 91 138 60 90 58 R:2.5 86 114 93 94 113 59 C:0.5 R:1.0 92 95 0 62 64 O:0.5 C:1.5 63 67 70 1 A:0.2 O:2.5 69 68 80

BLOCK 3 [red]

Defining the three attractors to determine programme density factors.

Determining Density

Chapter 2: L-System

Amenities 9%

Amenities

Residential

Amenities 8%

12% PERSONS PER PROGRAM 18% Residential 42%

Ofﬁces 30%

BLOCK 1 [green]

424p

424p 193p 308p 197p 93p 328p 4 PERSONS PER 142 PROGRAM 131p BLOCK 2 [blue]

92p

142

109197p

193 per

197 per

165 per

308 per

328 per

230 per

93 per

92 per

72 per

131 per

165p

230p

72p

230p

72p

BLOCK 3 [red]

Programme density factors at each block.

8891 sqm

424 per

395p

Programme density factors at each block.

395p 165p 328p 92p 395 per

Comercial 19%

109 197p 395p 193p 131p308p 93p 328p 165p 92p 230p

109

Ofﬁces 27%

Comercial 26%

93p

7709 sqm 131p

308p

142

424p 193p 4 PERSONS PER PROGRAM

Programme density factors at each block.

10491 sqm

C Ofﬁces 44%

Comercial 19%

72p

Residential 46%

L-System

distribution of programs

Green Space 1. global

any block with less than 2 programs are automatically made into green space

2. regional

all green space types [programs] as distributed by the L-system

3. local

leftover space after large program areas are subdivided are made into green space

O P E N S PA C E :

Chapter 3

Green Areas

Chapter 3: Open Space Once the network programme nodes are connected together through the Delaunay triangulation, it is evident that some blocks have a smaller distribution of programmes than others. In order to apply the Voronoi pattern to the block and subdivide the area, the points (or sites) necessary must be greater than 1. Since each cell in the Voronoi diagram encloses the location of the point (site), the cell itself is comprised of all the points on the plane that are closest to itself than any other. If there are no other points to quantify this distance from, the pattern cannot be applied to that block. For the limitation of buildings with an extremely large footprint, any block with less than 2 programmes were automatically converted to public green space. This was the first step in determining the distribution of green spaces apart from the L-system.

Area with <2 pts. is unable have the Voronoi pattern applied.

VORONOI PATTERN

Distribution of programme is turned into workable area on blocks.

GREEN SPACE [global]

Blocks lacking a minimum amount of pts. are converted to green space.

RULES

The entirety of the block is used as green space.

Green Areas

Chapter 3: Open Space After the global determination of green spaces due to lack of the number of required programmes, green space is next located by the L-System. The branching system has calculated the distribution onto the site due to existing attractors as well as programme relationships. The Voronoi diagram was used to parcel out the division of the blocks for each programme. All Green space nodes and resulting cells are located.

The L-System distribution of G programs.

Regional green spaces are located within voronoi cells in blocks.

G G

GREEN SPACE [global]

Blocks lacking a minimum amount of pts. are converted to green space.

GREEN SPACE [regional]

All green space cells as distributed by the L-system are located.

RULES

Green Areas

Chapter 3: Open Space The third level of determining locations of green spaces concerns the site at the regional scale. Due to the nature of the Voronoi diagram, the distance between the locations of the points (sites) are measured in terms of creating the cells. This results in certain programmes receiving large areas as footprints. In order to control the footprint, the remaining parcelization is measured in terms of area. Any area with a quantity larger than 1,000 square meters is located and reduced for a more workable space. The division of the area occurs by connecting a line between the midpoint of the largest side of the cell to the midpoint of the opposite edge. The larger of the two resultant cells is utilized for the respective programme. The tertiary regional green space is considered as the remaining leftover cell from division of the large areas. In this strategy, both the footprint of the buildings are managed while attaining further green space, thus diversifying the neighborhood. Breakdown of large areas [>1000 sq.m.]

largest length is split in two

LARGE Programme AREAS

All areas derived from the voronoi larger than 1000 sq.m. are located.

LARGE Programme AREAS

All areas derived from the voronoi larger than 1000 sq.m. are split.

RULES

Remainder becomes green space

program area leftover

Green Areas

Chapter 3: Open Space Once the three levels of locating public green spaces has been determined, the next step was to combine adjacent areas into singular larger parks. In this way, the city would begin to be manipulated in terms of the programme influencing the already established network. For instance, two green spaces across a tertiary road could combine and redirect traffic around the park. Similarly, pedestrian paths within the block itself could be absorbed into the park for a reduced network and growth of green space.

Initial green spaces [block and cell]

ALL GREEN SPACES

Compilation of all green spaces, including connections at global level.

GREEN CITY

Merging of green spaces to create continuity at the global/regional.

Combined green space [regional]

RULES

L-System

distribution of programs

Network 1. primary

2. secondary

3. tertiary

Height of bldg =

distance to street 0.5

distance to street 1.5

distance to street 2

+ 12

NETWORK: Chapter 4

Network points and Block formation

NETWORK NODES

Distribution of network points as per the L-system.

ADDITIONAL NETWORK NODES

Division of the site boundary into 47 additional network points.

Chapter 4: Network

COMPILATION

The additional points allows for increased connectivity at the boundary.

Network points and Block formation

Chapter 4: Network

The network points are distributed on the site as per the L system. To improve connectivity at the edges the boundary of the site was divided with points equidistant at 100m. Using the Delaunay triangulation method points were connected. Quadrilateral blocks were formed through inducing a rule of eliminating one shared edge. Any triangle with an area less than 100 sq.m. was merged with the neighbouring block.

Delaunay triangulation

Removal of shared edge

Quadrilaterial block formation

Triangles with less than 100 sq. m. are merged with a neighboring block. +

DELAUNAY TRIANGULATION

The Delaunay triangulation is used in order to connect all the points.

RULES

BLOCKS

By adding two adjacent triangles together, block formation occurs.

N e t w o r k Ty p e

PRIMARY ROADS

Connecting the primary network with the neighbouring primary roads.

Chapter 4: Network

SECONDARY ROADS

Secondary roads connect the primary roads at every 300m.

TERTIARY ROADS

Boundaries connecting secondary roads are defined as tertiary roads.

N e t w o r k Ty p e

Chapter 4: Network

The primary road network on the site was defined with a connection to the existing primary nodes from the left half of the Isle of Dogs. Each primary road was placed no more than 600m apart from each other, in order to optimize connectivity and flow. The primary network defined the neighborhood or region. Secondary road networks were then formed with connections to the primary network, the distance limited to no more than 300 m apart from each other. This secondary network thus formed the cluster. At the third level is the block formation. The block boundaries were connected to the secondary roads to form the tertiary networks.

Primary [neighborhood]

ROAD NETWORK

The established road network defined the connectivity to the blocks.

Secondary [cluster]

Tertiary [block]

RULES

Hierarchy of Roads

Chapter 4: Network

The population density is directly proportional to the road type. The width of the roads were defined by the amount of traffic it had to facilitate and the flow of people through the site. The roads were provided through offsets from the centre line of the network node, which reduced the block size through width of street and sidewalk. The pedestrian pathways increased from 1.5m for tertiary network to 4.5m for primary network, to accommodate the pressure of the population. Parking spaces were

primary secondary tertiary

provided at both the primary and secondary roads along the pedestrian pathways. Morphology of the built form is influenced by the network in that the height of the building also defined the type of the road. The closer the building to the primary road the higher it was allowed to be in order to accommodate the respective density. To define the height of the buildings with respect to the road widths a specific rule was introduced where a ratio of height to the street widths was considered. Considering our sample tissue analysis, an attempt was made to maintain the range of the ratio between 1.5 to 2.5.

NETWORK

Primary, secondary and tertiary roads are established.

NETWORK

Primary, secondary and tertiary roads types with road widths.

Hierarchy of Roads

Chapter 4: Network Street Width (S) Height of Building (H)

: 27 m : 55 m

Ratio of S/H

: 2.03

55 m

Primary Road

27 m 4.5

4.5

Street Width (S) Height of Buildings (H)

: 15 m : 30 m

Ratio of S/H

: 2.00

30 m

Secondary Road

15 m

3.0

4.5

3.0 Street Width (S) Height of Buildings (H)

:9m : 15 m

Ratio of S/H

: 1.66

15 m

Tertiary Road

2.0

3.0

2.0

RULES

H e i g h t To w a r d s N e t w o r k Ty p e

Chapter 4: Network

Differentiation in road widths with respect to the network type facilitated good connectivity to each block. Each block contained cells, essentially programme areas, formed by Voronoi patterning. These programmes derive height through the measurement of two specific parameters, the proximity of the centroid of the cell to the network and the type of network itself. This strategy allowed us to have differentiation in building heights in direct relation to the type of network the programme situates itself near. In terms of flow, this meant that the population density would be higher near the primary roads (with wider streets and pedestrian pathways) and would reduce as it approaches the tertiary roads.

NETWORK

Offset widths are applied to street types, reducing the block size.

NETWORK + Programme

Programmes derive height by location and proximity to network types.

G E O M E T R Y: Chapter 5

Patch Selection

Chapter 5: Geometry All the blocks on the site were numbered (as each one is different from the next) and 3 adjacent blocks were

172 9

R:1.0 C:1.5 O:2.5 A:0.7

150

98 99

office concentration near Canary Wharf and DLR tube

149

151 144

143 38

36 39

35 37 41

station) defined the density of each block based on the

Comercial 19%

R:2.5 C:0.5 O:0.5 A:0.2

Residential 46%

The three closest attractors points are considered from residential attractors had higher residential density, the factor considers other programmes to support the main programmes [Residential and Office typologies] in order to have a mixed and integrated system. These factors

Comercial 19% Offices 27%

were then used as a measure to divide the number of

Residential 46%

people required for each programme with respect to the block size.

Offices 27%

Comercial 19% Offices 27%

148148 Residential 46%

Offices 27%

given factor. the centre of the block. Although the block closest to the

Offices 27%

R:2.5 C:0.5 O:0.5 A:0.2

40 42 152 147 101 100 45 46 146 148 104 105 44 145 153 49 154 106 155 3 125 124 47 142 73 48 2 134 126 135 43 50 51 103 127 141 72 71 121 120 80 75 119 79 166 164 74 118 76 81 82 53 123 122 165 130 137 77 167 83 156 157 136 117 169 131 128 84 54 129 78 52 168 110 109 107 171159 158 170 112 55 56 133 85 108 115 132 111 87 88 139 61 57 89 140 116 91 138 60 90 58 86 114 93 94 113 59 0 62 92 95 64 63 67 70 1 69 68 102

attractor points on the site (based on the boundary, the

162 163 30 161160 34

selected as a patch for testing of geometry. The existing

Amenities 8%

24 23

29 27 28 32 31

8 5

172 11 10

148

153153

153

147147

5920 sqm

2647 sqm

5920 sqm

263 per

118 per

337 per

110 per

49 per

141 per

153 per

69 per

197 per

48 per

22 per

62 per

147

Cell Formation

Chapter 5: Geometry

The programmes enclosed within each block, are

the varieties of road types, which would allow testing of

bounded

Voronoi

all the programmes in response to network. The voronoi

patterning. Each block is given an offset depending upon

patterning played a major role in provided differentiation

the type of road (Primary, Secondary, Tertiary) along

of cell size in each block. This was achieved due to various

the boundary of the block. The boundary of the block is

parameters contained within the block, for example, the

considered as the centre line of the road type, shaping

number of programme points, the size of the block and

the network. The patch was selected as it consisted of all

the shape of the block (boundary condition).

within

certain

space

through

O C

R A R

N R

Network widths are determined based on typology.

C G N

ROAD OFFSET

Network boundaries defining blocks.

R C

L SYSTEM PROGAMS ON SELECTED PATCH

R C

C R

VORONOI

Programmes are allocated space through voronoi patterning.

Cell Formation

Chapter 5: Geometry

Every cell in the block was given an offset of 1.5 m

having areas of 1000 sq.m and above were reduced to

internally to define the maximum footprint size for that

half of its size and the larger part of the two was used

particular plot. The resultant cells were then analysed with

to allocate the respective programme closer to the

respect to their sizes. Cells having areas 200 sq.m and

maximum number of neighbours. This strategy facilitated

below were merged with their immediate neighbouring

in eliminating formations of large masses of buildings.

cell having maximum area. This strategy was adopted to

The efficient range for footprint was thus considered

avoid extremely small footprints with tall buildings. Cells

from 200 - 1000 sq m.

CELLS

Merging of cells

Splitting of cells

RULES

N O

C A

A O

C R

R N R

R C

G N R

CALIBRATING AREAS OF ProgrammeS

Programmes with large and small areas are identified.

CALIBRATING AREAS OF ProgrammeS

Programmes with low areas are merged with the neighbouring cells.

CALIBRATING AREAS OF ProgrammeS

Programmes with large areas are subdivided to reduce footprint.

Density

Chapter 5: Geometry

After calibrating the cells in each block and locating

Certain area requirements for programmes [residential

green space requirement was divided into two parts,

the programmes, the estimated area requirements are

and green spaces] were calculated on the basis of

primarily as local green space in each block consisting

applied for each programme with respect to density.

minimum standard area requirements and proximity

of 25% of the minimum required green space and public

First, the size of the patch defined the population density.

to commercial, offices, amenities nodes by means of

open space consisting of the rest 75%. Amenities were

Note the population density itself was determined

approximation per person. According to WHO [World

broken down into leisure and public utilities, respectively,

in respect to the attractor factors defining the area

Health Organisation] standards, minimum green space

in order to differentiate the distribution of amenity nodes.

requirements for that particular programme and block.

requirement per person is estimated to be 9 sq.m. This

Density

O C O

7614 sq m

C 19 % 1614 people 1614 sq mt 1614 people 1 sq mt per personC 19 % 1 sq mt per person

5861 sq m

R R

R 46 % 775 people 19375 sq mt R 46 % 775 people 25 sq mt per person 25 sq mt per person

R A

7614 sq m

2669 sq m

G N

Density

2669 sq m

O 27 % 435 people 6525 sq mt O 27 % 435 people 15 sq mt per person 15 sq mt per person 5861 sq m A 8% 129 people 516 sq mt 8% 129 people 4 sq mt per personA 4 sq mt per person G = 2.3 x 1614 = 3712 sq mt G = 2.3 x 1614 =

19375 sq mt 1614 sq mt 6525 sq mt 516 sq mt

3712 sq mt

REVISED Programme AREAS

Revison based on rules of the minimum / maximum areas of cells.

DENSITY

Calculations of programme type densities per block.

Height

Chapter 5: Geometry

Due to the nature of the Voronoi pattern, cells in each

to the neighboring block. Each cell was mapped with

patch had many acute angles. In order to provide better

respect to proximity to network type and its distance

efficiency of the use of space, a rule enabling a curved

from the centroid of the cell. The height of the built form

edge was introduced. This strategy helped us in avoiding

was defined by these two parameters. This strategy was

negative spaces formed by the voronoi patterning, in

initiated to achieve differentiation in the heights of each

which there was difficulty in usage. If the block did not

built form in relation to proximity to the road type.

Tested: Difference in curve area based on quantity of points

3 point cell Area: 400 sq. m

Interpolated Curve [D=3] Area: 210 sq. m

4 point cell Area: 400 sq. m

Interpolated Curve [D=3] Area: 271 sq. m

have certain programmes its density was balanced over RULES

N O

R A

O C

O A

R A

R R R

G N

N R

RESULT: INTERPOLATED CURVES

Reduction of extreme angles allows for more dynamic spaces.

PROXIMITY

Each programme locates the distance to the closest network.

HEIGHT + PROXIMITY

Ratios for each network type are applied to achieve programme heights.

Geometry

Chapter 5: Geometry

The footprint of the built form was defined by the density required. If the desired density was low and the height provided was high, the cell tried to maximize footprint in order to achieve that height. In cases where cells

FOOTPRINT if density is less the footprint of the building is reduced to half O O

with respect to hierarchy of programmes, to confirm that

lower floors and have access to the street.

O C

HEIGHT GENERATION FOR GROUPED PROGRAMS C

footprint achieved due to interpolating curves

footprint as per density requirement

O A

1/4 of max. height

grouped programs

A R R R

Programmes achieving hierarchy when merged / shared cells.

Programme ALLOCATION

3/4 of max. height

R R

max. height

RULES

O A

ground

RULES

R O C A

consisted of two programmes, another rule was induced the programmes like amenities and commercial acquired

HIERARCHY OF PROGRAMS [in group]

G R

BUILT FORM

Desired density achieved with the programmes.

MORPHOLOGY OF PATCH

Geometry achieved after extruding the programmes.

Library

Chapter 5: Geometry While the network height equations help to determine the profles along the roads of the site, it became important for the group to establish geometry rules based on programmematic relationships. This was the second layer of manipulation and rulesets that could be applied to the location determining L-system distribution of programmes. Where the L-system achieves branching through heirarchy, set up by preconceived rules [R -> C, A, for example], it proved interesting to not only look at the flow of information vertically, but also horizontally. In this configuration, the location of the programme was important in a contextual basis, mainly itâ&#x20AC;&#x2122;s geometrical properties would be influenced by its neighbors. The cutoff for looking at all neighbors is possible through the

boundaries set up by the block formations. The main intent behind this new level of geometrical influence is driven by our understanding of each â&#x20AC;&#x2DC;buildingâ&#x20AC;&#x2122; not simply standing by itself, but establishing a

consistent relationship with its surrounding. Residential buildings would try to bond, or get closer to each other, thus maintaining certain shared properties. Green C

space became another way to tie cells and programmes

together, so that a new level of private green space could be located within the block. Similarly, programmes R

Cross branching relationship 64

could attract or repel each other within their respective boundary of the block.

Library

Chapter 5: Geometry

To ensure that the geometry has a response to the L

between the two programmes. For example, when

system, both in hierarchy as well as spatial position with

residential and residential cells come together they are

respect to the closest neighbour, a catalogue of rules

connected at the top to form a common green space to

[Library] was prepared between one programme to the

facilitate the density. The Library was initiated to optimise

other neighbouring programme. The rules were defined

the use of information provided by L system, with an

considering the final aim of the project, the integrated,

understanding of programme to programme adjacency.

RESIDENTIAL + RESIDENTIAL R

1. R + R remain in place. 2. Create 1 FL green space at the top floor of lower height R.

interconnected and walkable city, and the relationships

OFFICE + COMMERCIAL O

O-C

R-R

1. O + C remain in place. 2. Create O connection between O + C, at height of C.

RESIDENTIAL + COMMERCIAL R

R-C

1. R remains in place. 2. Shift C to share adjacent side with R.

LIBRARY RULES APPLIED

Rules from the library are applied to the neighbouring programmes.

LIBRARY RULES

Local Green Space

Chapter 5: Geometry

After applying the library to the built form the patch

All the combined green spaces in the patch were then

was analysed to optimize local green space. The areas

checked if they met the 25% standard requirements of

of programmes larger than 1000 sq.m. were reduced

green space per person [9 sq m / person].

and one half of it was converted to green space on the ground. The library allowed for the inclusion of additional green space at various levels as a part of the rules.

Amenities

Leisure

Public Utilities

Restaurants Cinema Theatre Pubs

Schools Hospitals Fire stations

LARGE AREA if area of voronoi cell > 1000 sq.m:

1 midpoint of longest edge

CALIBRATING LOCAL GREEN SPACE

Smaller area portions of reduced programmes made into green space.

RULES

perpendicular edge

select larger area for program and other half becomes green space

C R I T I C A L A N A LY S I S :

Chapter 6

Starting point

Chapter 6: Critical Analysis Start Point / Boundary Distribution of points proved to be an issue further along, since the L-system was restricted to the boundary of the site and much of the area at the periphery had no points. This greatly limited the application of the Delaunay triangulation in terms of connections of N nodes at the boundary, and later the Voronoi diagram subdivision. One way that the group tackled this problem was subdivide the boundary of the site into segments of 100 meters with a network node at each segment, adding 47 more points to the site. This allowed for a clean connection for roads at the boundary, however, in terms of distribution, this was still problematic. An improved approach would have been to not simply use the siteâ&#x20AC;&#x2122;s area and contour as the limitation for the growth of the L-system, but rather, extend the border. While we may have achieved a lot of branches that would need to be manually cut off, distribution of points would still be able to occur very close to the edge of the site. Using this method would have created for less blocks to form without the required number of programmes [negating a secondary rule for conversion of the respective blocks to green space].

Distribution

Chapter 6: Critical Analysis

The reasoning behind usage of the L-system was that

then programme applied secondary, the group aimed

In terms of programme distribution, we achieved certain

if we managed to optimize the factors within it, then

for a different approach. The system would be treated

types of programme attraction and repulsion. For

each programme would be spatially located within the

as parts to a whole, where each programme was

instance, amenities and green space were the most

site. This meant that the L-system would cease to be a

weighted in terms of the neighbors they connected to

widely spread out in terms of distance to each other.

diagram, and instead would act as a topological map.

within a heirarchy. In this way, we achieve first the node

Commercial nodes located themselves towards the

Having multiple start points meant that distribution was

connectivity diagram which allows for the axial map and

center of the site, while clumping of nodes was seen

differentiated between the North and South halves of the

road network to emerge from. The problem became that

in the offices and residential distributions. The network

site. Thus, the L-system is run to favor a higher percentage

the node connectivity diagram was only that, a diagram.

node was noted to occur in curve-like formation, but

of Office nodes at the North half while Residential nodes

The way that the diagram became a map was from the

was also distributed across the entirety of the site. This

are preferred for the lower.

basis that distance was an important factor in positioning

followed our initial studies in that residential and office

Where the traditionalist attitude toward city design stems

within the branching system. It is essentially the space

nodes would attract each other while other programmes

from the idea that roads need to be first determined and

syntax process in reverse.

like amenities did not need to locate themselves near each other.

Amenities

Commercial

Green Spaces

Network

Offices

Residential

L-System

Chapter 6: Critical Analysis

The branching network determined the initial location

programmes.

of each programme and distributed these on the site,

Regarding the digital development, the use of it was

allowing for a complete mix use and the inclusion of

limited for the high demanding computational process.

the network as a main fitness criteria to accomplish a

This situation constrains the variables utilized within

walkable city. The main ambitions of the system were

the system and the result is more restricted. Therefore,

achieved, however in analysis of the urban process and

the computational result was not necessarily the most

the final result, it can be noted that the system has more

optimized result and needed further manipulation to

potential. The decisions of combining it with the library to

achieve certain parameters. Probably with more time

realize the geometry limited the results; nevertheless, it

the computational tools could have been tweaked to

was a conscious decision to apply geometry based on

be further optimise certain factors. Nevertheless, we

position. The goal was that outcomes could be obtained

understood the prospective of the tools as an alternative

applying the same system at different hierarchies to

method [or a part of a method] to develop the city.

reach the 3 dimensions. This can be illustrated in applying the L-System at the unit level, which would spread

R 1bed

the residential buildings as 1 bedroom, 2 bedroom or

R 2bed

R 3bed

R 2bed

3 bedroom apartments, or even applying the system more intricately if distributing the programme inside the apartments. One of the main characteristics of the branching

R 1bed R 1bed

R 2bed

R 3bed

R 2bed

R 1bed

sets already established. Hierarchy was not considered

A R 1bed

R 2bed

This topological relationship could be considered for the organization of the blocks or the relation between the

R 3bed

R 2bed

R R 1bed

O C

to be studied as the result of each succeeding generation where each of them has a different hierarchical level.

R 2bed

system, hierarchies, was not exploited because this was considered to distribute on the site based on the rule

R 2bed

O R

R R

Connection

Chapter 6: Critical Analysis

Delaunay Triangulation The Voronoi diagram and the Delaunay triangulation are

both geometric structures, and are closely linked together.

triangulation worked quite efficiently in order to try

The criticism could be made that utilization of the

Each patterning technique was used specifically within

and connect all the Network nodes distributed by the

Delaunay triangulation introduced a different system

our distribution for the purposes of deriving relationships

L-system. Within the primary tests, ratios between the

following the usage of the L-system. However, the

based on final positioning of types [programmes].

programmes were analyzed to try and achieve optimum

L-system was primarily a distribution method within the

The groupâ&#x20AC;&#x2122;s intent was to first use the Galapagos

quantities of the respective programmes. For instance,

context of the site. In order to begin to associate geometry

plugin to try and find the fittest angles and lengths of

Residential nodes attracted Amenities and Green

with the programmes, the Delaunay functioned efficiently

each programme [Residential, Offices, Commercial,

Spaces, in the heirarchical branching. The Delaunay

in linking the spatial position of the Network programme

Amenities, Green Space and Network] in the branching

attempted to link all the Network nodes together based on

in terms of creating blocks.

system. Once this is achieved, the exact location of each

proximity and minimal spanning. The distance between

One of the issues with the Delaunay triangulation which

programme is also considered the fittest, and is further

each connection road from node to node was specified

needed to be sorted out

used to delineate space.

to be less than 300 meters, per our previous studies of

though the L-system attempted to even out distribution

Network topological connectivity diagram

Delaunay Triangulation using Network nodes

O G

O N

R N

N C

R N

G R

L-system distribution of types [programmes]

was the distribution. Even

walking distances.

Delaunay

the

connectivity,

network

terms

R C

Connection

Chapter 6: Critical Analysis Voronoi Diagram

through relatively optimized angles, branch lengths and

Usage of the Voronoi pattern allowed for the subdivision

The Voronoi diagram is a dual graph of the Delaunay

quantities of types, connections between [N] nodes

of space within a predetermined boundary, per the

triangulation. Both use points [sites] on a plane in order

created some blocks lacking programmes. It was evident

number of programmes. This parcelization of the block

to locate connecting lines. Where the Delaunay forms

that the L-system had too many parameters to attempt

based on the L-system distribution gave each programme

itself with the location of the point, and finds two next

to fix one pattern perfectly for the site, and further rules

a region or area to grow in limited by the boundaries of

closest points, the Voronoi uses the point in reference to

needed to be implemented to adapt to these conditions.

the respective block. The Voronoi worked also within a

neighbor points in to located the walls of its cell.

One way of dealing with the lack of programmes in

neighbor relationship since the corresponding region

The Voronoi was effective in that, based on the positioning

certain areas was to locate green spaces and manipulate

would be determined based on the distance to another

of the point in reference to both its neighbor points, as

the city at the local scale. The effect of these applied

programme. The cell of the Voronoi diagram is determined

well as the network, the cell was given spatial boundaries.

systems was that every block was differentiated in terms

by the intersection of planes between other points, so

As the L-system wasnâ&#x20AC;&#x2122;t perfect, many issues came up in

of proportions, area and the amount of programmes

that the resultant diagram has straight line segments. 1

dealing with the variant programme cell areas.

contained within the boundary.

1â&#x20AC;&#x201A; de Berg, Mark. Computational Applications, 2nd Edition.

Geometry:

Algorithms

and Area: 91 sq.m.

Area: 210 sq.m.

Area: 132 sq.m.

Delaunay + Voronoi as dual graphs [Network nodes]

Block formation as the new boundary

Area: 321 sq.m.

Area: 267 sq.m.

Variation in spatial dimensioning of the block [Voronoi diagram]

Programme

Chapter 6: Critical Analysis

Green Space There is an informality to park spaces that is unmatched in other spaces [except perhaps the street corner]. The main interest in these open spaces is based on the fact that they have no programme at all, but rather are themselves “directly and drastically affected by the way the neighborhood acts upon them.”1 The distribution of such areas across the site in fragments allows for the public to engage in these social spaces throughout the day. As Jane Jacobs emphasizes, the mixture of uses of buildings surrounding park spaces allows also for a mixture of users, who also function on different schedules. Based on the original studies concerning green space within a city, the group found that the optimal quantity was roughly 9 metres square per person. However, where a city like Curitiba could attain such a percentage of green space to population, it is important to note that the respective city doesn’t fall within the high density figure we were aiming for. On the ground, in order to get enough park space for 100,000 inhabitants, we would have required 900,000 sq.m., which would have taken over most of the site. Instead, the goal was to distribute smaller pieces of green spaces which were accessible within the requirement for walking [150m]. 1 Jacobs, Jane. The Death and Life of Great American Cities. New York: 1961. pp. 105.

Cumulative Area: Population:

237,394 sq.m. 100,000 people

Green Space:

2.37 sq.m. per person

Park total: Proximity to other parks: [Distance > 150m]

181 28 paths

Programme

Chapter 6: Critical Analysis

and highly developed form of order.”1 The existing site

be understood through both plan and section.

contained one single large park space. In terms of

“Intricacy that counts is mainly intricacy at eye level,

connectivity to the site, accessibility to this park was

change in the rise of ground, groupinngs of trees,

not ideal or efficient. One focus in the project was to

openings leading to various focal points - in short, subtle

interconnect green spaces within the larger context of

expression of difference.”2 Jane Jacobs describes the

the city.

necessity for park areas within cities to have a level of

Through the usage of the rulesets applied to the site at

differentiation in order to distinguish each space from

the block level and cell level, one of the goals that had

the next. This is important in that users don’t necessarily

not been achieved was the connectivity of the green

associate the same functions within each park space

spaces. We attempted to connect larger park areas with

that they encounter. Variation in size, location, light and

neighboring ones, in the endeavor to begin to manipulate

connectivity are all important aspects in differentiation

the proposed network. In this strategy, only tertiary roads

and hierarchy.

within the city, where the programme relationships could

form of chaos. On the contrary, they represent a complex

Furthermore, the bridges would create level differentiation

Pr im

“Intricate minglings of different uses in cities are not a

Green Space

Plan

Section

would be influenced [taken over] so that green spaces could become fluid singular larger parks. In order to achieve connectivity at between green spaces across from primary roads, an improved strategy is desired. Primary roads cannot simply be taken over as Section [part]

this would greatly limit transportation flow within the city. Instead, the application of a green bridge spanning over the network would act as means of continuing pedestrian flow while maintaining the usage of theparks and roads. 1 Jacobs, Jane. The Death and Life of Great American Cities. New York: 1961. pp. 235

2 Ibid. pp. 114.

Perspective

Network

Chapter 6: Critical Analysis

The L-system was utilized in terms of distribution of

dimensional plane on the ground. By analysis of vertical

network nodes based on distance. These nodes were

travel, the group could have achieved more accurate

then connected together using Delaunay triangulation

flow

method. This strategy proved to be very helpful as we

formation and height criteria. This strategy could have

could form differentiated blocks and even continue with

helped green spaces as well since these were scattered

our ambition of developing a walk able city. There were

between the blocks. Instead, a more integrated vertical

certain areas which could have been looked more in

travel could have facilitated inclusion of green space

detail and facilitate in improvising our system. Critical

within the vertical building height instead of simply on

analysis involved the percentage of network system,

the ground.

profiles of different roads, and overall connectivity in

In terms of the nodes themselves, it could have been

terms of flow.

interesting to study the number and size of the nodes

One of the major flaws realised later on was the

and their relationship to the growth and metabolism of

percentage of roads, which constituted to about 00% as

the city. With respect to the detail of spaces there was a

compared to the overall area of the site. To understand

limitation to only the profiles of the roads. It could have

the reason for this overwhelming figure, the profiles were

been interesting to study the number of functions, parks,

reviewed and criticized. One of the major factors for this

and pathways (turns, obstacles) a person would have

was the primary roads were comprised of parking spots

to to make in order to reach home from the respective

allocated beside the pathways. This could have been

transportation node, using the space syntax. This could

completely eliminated, as road networks in similar heavy

have added more differentiation within the roads type

traffic [for instance, in Central London] do not consist of

and situated programmes based on these pathways.

relationships

between

block

dimension

Altered Rule for Primary Network

and O C

C R

Program cells around Primary network

O R C

Distributing Commercial programs at the bottom for primary road to add liveliness

O R C

parking lanes at the primary networks. Instead, parking is located on secondary or tertiary roads. Looking at the connectivity of the system, consideration was not placed regarding the vertical network and the amount of time it takes to exit a tall building and reach the street level. Connectivity was looked at only on a two 78

View showing differentiation in heights of cells in primary road

Geometry

Chapter 6: Critical Analysis

Height The gradual variation in heights defined the amount

The programmes like Commercial and Amenities never

of use within the road type, as this affected density.

required much height as they are more functional with

The height of the built form was dependent on various

a proximity to the street. As the height was majorly

parameters like the distance from the road, type of road,

dependent upon the proximity and the type of road,

density of the patch, type of programme and the number

it never considered these programmes which were

of programme cells.

unusable at the maximum height allowed by the network.

In certain cases the height value was never utilised as a

These programmes for this reason was best if was close

few programmes were required to be close to the ground

to the ground.

such as [certain types of] amenities and commercial

Furthermore, an environmental aspect needed to be

spaces. Geometry was well designed in terms of final

applied to higher height levels so that differentiation

outcome since the building performed just as a mere

of geometry was also looked at vertically. In terms of

extrusion from the ground. Furthermore, buildings

light, setbacks could be applied, similar to Manhattan

themselves did not integrate a mixed use when we

maximum FAR standards. Cuts within the building itself

induced the rule for height, as height was applied simply

should be considered, so that pockets of space could

to the programme. In this sense, geometry could not

begin to form and become their own programme.

optimise the height value and the connection between

Height determined by simple extrusion of cells

Environmental factor of light imposed on height (setback)

the two were lost. Considering the resultant building types, decisions could have been made to alter the rule for height so that it allowed for more integration of programmes. The primary roads could have the distributed commercial, amenities programmes at the first two or three floors to add differentiation and liveliness along the networks. The built form offset also adds onto the value in terms of proportions and view from the roads.

Area of plan section reduced with higher height values

Geometry Library The library was induced so that we set a relation between one cell to the other neighbouring cells.

Chapter 6: Critical Analysis Initial Rule

Altered Rule

Tested Rule

Considering Environmental Conditions

It proved interesting to not only look at the flow of information within the L-system vertically (branching),

15M

but also horizontally in terms of programme neighbors. This was the second level of manipulation over using the topological information for its spatial location.

4 point cell

Considering 15M width

Height towards road type

Cell Morphology

Cell Morphology considering environmental condition

The cells repelled and attracted each other with respect to some rulesets. Even after introducing the library there was no distinct change in the geometry of the built form, as the programmes typically moved closer or further away from each other. Certain rules in the library created voids in the patch when the cells were moved from one place to another location in the block. The rules in the library revolved around move, rotate or adding a green space between the two cells either on the ground or at levels. The flaw in this set of rules in the library is that there is no consideration involving environmental conditions. The geometry could have been that much more influenced if light or connectivity affected the built form in more integrated methods.

Geometry Interpolated Curves Introducing interpolated curves as part of the geometry

Chapter 6: Critical Analysis Tested: Difference in curve area based on quantity of points

of the pattern proved to be problematic later on, as the application of a library to a geometric form that had curvature made it difficult to manipulate the curved edges. Furthermore, since one of the steps prior to

3 point cell Area: 400 sq. m

Interpolated Curve [D=3] Area: 210 sq. m

4 point cell Area: 400 sq. m

Interpolated Curve [D=3] Area: 271 sq. m

the interpolation was to offset the cell by 2 meters, this estimated curve created further gaps between buildings. In some ways, the interpolated curve achieved what was desired, in that, the more acute the angle, the more the boundary of the cell was estimated. Also, the interpolated curve was based on the vertices of the respective cell, so

Improvement:

in a sense, the more the corner points to estimate from,

Possible rule for acute angles

the more similar the curve is to the proportions of the cell. This created for a variation in accuracy, as cells with more points had less dramatic curves while 3 point cells had more estimated curves.

3 point cell Area: 400 sq. m

Manipulated 4 point cell Area: 381 sq. m

Since the interpolation was induced in order to limit the number of acute angles that existed within the site, another method could be thought of to reduce such angles. Instead, a different rule could have been pursued where for any angle less than 45 degrees, another edge could be drawn to cut off the acute angle. The leftover space from this reduction of area could be turned into private green space.

P E R S O N A L A N A LY S I S :

Chapter 7

Morphology Morphology of the city should begin not with the statistics mined from predecessors, but rather occur locally and through understanding of situation. In our project, this development of the form can be seen more critically in negative space rather than the built. In a certain sense, our application of the library did not necessarily attain a level of geometrical complexity [in which I mean, not a complex form but rather a complex process through which form is derived]. Through differential weighting of factors, the morphology of our site is understood more in context of network connectivity and green space influencing the spatial organization of the built environment.

The diagram, or pattern, is quite important in our project, as three different stages of pattern-making influence spatial organization and create the city. The L-system, which at first was tested as a pattern, and then essentially a map with location emphasis, only worked in light of the fact that we accepted the distribution provided by the system. This distribution is critical, as it is weighted variant on the types [programmes] and their relationship to each other. The two dominant types were Residential and Offices, and each was given dominance at one half of the site, respectively. The distribution was marked by specifically three factors, two of which had an inherent geometric function [angle and length]. Once the L-system places the pattern map onto the site, neighboring relationships between the component N [network] is established through the existing node connectivity. In a sense, the L-system acts as a node connectivity diagram which through Delaunay triangulation, we were able to achieve the axial map [which in turn became the road network]. The final stage of an applied pattern occurs in terms of the Voronoi diagram, which acts to subdivide already 84

subdivided land [the block]. The Delaunay created a connected network [the negation]; the Voronoi took each leftover cell and broke it down to denote the respective

the XY plane, what we ended up with was essentially a pattern. Eventually, that pattern became the basis for Z directional growth in the form of extrusions. The city

Spatial organization of the leftover programmes [R,O,C,A] are influenced by the rulesets applied to the distribution of green spaces. Through analysis of the green spaces at the global, regional and local scales, further land allocation occurs, at times completely removing programme or reducing programme area in favor of added green space. Later, the morphology of the green space itself is influenced by its connectivity to itself, as the distance from one park to another is relevant within the project [300m walkable green city].

Morphology of the derived form is problematic in the fact that the diagram becomes the basis for the creation of space. This is inherently an issue because the determination that went into allocation position is inself limited and restricting. There is no proof to state that the distribution provided by the L-system was perfect as a start point for the rest of the project, but it soon became static.

programme area.

Each building is defined through differing sets of relationships, enabled at different stages of the process. First, these relationships are based on [at the local scale] programme to programme attraction/repulsion by rules enabled within the L-system, and later a geometrically enforced library which transforms the initial building form based on neighbors. This more localized spatial morphology is derived through rulesets provided within the library, which affect the form of the building as based on its adjacent neighbor. While this did not create for dramatic changes to the form, the library studied immediate neighbor relationships and proposed addition, subtraction and displacement of the physical geometry to occur within the context of a boundary, the block. The issue with the library itself is that the L-system could have been more integrated to assume within itself a characteristic of spatial dimension [the Z axis]. Where branching and angles allowed for growth in

should not have grown in this method, but rather as an emergent 3 dimensional branching.

Much of the urban morphology that occurs through our process is rooted in the application of intelligent patterns which to certain extents, analyzes neighbors in order to produce varied growth. At each stage of the process, the relationships that exist are understood differently, weighting different factors to promote transformation at all scales. -Mehnaj Tabassum

Branching City Bio-mimicry, a science that studies naturesâ&#x20AC;&#x2122; models and takes inspiration from these designs and processes to solve human problems. It showcases a new way of

viewing and valuing almost four billion years of naturesâ&#x20AC;&#x2122; R & D. Bio-mimetic systems are interpreted to achieve a certain kind of symbiosis with nature. There are various systems designed to understand their strategies. L system, one such branching system was originally used to describe the development of simple multicellular organisms, later this system was used to study the higher plants and their complex branching system. The recursive nature of the L System rules leads to self similarity, fractal like forms. These forms repeat indefinitely even after magnified. The tree is a teleological form, it is a form with a purpose. The phenomena of parsimonious minimization principle in the trees interests me to study the internal transportation of fluids and the vertical zoning of cells. With the ever growing population and their increasing demand for resources it does seem clear that mixed use vertical zoning for a neighbourhood appears to be the immediate solution. For our Core-2 project, I closely worked over generating strategies and geometry for the patch in our endeavor to strike a relation with the L System. It appeared very difficult to translate the topological information into the third dimension. As one of our many experiments we looked at spreading the programs on the ground using the L-System and then allowing the programs to grow vertically to spread the density over the site. After our persistent attempts for

a couple of days to translate the topological information in the third dimension we comprehend the computational restrictions with the plug-in and the stipulated time to

explore the same. In that crunch of time we developed the library, an interesting strategy which does not only look at the flow of information vertically but also horizontally and its influence over the neighbouring cells. I imagine the library had a lot of potential but the rules were not thought about carefully. Looking at this project develop, I would be interested to look at the biological systems of the tree and use their strategies to generate the building morphology. Using the L System as a tool, their strategies will allow us to efficiently spread the programs vertically while optimizing the network systems. A library of building morphologies can be generated based on the population density, network and environmental factors as few of the parameters. Being particularly interested in the field of Bio-mimicry from my undergrad, I have always been looking at projects with those lens. It appears very interesting to look at transportation of fluids and zoning of cells in trees as an inspiration for developing a mixed use vertical zoning for a neighbourhood, thereby generating the building morphology and in that way optimizing the transportation networks and efficiently spreading programs. -Tejas Sidnal

To p o l o g i c a l o p t i m i z a t i o n o f c i t i e s w i t h L - S y s t e m Cities have been studied for centuries as the main settlement for human beings and in recent years the number of people who are born are exponentially increasing in an accelerated pace. Every urban area has an established transportation network that follows a population and environmental influences, regularly in pattern plan that throughout the years become obsolete. To face that issue new ways of cities generation must be addressed, tackling the imminent overpopulation of cities. However, to design a city poses a number of problems to address. Therefore, we used a procedural system frequently seen in natural phenomena such as land-water creations, plants and trees formations. We implemented this method to generate the ubiquitous road network system that form the structure of cities urban neighborhoods and create an completely integrated city (Inter-City), which aims to have an evenly distribution of program such as office, residential, retail, commercial, amenities, green spaces, road network and transportation working unison, which can be adapted to any supplied terrain. L-System uses recursive nature based on initial rules of axioms where the generation give back a fractal-like result, geometrically or syntactically. Hence, we employed branching techniques to generate cityscapes were the main goals of the system were: Firstly, creating a mixed used city, evenly spread along the site to finally have an integrated and walkable city. Secondly, the allowance to the designer to have more control over the generation process by the manipulation of simple parameters via an intuitive changes in the first axioms (initial rule), distance and angle between branches. Correspondingly, the user has a dynamic engage with the iterative algorithmic design just by 86

tweaking some simple parameters and actively see what the repercussion on the final output are. To reach this targets we divided the generation of the city in different parts:  The first step was to evaluate how many initial points or axioms the site will need in order to fill the plot and have enough program with the desired distance to maintain the initial parameter of a walkable city (see image #1).  The second step was to generate a set of initial rules of pairing where we wanted that the program communicates or instead evades. For now onward the program will be called just for initial letter(office as “O” , residential as “R”, commercial as “C”, amenities as “A”, green spaces as “G” and networks as “N”. So for example the office (O) programs attracts another office (O) and amenities (A) programs. In contrary, the residential programs attracts another residential(R) and a commercial program(C) but repeals office (O) programs from itself (see image #2). The initial axiom letter would be any from the pool of programs.  The third step was to add two different parameters in the iterations generated to fill the site. Those are distance and angle between programs. As a result after run several iterations, we encounter that firstly the process of calibrating all the programs configuration, connections needed, separation between each typology such as distance and specific angles among themselves, all of them in a single calculation was a tremendously computer-demanding and timeconsuming task, due to the amount of free parameters to be estimated. Besides, allowing the system to selfselecting the first axiom or starting rule delivered completely different results, giving more program

where was not needed and not given enough network (N) points on the site to generate and adequate roads network infrastructure, due to different factors such as closeness of points and to the lack or overpopulation of them. That happened because of the process is not a linear calculation and every time that the system change to a new axiom, lose all continuity of it. To solve this problem we limited the first axiom to networks “N” programs. This decision was taken understanding that the first letter or axiom created a constant in the procedural calculation and it could be controlled just by the balancing of “N’s” on the site. Additionally, the reduction of the initial parameters in distances (from 0 to 200) and angles (from 0 to 360 degrees) to a tighter array of 5 rounded numbers on each of them, it narrowed the possibilities and calculations. The final result was a more controllable system that created more evenly dispersion of programs (R,O,C,A,N,G) full filling the site and having an average distance of 100 meters among each of them and an ideal amount of 100 network (N) points. To sum up, after a rigorous process of refinement and depuration of the system, using a recursive/procedural approach in city generation, it still being a new field on the computational endeavors and to realize the specific task such as the allocation of the different typologies or programs in a city patch will needs several feedbacks from the context where it is executed to make a well integrated distribution of uses. With a well calibrated system the result generated definitely can automate by computer processing, so the acceleration of the process can be radically boost. Although, there is not such a thing as an ideal urban fabric, and for that reason the outcome that this algorithmic-based and script-based approach to urban design development must be always evaluated

To p o l o g i c a l o p t i m i z a t i o n o f c i t i e s w i t h L - S y s t e m and criticized by the designer whether it is the optimum solution for the problem, understanding the specific characteristics and limitations of the analyzed city patch. Moreover, the following process of blocks and building generation consequently should be address in a way that complements the initial distribution of typologies to have a successful result.

Axiom

AXIOM

R R O C A N G ANGLES

45 30

DISTANCES 50 200 175 75 100 50

-Ulises Juliao Axiom

Axiom

AXIOM

N R O C A N G ANGLES

DISTANCES

15 30 15

30 30 30

UPPER SIDE

15 30 15

30 30 30

LOWER SIDE

50 25 75 50 75 25

50 50 50 50 50 50

LOWER SIDE

UPPER SIDE

Image #1

Axiom

R R

3 45O

X+

G C

30O

-30O

B -45O

N N

-15o

X+2

X+1

15o

Image #2 87

Integration One of my main contributions in the project was focused

offices and residential. The different morphologies of

programmes. Therefore, elements with homogeneous

in the development of the L-System as main digital

every program created elements with different heights

heights and densities that allow us to generate zones

tool to spread and define the initial location of the

and densities, limiting the relation between them and

that could define in a better way the relation between

programmes, therefore the distribution of the intervened

generating a poor spatial condition of the built space.

built space and open space.

an integrated city with every block having mix use.

It can be seen that the regular distribution was achieved,

-Nicolas Cabargas

Certainly, the intension was to have a homogeneous

but this characteristic made very difficult to succeed the

distribution of the program and open space, allowing to

others mentioned ambitions. This problematic generated

the users reach all the necessities through a walkable

the main question of this critical analysis: Is the uniform

distance. In addition, to increase the quality of the public

distribution meaning of integration? The definition of

space and the relation of the built space, dense buildings

Integration is: â&#x20AC;&#x153;a combination of parts or objects that work

should form a gradient of the built environment to the

together wellâ&#x20AC;? In my opinion, after analysing the results

positive externalities (parks and river) and a barrier to

of the project it can be said that regular distribution is

the noise coming from the main roads.

not meaning of integration. According to the block scale

patch. The main ambition of the project was to achieve

and site conditions, a synergy between clusters should Analysing the urban result, the uniform distribution of the

be developed improving the overall performance of the

programmes, generated blocks within all the typologies.

city. Hence, can be concluded that the behaviour of the

This condition produced isolated clusters without relation

city should be evaluated as an organism compound by

between them. This condition is more related with the

different and specific organs. Thus, should consider the

logic of mega-blocks, where every cluster wants to be

relationship between clusters and its complement as

completely independent solving all their necessities

main aspects to evaluate the integration of the city and

without any relation with the neighbours. Furthermore

not only the uniform distribution.

at local level, in each cluster the relation between programmes were restricted by the application of the

This understanding at global scale and the possibility of

library rules for the building formation, for example:

consider mix use buildings at local scale, could allowed

was not allowed merge in the same building amenities,

to have a complement between low and high-density

THE SITE: Appendix

Land Use

Appendix: The Site Zoning | Programme Distribution The Isle of Dogs, located at the east-end of London in the borough of Tower Hamlets is now the second Financial District after central London. It was previously the site of the highest concentration of council housing in England and is reputable as a poor example of urban development. Currently, the Canary Wharf tube station acts as the headquarter of banks and other office complexes. The area is in a state of rapid urbanization where the existing low lying context and population is being overtaken. There is a programmematic distribution dominated by offices in a highrise configuration surrounded by a large amount of residences (complex buildings, family houses N

Scale 1: 15000

MMERCIAL

SIDENTIAL LEISURE

BLIC OPEN

DUSTRIAL RETAIL

Scale 1: 15000

Residential 30.7 %

51.3 %

Bunglows

R 1R1

0.7% % 0.7

Commercial 51.3 %

30.7 %

Row Housing

R 2R2

16.7 16.7% %

Leisure 2.2 %

2.2 %

Social Housing

R 3R3

6.7 6.7% %

Open 7.8 %Space

7.8 %

R 4R4

2.8% % 2.8

Industrial 6.6 %

6.6 %

M M1 1

0.1 0.1% %

Retail 1.4 %

1.4 %

+ Residential M2 Residential + RetailRetail Shops Mixed UseMixed Use M M2 2

0.1 0.1% %

Commercial

R1 - Single (1-2)

26.9 %

R3-Apt Housing (5-9) R4-Apt (10 +)

Apartments Retail Mixed + Commercial M1 Offices + Retail Shops Use

Amenities Public Open Space Retail Shops

R2 - Row Housing (3-4)

Mixed Use

Commercial

12.4 12.4% %

Amenities

A A

2.6 2.6% %

Public Open Spaces

P P

54.8 54.8% %

Retail Shops

S S

2.1 2.1% %

and council buildings) that enclose about 50% of the land. The abrupt transition amongst each typology is observed when one walks through the avenues, streets and alleys. Radical changes of scale and uses as well as the accelerated and unorganized development can be identified immediately on the site. The initial study focuses on the distribution of programme, scale and uses in order to quantify the existing urban structure.

Land Use

Appendix: The Site Study of Heights

Site Selection

The concentration of the tallest buildings in London

To understand the growing behaviour of the site the right

is part of the planned development to create a new

half of the island was selected with the intention that it

Financial Centre. Close to the Canary Wharf tube Station,

contained a variety of programmes.

building heights increase to 10 stories and higher. This

1 to 2 Story Building 3 to 4 Story Building 5 to 9 Story Building 10 & more Story Building

360m

is representative of the rapid urbanization as there is a

The distribution of the main typologies and its

high demand of ground in the financial market of office

substructures was categorized as:

buildings.

Residential (single family, social housing,

Meanwhile, the rest of the site has not been developed

apartments, mixed use).

alongside with to the impact of the financial giants. Low

Office Buildings (offices, mixed use).

rise buildings under 5 stories dominate along the site,

Commercial.

mainly residential buildings containing residents that

Amenities.

do not work within the Canary Wharf area. Instead,

Public open spaces.

the major percentage of workers on the area needs to

Retail shops

583mcommute

or come areas along London. 83m from other393m

Scale 1: 15000 Height Analysis

360m

63m

APROX

83m

583m

393m

1420m Section North-South

63m

APROX

North-South Section

1420m 863m

845m

Section North-South

44m

APROX.

863m 1708m

East-West Section Section East-West

Existing Roads Streets Profiles and Pattern The roads in the Isle of Dogs change depending on the closeness to the main artery where the public transport (buses) pass by. These main streets (Westferry road and Manchester road) are oriented along the site river boundary defining the Isle of Dogs edge. It splits the site in two major parts: A mixed use area contained on the inner bound of the road while the outer bound close to the river edge has primarly residential houses. The heights of Isle of Dogs has a defined pattern of the width of the streets responding to the height of the surrounding buildings. This ratio changes from 1:1 to 1:2 on main streets and 1:3 in tertiary roads.

Appendix: The Site

Networks

Appendix: The Site

Walkable City One of the main aims of this project was to understand the existing connectivity within the network (cars,

South Quay

bycicles and pedestrians) as well as public transportation (buses, tube and DLR) and how it has been planned to

Part A

that may have organizations allowing for better mobility

7.5

serve the area of Isle of Dogs. By studying other cities

Cross harbour

and fluidity, the Isle of Dogs can be influenced by the

5 min

implementation of an adapted system. The existing tissue was studied and categorized into

Part B

primary, secondary and tertiary streets to understand how the flow of people can be maintained in conjunction with both a bus system and a tube line.

Tube DRL

By analyzing an optimal walking distance, the goal was

Jubilee

to achieve a walkable city where people can move from

Buses 135

one corner of the site to a tube station in less than 7.5

minutes with just walking about 600 meters. To test

5 Mins

N55

7.5 Mins

various methods,minimal spanning paths and distances are calculated. For instance, the distance from one point to another is simply an understanding of spatial location. In order for one to walk from point to point, the relationship between pathways must be taken into account. Walking around a block or having to circumspect obstacles creates for a longer travel distance.

5 Mins Part A

7.5 Mins Distance : 600 M Time : 7.5 Min

7.5 Mins 5 Mins

7.5 Mins

5 Mins Actual Distance : 883 M Actual Time : 11 Min

7.5 Mins

Part B

7.5 Mins Distance : 600 M Time : 7.5 Min

5 Mins

5 Mins Actual Distance : 845 M Actual Time : 10.5 Min

Networks

Appendix: The Site

Data Collection | People, journeys and uses A process of data collection and mapping was established in order to understand the ways in which the part of the city is used and how the metabolism of the site could be quantified. Movement and network become an important criteria in that people, schedule and the underlying infrastructure help to keep the city going. People Analysis A comparison among tube stations such as Bank & Monument, Canary Wharf, Higbury and Islington shows that the a very high number of people travel on weekdays to the Canary Wharf station. This can be tied in to the fact that there is a high concentration of offices and a new financial center within this zone. Journeys Another study measures time in that it quantifies a large influx of people coming to the area (to Canary Wharf station) traveling more than 15 minutes in comparison with another main tube stations. Uses A high percentage of the people that come to the Canary Wharf station is between 25 to 60 years old. This is a reflection of the type of flow that can occur, for instance, a younger generation of workers require very different amenities from a neighborhood than an older population.

Bycicles Cycle stations Tube DRL Jubilee Buses 135 D3 D7 N55

Existing networks

Scale 1: 15000

Networks

Appendix: The Site Annual Travels! Weekday!

87584!

Saturday!

Bank / Monument

Average Journey Lenght (kms)!

Sunday!

1%!

82010!

Bank / Monument Canary Wharf

29214!

21639! 11203!

Bank & Monument

Canary ! Wharf

20838!

Highbury ! & Islington

Heron Quays

13%!

54%!

Crossharbour

Island Gardens

5%!

South Quay

Mudchute

9%!

! 32%!

Canary Wharf

Spent Time on Jurney!

Canary Wharf - DLR

15 - 30!

45 - 60!

1%!

60 - 90!

Bank / Monument

35%!

4147! 770!

Canary Wharf

2629! 411! 130! Highbury & Islington!

Home to Work!

82010! 87%!

25-34

35-44

45-59

60-64

65-70

Work to Home!

16-19

20-24

25-34

35-44

45-59

60-64

65-70

44231!

2% Under 16 16-‐19

14%

48338!

0%!

Highbury & Islington 1%

20-24

Over 70 !

Journy Purpose!

Canary Wharf

1%!

26%!

9754!

DRL / Tube (Persons)!

16-19

Under 16 !

16548!

16461!

2160! 195!

Canary Wharf - DLR

0%!

24%!

35664!

11638!

11909! 13%!

1%!

12%!

19555!

30 - 45!

47448!

33770!

1%!

Over 70 !

< 15 mins!

10%!

26%!

DRL People Destination!

9%!

25%!

9.96! 43%!

11668!

0%!

Under 16 !

Highbury & Islington!

24801! 22198!

0%!

14%!

6.29! 27%!

6.96! 30%!

1%!

20-‐24

28%

25-‐34 35-‐44 34% 9603!

7013!

5036!

9204!

19%

45-‐59 60-‐64 65-‐70

Bank / Monument

Amount of people analysis

Journey analysis

Canary Wharf

Highbury & Islington!

Users analysis (Age)

Samples Boundary Condition

Appendix: The Site

City Samples | Critical comparison A systematic analysis is of tissue samples among three main criterias (Boundary, Network and Open Space) is pursued. The aim is to use external resources of city samples with better or similar conditions of the site and understand the interventions that have driven optimization of the respective categories.

CRITERIA

Boundary In this first criteria the comparison of the average height vs width, and the land use were utilized to compare the Isle of Dogs and Manhattan.

Boundary

Average of Height / Width Land Use (Functions)

Isle of Dogs, UK

Manhattan, USA

Isle of Dogs, UK

Queens, USA

Curitiba, Brazil

Isle of Dogs, UK

Islington, UK

Paris, France

Network The second criteria compares the average of height with width, distance with route and road vs sum of length. The

Network

Average of Height / Width

city samples used were the Isle of Dogs, Queens and

Distance / Route

Curitiba in Brazil.

Length of Road / Sum of length of all Roads

Open Space Lastly, parks, private and public open spaces and parking lots were quantified in order to establish open ground with built. The city samples studied included the Isle of Dogs, Islington in London and Paris.

Open Space Parks

Samples Boundary Condition

Scale 1: 6000

Appendix: The Site

Isle of Dogs

Manhattan

N C’

A’

To Midtown

E’

B’

Boundary 1

Boundary 2

Boundary 1

To Downtown

Boundary 2

R1 R2 R3 R4

Bunglows Row Housing Social Housing Apartments

R1 R2 R3 R4

0.9 % 47.6 % 13 % 11.9 %

R1 R2 R3 R4

2.5 %

R1 R2 R3 R4

M1 M2 M3

Offices + Retail Shops Mixed Use Residential + Retail Shops Mixed Use Residential + Offices Mixed Use

M1 M2 M3

1.9 % 2.6 % 3.5 %

M1 M2 M3

13 % 0.7 % -

M1 M2 M3

27.9 % 8% 28.5 %

C P A S I

Commercial Public Open Space Amenities Retail Shops Industrial

C P A S I

18 % 0.6 % -

C P A S I

16.5 % 43.8 % 11.2 % 12.3 %

C P A S I

1% 3.1% 31.5 %

Samples Boundary Condition

Appendix: The Site

Boundary | Average of heights vs width

Isle of Dogs

Scale 1: 1000

Height / Width = 0.63

Height / Width = 2.58

30 M

different scenarios, the river edge condition and the rail condition. The specific areas selected in both city

24 M

For the building height vs streets width we selected two

110 9M

samples in Manhattan shows first: 42

River edge condiiton

26.3 M

It has a public green area which merges into the fabric

35.2 M

9.3 M

of the city, which is In contrary on the Isle of Dogs where the building starts in an abrupt manner just after a

Manhattan (Riverfront)

pedestrian passage or a street.

Scale 1: 2000

Height / Width = 0.027

327.8 M

Street condition

Manhattan

The aim of the selected city sample in Manhattan was

Scale 1: 1000

Height / Width = 0.636

to see how the buildings begin to stagger away from a

this leave an empty space without use that can be built in a more useful manner.

19.6 M

100

18.1 M

from the main transportation to the building height but

18 M

train line. The Isle of Dogs has similar angle proportion

Samples Boundary Condition

Appendix: The Site Isle of Dogs / Roads and Profiles Street condition Another street condition in the Isle of Dogs is merging of uses within the city organization. This is studied in the various levels of street types, primary, secondary and tertiary. Building height and usage are studied in terms of the street they occupy.

Primary Roads

Secondary Roads

Tertiary Roads

Pedestrian Roads

1275m = 24%

1347m = 25%

2317m = 44%

373m = 7%

Primary Road Profile / Ratio (Average Height / Width) = 0.52

101

Samples Network

Appendix: The Site

Isle of Dogs / Roads and Profiles Some street profiles were studied along the three typologies of streets (primary, secondary and tertiary). The composition of them shows that the ratio between building height and width is affected by its proximity to the different boundary conditions as river, rail line or tube station.

Secondary Road Profile / Ratio = 0.44

Tertiary Road Profile / Ratio = 0.51

Primary Roads

Secondary Roads

Tertiary Roads

Pedestrian Roads

1275m = 24%

1347m = 25%

2317m = 44%

373m = 7%

102

Secondary Road Profile / Ratio = 2.5

Samples Network

Appendix: The Site Isle of Dogs / Travel to public transport One of the experiments established was the simulation of a typical scenario of traveling to a bus stop or the nearest tube station. A common example shows that an people need to walk about 250m in 3 minutes to reach the nearest bus stop. On the other hand, the walking distance to the nearest tube station is about 600m within 8 minutes. Both are in an acceptable range of walking time and distance for the integration required.

Distance: 173m / Route: 254m (3min)

Primary Roads

Secondary Roads

Tertiary Roads

Pedestrian Roads

1275m = 24%

1347m = 25%

2317m = 44%

373m = 7%

Distance: 492m / Route: 614m (8min)

Bus Stops

Train Stations

Route

103

Samples Network

Appendix: The Site

Queens / Roads and Profiles Queens was found to have a consistent ratio between building height and street width. That its due to the normative of the maximun building height restrictions on the city. This presented in a common language of heights, as well as it has balanced ratio of 0.13 of difference between primary and tertiary streets.

Tertiary Road Profile / Ratio = 0.41

Secondary Road Profile / Ratio = 0.34

Primary Roads

Secondary Roads

Tertiary Roads

Pedestrian Roads

500m = 10%

1915m = 38%

2562m = 51%

0m = 0% Primary Road Profile / Ratio = 0.28

104

Samples Network

Appendix: The Site Queens / Travel to public transport In the Queens tissue sample, the necessary walkable distance to travel from the selected starting point to the nearest bus station is approximately 300m in 4 minutes. For the tube station the walking distance is 370m and can travelled in 5 minutes. Proportionally it has the same distance relationship as found in the Isle of Dogs, with the main difference in the organization of the block likegrid formation.

Distance: 272m / Route: 315m (4min)

Distance: 369m / Route: 427m (5min)

Primary Roads

Secondary Roads

Tertiary Roads

Pedestrian Roads

500m = 10%

1915m = 38%

2562m = 51%

0m = 0%

Bus Stops

Train Stations

Route

105

Samples Network

Appendix: The Site

Curitiba / Roads and Profiles Curitibaâ&#x20AC;&#x2122;s organization of buildings is similar to the Isle of Dogs close to the Canary Wharf station, where most of the office complexes are centralized and are higher heights. The relationship that exists is that the height of the building is more than two times the width of the street.

Primary Roads

Secondary Roads

Tertiary Roads

Pedestrian Roads

1122m = 38%

620m = 21%

1203m = 41%

0m = 0% Primary Road Profile / Ratio = 2.21

106

Samples Network

Appendix: The Site Curitiba / Travel to public transport The horizontal distance has a similar proportion to the tissue sample found in Queens and the Isle of Dogs. The walkable distance to the nearest bus stop and tube station has the acceptable range, not overpassing the Isle of Dogs example.

Distance: 454m / Route: 617m (8min)

Primary Roads

Secondary Roads

Tertiary Roads

Pedestrian Roads

1122m = 38%

620m = 21%

1203m = 41%

0m = 0%

Distance: 421m / Route: 614m (8min)

Bus Stops

Train Stations

Route

107

Samples Open Space

POSITION 3:

1.9

Millwall

Green Area per Person

E.OS-1 9,566 sqm

POSITION 2:

W.OS-3 296 sqm

1.9 sqm per person

2.D

2.C

2.B W.OS-4 464 sqm

E.OS-2 139,633 sqm

3.F

3.B 3.C

W.OS-5 3,476 sqm

3.E 3.D

E.OS-3 84,758 sqm

W.OS-6 3,507 sqm E.OS-4 12,211 sqm E.OS-5 852 sqm

108

Total Area: 247,020 Population: 14,547 16.9 sqm per person

3.G

WHO min: 9 sqm

3.0

Tokyo

5.6

Barcelona

Isle of Dogs

CUBITT TOWN & BLACKWALL

Santiago

W.OS-2 22,043 sqm

Total Area: 29,870 Population: 15,494

16.9 14.0 12.6 11.5 10.0 9.2

1.C

MILLWELL pop.: 15,494

23.1

Paris

28.3

Madrid

Toronto

W.OS-1 84 sqm

52.0

Cubitt Town

1.A

New York

Ratio: 9.2 sqm per person

Rotterdam

Total Area: 276,890 Population: 30,041

Curitiba

POSITION 1:

park space: sq. meters per person

Appendix: The Site

Samples Open Space

Appendix: The Site Green space calculations

HIP OF RESIDENTIAL ZONES TO DESIGNATED PARK AREAS

According to the World Health Organization (WHO) every city should have a minimum of 9 m2 of green space per person and an optimal amount would sit between 10 3.A

and 15 m2 per person. In the area of Millwall the green

space ratio is just 1.9 sqm per person. However, in the

3.C

right-hand side, Cubitt Town & Black Wall contains 16.9 MILLWELL

sqm of green area per person. Overall, both have and

CUBITT TOWN & BLACKWALL

average of 9.2 sqm per person. In order to increase the density to a projected population of 100,000 inhabitants the intention is to keep into the POSITION 1: 1.

optimal green area ratio required per person. In order to achieve this, various parameters and technics will be

implemented when the distribution of programme and

1.A

POSITION 2:

uses will be place on the site.

1.C 3.A

MILLWELL

CUBITT TOWN & BLACKWALL

POSITION 3:

3.G

3.G 3.F

3.B

3.E

3.C

3.D

Path 1.A 1.B 1.C

Distance 281.0 728.3 471.4

Walking 283.2 1,015.2 538.6

Ratio 1.0 1.39 1.14

Path

Distance

Walking

Ratio

2.A 2.B 2.C 2.D

465.5 510.5 706.8 861.3

609.0 747.1 1,037.3 1,122.6

1.31 1.46 1.47 1.30

Distance

Walking

3.F

3.D 3.E

492.8 270.2 290.5 731.9 852.6 546.4 570.7

710.5 360.1 355.8 1,022.1 1,179.6 1,062.0 1,426.9

Ratio

1.44 1.33 1.22 1.39 1.38 1.94 2.5

2.D

2.B

2.C

3. C

Path

3.A 3.B 3.C 3.D 3.E 3.F 3.G

109

Samples Open Space

Appendix: The Site

count as one open space

ISLINGTON

ISLE OF DOGS estimated population: open space / parks: person per open space:

estimated population: open space / parks: person per open space:

2,560 3,940 1.54

ISLE OF DOGS estimated population: open space / parks: person per open space:

ISLE OF DOGS 4,042 26,046 sqm 6.44

private space: public area: ratio:

150,327 sqm 99,673 sqm 1.51

ISLE OF DOGS 2,560 3,940 1.54

private space: public area: ratio:

estimated population: open space / parks: person per open space:

ISLE OF DOGS

ISLINGTON

estimated population: open space / parks: person per open space:

estimated population: open space / parks: person per open space: ISLINGTON estimated population: open space / parks: person per open space:

2,560 3,940 1.54

ISLE OF DOGS 2,560 3,940 1.54

4,042 26,046 sqm 6.44

private space: public area: ratio:

ISLINGTON

ISLE OF DOGS

Area not within 1 minute walkable distance: Number of open spaces / parks: Ratio: 110

191,410 sqm 2 95,705 191,410 sqm 2 95,705

figure ground area parking lot covera percentage:

PARIS

ISLINGTON

figure grou parking lot percentage

PARIS ISLINGTON count as one open space

150,327 sqm 99,673 sqm 1.51

4,042 26,046 sqm 6.44 ISLE OF DOGS

estimated population: private space: 148,6737239 sqm open space / parks: 101,32721,755 PARIS public area: sqm sqm person open space: 3.00 ratio: perpopulation: 1.47 7239 estimated ISLINGTON open space / parks: 21,755 sqm private space: person per open148,673 space: sqm 3.00 public area: 101,327 sqm ratio: 1.47

150,327 sqm 99,673 sqm 1.51

walkable distance / time: 80 meters / 1 minute

Area not within 1 minute walkable distance: Number of open spaces / parks: Ratio:OF DOGS ISLE

count as one open space

estimated population: 7239 ISLINGTON open space / parks: 21,755 sqm private space: 148,673 sqm count as one open space person per open space: 3.00 public area: 101,327 sqm ratio: 1.47

ISLE OF DOGS

private space: public area: ratio:

ISL ISLE figu figure pa parki pe perce ISLE OF DOGS

150,327 sqm 99,673 sqm 1.51

ISLINGTON

estimated population: open space / parks: person per open space:

ISLINGTON PARIS private space: 148,6737239 sqm estimated population: public area: sqm sqm open space / parks: 101,32721,755 ratio: per open space: 1.47 3.00 person

walkable distance / time: 80 meters / 1 minute

Area within 1 minute walkable distance: 188,564 sqm Number of open spaces / parks: 7 Ratio: 26,938 sqm [per park] walkable distance / time: 80 meters / 1 minute walkable distance / time: 80 meters / 1 minute

ISL ISLE figu figure pa parki pe perce

ISLINGTON

figure grou parking lot percentage ISLE OF DOGS

figure ground area parking lot covera percentage:

walkable distance / time: 80 meters / 1 minute

ISLINGTON PARIS

Connection streets :distance: Area within 1 points minutetowalkable Numberofofopen individual open spaces: Number spaces / parks: Ratio: Ratio:

23 176,145 sqm 7 12 3.28 [Nodes] 14,679 [per park]

walkable distance / time:

walkable distance / time: PARIS 80 meters / 1 minute

80 meters / 1 minute Area within 1 minute walkable distance:

176,145 sqm

Samples Open Space

Appendix: The Site Green space distribution One of the main objective is the allocation of the green spaces within the urban fabric. The closeness of them is crucial to create a really livable city with a balance distribution between active programme(offices, retail, residential, etc.) and the recreational programme. At first glimpsy, Isle of Dogs count with enough green area to reach to the international minimum by the WHO, but the way that it is scattered in the site its clearly piled in one corner. We studied three different patches in the Isle of Dogs, Isllington and Paris. The Isle of Dogs selected sample was in a mainly residential area and showed the green space per person is far less than the needed (1.5 person per sqm) and also that the distance to be reached in a walkable manner is deficient. On the other hand the Isllington sample, also in London, even showing an increase in the amount of green areas in the selected patch (7), the amount of people per square meter do not reach the minimum acceptable (6.44 people per sqm). Finally the Paris sample the number of parks and green areas increase even more to 12, but with a ratio of 3 in the relation people vs green. In conclusion, every sample has different characteristics but help us to understand how to spread properly the green spaces and as well to understand the amount of square meters needed to reach with the optimal sqm per person. 111

Sources -MARK DE BERG Computational geometry : algorithms and applications 2nd. edition New York : Springer Verlag, 2000. -MICHAEL WEINSTOCK The Architecture of Emergence: The Evolution of Form in Nature and Civilisation John Wiley & Sons 12 Feb 2010 -D’ARCY THOMPSON On Growth and form Cambridge University Press 2000 -JANE JACOBS The

death

and

life

great

American

cities

Harmondsworth: Penguin Books in association with Jonathan Cape, 1972 -PHILLIP BALL Nature’s Patterns : A Tapestry in Three Parts. Part 3 Branches. OUP Oxford 26 May 2011 -WEBSITES http://mathworld.wolfram.com https://en.wikipedia.org/wiki/L-system 112

Architectural Association School Of Architecture Graduate School Programmememes Coversheet For Submission 2012-13 Programmeme: EMTECH Term: 2 Student Name(S): Mehnaj Tabassum, Tejas Sidnal, Nicolas Cabargas, Ulises Juliao Submission Title: InterCITY Course Title: Core Studio 2 Course Tutor: Michael Weinstock, George Gerominidis / Evan Greenberg / Mehran Gharleghi / Guy Austern Submission Date: 01-05-2013 Declaration:

â&#x20AC;&#x153;I certify that this piece of work is entirely my/our own and that any quotation or paraphrase from the published or unpublished work of others is duly acknowledged.â&#x20AC;?

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