Embed Size (px)
DESCRIPTION
Space Syntax: Space, Configuration & Navigation. Nick S Dalton [email protected]. Why are architects interested in graph theory?. Creating successful buildings & urban spaces. Broadgate city of London. Building level. Stopping/meeting behavior - PowerPoint PPT Presentation
Citation preview
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Nick S [email protected]
k
Space Syntax:Space, Configuration & Navigation
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Why are architects interested in graph theory?
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Creating successful buildings & urban spaces
Broadgate city of London
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Building level
• Stopping/meeting behavior– How creative environments
work (research laboratories, Media)
– Interaction and information flow through an organization
– Navigation wayfinding (hospitals/airports)
What space seeks to do is separate the spatial component out from these complex social systems.
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Urban level
• Interested in pedestrian movement– Passing trade important
for retail– Relationship between
space, design and crime– Avoiding nightmare
projects (Oxford Leys, Docklands)
– Archeologists interested in historic function
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Questions
• Despite the high value of ‘village’ properties and many attempts. Developers seem incapable of creating a ‘village feel’.
• Yet historic villages themselves where created by people ignorant of urban design.
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
QuickTime™ and aTIFF (Uncompressed) decompressor
are needed to see this picture.
1970’s work began at the unit forAdvanced Architectural studies (UAAS) Bartlett School of architecture University College London
Looking for a ‘language’ or ‘grammar’ of space.
1983 - Architectural Morphology by J.P.Steadman1984 - The Social Logic of space Hillier &Hanson
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Process
• Buildings• Derive maps of ‘discrete space
– (space==node)
• Where spaces intersect create link– (link == edge)
• Build measures of structure of graph• Visualize the results back on the
space map
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
people move in lines interact in convex spaces see changing visual fields as they move around built environments
people
spaces
Because space is intrinsic to human activity, we shape space in ways which reflect this. So we must start from this when we seek to analyse space.
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
• We can use this simple technique to show how culture manifests itself in the layout of space. For example we can analyse house plans in terms of the shape of justified graphs from rooms with different functions
total depth fromgrande salle: 31 total depth from outside:18 total depth from salle commune:21
grande salle vesti- bule
bureau salle salle commune
couloir
vesti- bule
laverie laiterie
debarras
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
networks of domestic spaces
• And colour the results up so we can see see that different functions have different degree of integration into the layout as a whole
grande salle vesti-
bule
bureau sallesalle commune
couloir
vesti-
bule
laverie laiterie
debarras
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Are these buildings ‘similar’?
sallecommune
sallecommune
sallecommune
sallecommune
sallecommune
sallecommune
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
sallecommune
sallecommune
sallecommune
sallecommune
sallecommune
sallecommune
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Axial Lines
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
The axial network
a
bc
axial
a b
Traffic (node and link)
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
A ‘Beady Ring’ Settlement
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Line Representation of Spatial Configuration
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Axial Lines
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
‘Justified’ Graphs
Mean depth = 2.29 Mean depth = 1.43
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
‘Axial Integration Map’
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Oxford Axial map (out of date)
You are here
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Central Oxford (out of date)
You are here
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Oxford City Center
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Central Oxford (out of date)
You are here
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
images of London
QuickTime™ and aTIFF (Uncompressed) decompressor
are needed to see this picture.
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Observing of patterns of movement
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
-1
0
1
2
3
4
5
6
7
8
1.25 1.5 1.75 2 2.25 2.5 2.75 3 3.25 3.5ra5pedLondon
ln(x) of adults/ph
y = 2.286x - .559, R-squared: .527
0
1
2
3
4
5
6
7
8
9
1 2 3 4 5 6 7 8 9 10Fitted RA3 and net Capacity
Sqrt of Sqrt of allveh-bus/ph
y = .97x - 1.056, R-squared: .828
The correlation between the log of observed adult pedestrian flows and radius 5 integration, (r=.726, p<.0001, n=466)
Correlation between normalised vehicular flows and a fitted variable including radius 3 integration and net road width, (r=.91, p<.0001, n = 395)
Axial map of London, 17,000 lines, coloured by radius 3 integration.
Spatial Configuration Correlates with Movement
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Just a reminder
• Just a pure graph• No ‘attractors’ (shops)• No ‘sources’ (housing,stations)• No ‘resistances’ (congestion,traffic)• No distances (pure topology)• Ideal model for early design stage -
master planning.
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Axial map of Tokyo, 70,000 lines, coloured by radius-n integration.
Den Haag
Manchester
Shiraz
Spatial Configuration Embodies Culture in Co-presence
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Relativisation
QuickTime™ and aTIFF (Uncompressed) decompressor
are needed to see this picture.
But people don’t walk across the length of London.
How to compare London with historic London or other cities with different numbers of lines ( different sizes)
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
‘Justified’ Graphs
• Radius ‘3’
Mean depth = 2.29 Mean depth = 1.43
exclude
include
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Radius subgraphs
• Each sub graph (up to a radius) has access to different numbers of nodes.
• Need a method to permit comparison of structure of different sized graphs.– Subgraphs from a node– Different houses buildings or urban
systems
• Does anyone else look at cumulative path length sub-graphs (Social networks?)
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Relativisation
€
RAi =2(MD −1)
(n− 2)
€
MDi =TDini −1
€
RRAi =RAiDn
Normalization
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Normalization
€
RAi =2(MD −1)
(n− 2)
maximum total depth
minimum total depth
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Relativisation
€
RAi =2(MD −1)
(n− 2)
€
MDi =TDini −1
€
RRAi =RAiDn
Normalization
Integration = 1/RRA
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Radius 3 Mean depth
Oxford Street
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Radius 3 Integration
Oxford Street
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Social: Teenage Socialization
Teenagers’ and children’s space use patterns colonise strategic but isolated spaces
Adult movement patterns are centre to edge
1970’s housing in North London has found problems of youth socialisation
Spatial segregation and complexity freeze out through movement
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Perceived usefulness and frequency of being seen for ‘creative’ staff
Perceived usefulness and frequency of being seen for all staff
Moving and static space use in HHCL
All line analysis of spatial layout
Spatial Layout Drives Communication& Innovation at Work
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
The End
• Further information• www.spacesyntax.org• http://bat.vr.ucl.ac.uk/webmap/• The Social Logic of Space [Hillier &
Hanson] • Space is the Machine[Hillier]• The Social Logic of Housing[Hanson]
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Extra Time
• Small world or not small world ?• Intelligibility (measure)
– ‘nameing’ places
• More localization methods • Highly non planar mapping
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Is it a Small world?
• Mean path length is typically low• Degree distribution more Poisson than power law • Axial maps are highly clique free (Watts and Strogatz)
definition of small world• Also lack of cliques means not scale free.• Cities Have structural hubs (high street) but tend to be more
robust to blockage.
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Is a city a small world?
• Path length distribution is also wrong for a small- world ( but consistent across all axial maps)
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Extra Time
• Intelligibility• Correlation between
– Connectivity( Degree) – Global integration (normalized
cumulative path length )
• The relation between what I can see and how I can go in the system
• Appears to be strong for historic neighborhoods and weak for dysfunctional housing estates
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Maiden lane estate
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Barnsbury
Maiden lane estate
Correlation between Radius3 and Radius Infinity
degree
integration
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
• Intelligibility Mapping
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Camden town
Summers town
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Oxford
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Extra time
• Local cumulative path length• Radius ( count of onion rings)
– Relativisation only works with rational steps
– Needs strong scaling structure
• Vicinity (new)• Decay (new)
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Vicinity vs Radius
• Ordered J-graph sequence 1,2,2,2,3,3,4,4,4,4,5,5,5,5,5,5,5,6,6,6,6,6
• V9 = [1,2,2,2,3,3,4,4,4]• R3= [1,2,2,2,3,3]• 1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3
,3,3,3,3,4,4,4,4,4,4,4,4,• R3=[1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,
2,3,3,3,3,3,3]• V9=[1,2,2,2,2,2,2,2,2]
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Extra time
• K eccentricity appears to be the reverse of Vicinity
• Is there a ‘proper’ mathematical term for vicinity?
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Empirical Evidence
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Non planar graph
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Random grand final thought
Possible to layout non planar graphs in a planar way ?
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Planar representation Tuft would be proud of
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Convex Spaces
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Convex Spaces
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Convex Spaces
Mutual awarenessIntervisibilityCo-presencePotential for social interaction
ExclusionConcealmentIsolationNo potential for social interaction
antonymous
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Mean Shortest Paths & Mean Out-of-group ‘Utility’:
Numbers for Nine Organizations
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
UCL Departments
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Density of Internal Phone Traffic
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Sample Building
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Cognizing Urban Spatial Configurations
• To decide how to navigate the urban grid, we must have some ‘picture’ of its geometric and topological properties.
• This is why we say that before cities are social products, they are human products. They reflect how our minds read their ambient space and use it to guide both their actions and their bodies in space.
• Moreover, insofar as cities are human products, they tend to be universal, and insofar as they are products of culture, they tend to be differentiated. The individuality of cities arises because both of these are partial orderings against a random background, so a large number of idiosyncratic facts also shape cities.
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Towards a Theory of UrbanConfiguration & Cognition
• Our theory of how we cognize urban configurations requires that human beings interact with spatial complexity in their ambient space by building a ‘picture’ of its geometry and topology. Is this possible?
• We have recently had some very strong evidence that this is the case, but showing quite unambiguously that people use the geometry and topology of their spatial environment as the main guides to navigation, rather than, say, simple distance minimisation or landmarks.
Space
Synta
x La
bora
tory
Th
e B
artle
tt, UC
L
Conclusion
• This has a consequence of huge importance for urbanism. It means that people are reading the architecture of the grid in order to move and animate the city. They are not responding like automatons to the simplicities of location and distance.
• The architecture of the large scale urban network is then the prime determinant of how the city functions, and how they become the diverse and wonderful things they are.
• The implication is that we have to reclaim the large scale architecture of the city for careful and knowledgeable design.
