Nick S Dalton sdalton@cs.ucl.ac.uk

1. Space Syntax: Space, Configuration & Navigation Nick S Dalton sdalton@cs.ucl.ac.uk

2. Why are architects interested in graph theory?

3. Creating successful buildings & urban spaces Broadgate city of London

4. 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.

5. 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

6. 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.

7. 1970’s work began at the unit for Advanced Architectural studies (UAAS) Bartlett School of architecture University College London Looking for a ‘language’ or ‘grammar’ of space. 1983 - Architectural Morphology by J.P.Steadman 1984 - The Social Logic of space Hillier &Hanson

8. 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

9. 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.

10. 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

11. 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

12. Are these buildings ‘similar’?

14. Axial Lines

15. The axial network Traffic (node and link) a b axial a b c

16. A ‘Beady Ring’ Settlement

18. Line Representation of Spatial Configuration

19. Axial Lines

20. ‘Justified’ Graphs Mean depth = 1.43 Mean depth = 2.29

21. ‘Axial Integration Map’

22. Oxford Axial map (out of date) You are here

23. Central Oxford (out of date) You are here

24. Oxford City Center

25. Central Oxford (out of date) You are here

26. images of London

27. Observing of patterns of movement

28. Spatial Configuration Correlates with Movement The correlation between the log of observed adult pedestrian flows and radius 5 integration, (r=.726, p<.0001, n=466) Axial map of London, 17,000 lines, coloured by radius 3 integration. Correlation between normalised vehicular flows and a fitted variable including radius 3 integration and net road width, (r=.91, p<.0001, n = 395)

29. 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.

30. Spatial Configuration Embodies Culture in Co-presence Shiraz Den Haag Axial map of Tokyo, 70,000 lines, coloured by radius-n integration. Manchester

31. Relativisation 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)

32. ‘Justified’ Graphs • Radius ‘3’ exclude include Mean depth = 1.43 Mean depth = 2.29

33. 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?)

34. Relativisation Normalization

35. Normalization maximum total depth minimum total depth

36. Relativisation Normalization Integration = 1/RRA

37. Radius 3 Mean depth Oxford Street

38. Radius 3 Integration Oxford Street

39. Social: Teenage Socialization 1970’s housing in North London has found problems of youth socialisation Spatial segregation and complexity freeze out through movement Teenagers’ and children’s space use patterns colonise strategic but isolated spaces Adult movement patterns are centre to edge

40. Spatial Layout Drives Communication& Innovation at Work Moving and static space use in HHCL All line analysis of spatial layout Perceived usefulness and frequency of being seen for ‘creative’ staff Perceived usefulness and frequency of being seen for all staff

41. 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]

42. Extra Time • Small world or not small world ? • Intelligibility (measure) • ‘nameing’ places • More localization methods • Highly non planar mapping

43. 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.

44. Is a city a small world? • Path length distribution is also wrong for a small- world ( but consistent across all axial maps)

45. 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

47. Maiden lane estate

48. degree Maiden lane estate Barnsbury integration Correlation between Radius3 and Radius Infinity

49. Intelligibility Mapping

50. Camden town Summers town