1. Exploring The Relationship Between Urban Morphology And Resilience In A Few Neighbourhoods In Pretoria Darren Nel & Karina Landman University of Pretoria

2. Contents Introduction Resilience and urban form Comparison of four neighbourhoods The evolution of the suburban tree Conclusion 2

3. Introduction Recent studies in urban planning highlighted importance of urban resilience Of these – few starting to show relevance of urban morphology for resilience –Attributes & indicators –Also linked to typical structure: tree or leaf –Paving way for new ways to study urban phenomena 3

4. Urban Resilience Amount of change system can experience without collapse or total transformation Specific sub-systems more vulnerable to such changes due to disturbances –Maybe because it is still recovering from disturbances or shocks Important to understand pattern of disturbances and ability of urban system to deal with these to strengthen resilience 4

5. Resilience and urban form “Urban resilience can be understood as the robustness of urban structures and networks against random failures” (Salat 2012) Failures: small scale (disruption in local transport networks or energy supply) or large scale Influenced by urban form 5

6. Lattice (tree) or semi-lattice Alexander (1965): Cities may reflect lattice (no overlaps) or semi-lattice (overlaps) City should not be a tree – Need to allow for social & spatial overlaps 6

7. Tree or a leaf Salat (2011): 2 paradigms –TREE: Disconnected and closed (travel far) –LEAF: Connected on intermediate scales More resilient: Fractal structure Multi-connected Complex on all scales 7

8. Resilience and urban form Histories of cities have evolved from leaf-like structures to tree-like structures with consequent loss of efficiency and resilience (Salat 2011) 8

9. Change over time (Salat 2011) 9

10. Indicators COMPLEXITY INTENSITY DIVERSITY PROXIMITY CONNECTIVITY 10

11. Complexity Quality environments: complex, diverse & with overlap Due to incremental change and adaptation over time Essential for resilient city: –Rich urban fabric through multiple points of contact, engage & interface –Link to connectivity & diversity (Salat 2011) 11

12. Connectivity In historical city it grew, in Modern City over-simplification reduced connectivity Understood through role of streets & intersections Need high connectivity, mechanisms to create new connections & low control Thus adaptive capacity critical – ability for self-organisation Le Havre (Salat 2011) 12

13. Diversity Complexity & adaptive capacity enhanced through diversity Among similar objects at same scale –E.g. population groups, income groups, housing units Or objects at different scales –E.g. metropolitan facilities or landmarks in selective areas Increased diversity also allows for greater redundancy and thus ability to cope with disturbances 13

14. Proximity Diversity also linked to proximity Average distance between two things –E.g. home & leisure / home & work Aim – minimum distance to reduce travel needs and related costs & energy 14

15. Intensity (density) Biggest opportunity for generation of urban opportunity through intense interactions & high levels of population support Link to complexity & diversity Concentration of object in given area -E.g. people or housing 15

16. Indicators Indicator Complexity Diversity Connectivity Proximity Intensity 16

17. Measurements Indicator: DiversityMeasurement The number of different usesThe number of uses within the area Number of road hierarchies The number of different road hierarchies within the area Indicator: ConnectivityMeasurement Intersections per km² Cyclomatic complexity of the car grid (per 0.64 km²) µ = L - N +1 (L: number of links; N: number of nodes) Average distance between intersections car grid (m) Mean value on the selection of the length of links between two intersections External Connectivity (How easy is it to get outside of the area) The number of connections to the surrounding area 17

18. Measurements (2) Indicator: ProximityMeasurement The mean distance between two destinations Average distance between two things (nearest shopping centre – straight line distance) Indicator: IntensityMeasurement Surface occupied by road network (%) 18

19. Connectivity –Nodes (Intersections) –Connections –Distance between intersections –Cyclomatic complexity Measurements (3) 19

20. Selected study areas: older areas Typical older neighbourhood, BUT closed-off Typical older ‘open’ neighbourhood 20

21. Analysis of two older neighbourhoods Typical older neighbourhood in Brooklyn –Grid pattern Typical older neighbourhood –Internally: grid pattern –BUT closed-off 21

22. Case 1: Brooklyn 22

23. Brooklyn: unit of analysis (800 x 800 m blocks) 23

24. Brooklyn; Proximity 24

25. Does not lend itself to large enclosures 25

26. Case 2: Irene 26

27. Irene: unit of analysis (800 x 800 m blocks) 27

28. Irene: Proximity 28

29. Selected area of concentration 29

30. Concentration of different types 30

31. Concentration of different types 31

32. Selected study areas: gated areas Enclosed Neighbourhood Security Estate 32

33. Analysis of two types of gated communities Enclosed neighbourhood –Existing area closed off for security purposes Security estate –Private development 33

34. Case 3: Newlands 34

35. Case 3: Newlands (enclosed area) 35

36. Newlands: Unit of analysis (800 x 800m block) 36

37. Newlands: Proximity 37

38. Most of Pretoria east: suburban layout 38

39. Case 4: Silver Lakes 39

40. Silver Lakes: unit of analysis (800 x 800 m block) 40

41. Silver Lakes: Proximity 41

42. The evolution of the suburban tree Indicator What is being calculatedBrooklynIreneNewlands Silver Lakes Intensity Surface occupied by road network (%) 9.115.437.524.8 Connecti vity Connectivity of the car grid31.628.1 12.5 Cyclomatic complexity of the car grid (per 0.64 km²) 25261411 Average distance between intersections car grid (m) 150152147224 External Connectivity (How easy is it to get outside of the area) 34232 Proximity The mean distance between two destinations (nearest major shopping centre – straight line distance) > 1 km 1 - 2 km Diversity The number of different uses< 6 1 2 Number of road hierarchies2121 42

43. The evolution of the suburban tree Salat (2012) ABCD 43

44. The evolution of the suburban tree Salat (2012) ABCD 44

45. The evolution of the suburban tree Adapted from Salat (2012) ABCDE Should a gated community be considered as a new type of urban morphology or just the ultimate manifestation of suburbia? 45

46. The evolution of the suburban tree Evolution of modernistic planning In Tshwane 46

47. The evolution of the suburban tree Evolution of modernistic planning In Tshwane 47

48. Conclusion (1) Gated communities represent an evolution of modern town planning principles Can be considered as the ultimate representation of suburbia with a wall In terms of morphology and function – very different from typical Medieval towns that were complex and well connected 48

49. Conclusion (2) Suburbia & typical gated communities can be well connected internally but disconnected with the larger urban fabric. Therefore it tends to follow a typical tree-like structure However, a city is/should not be a tree –As a tree is not resilient –Tree-like structures did not perform well in terms of indicators for resilience –Therefore, based on morphology, suburbia and the typical gated community is not likely to be very resilient Need a city of leaves to enhance resilience –To accommodate complexity, connectivity, diversity, proximity & intensity 49

50. Questions? 50

51. Fragmentation 51

52. Fragmentation 52

53. Fragmentation 53