Third International Workshop on "Geographical Analysis, Urban Modeling, Spatial Statistics"

1. Valerio Cutini [email_address] The periphery as a spatial pattern Working on the edge of town The International Conference on Computational Science and its Applications Università di Pisa - Dipartimento di Ingegneria Civile ________________________________________________________ L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali ICCSA 2008 – Perugia, June 30 th - July 3 rd

2. The notion of periphery In the common sense, the notion of periphery generally refers to several different meanings marginalization physical distance landscape uniformity functional weakness poor land values few public facilities economic depression segregation physical distance criminality References like that appear to share nothing but a negative meaning The periphery as an urban disease The periphery as a problem

3. A configurational approach to periphery Here, the notion of periphery will be approached in a configurational mode Such a view, though partial and not exhausting, allows a better comprehension of several questions The periphery as a spatial process , depending on the configuration of the urban grid How do urban areas get peripheral How can we do to redevelop such areas Which urban areas can be said peripheral Which spatial pattern characterises such areas

4. The thesis of this research. 1 The thesis we aim at verifying is that Not only the position of an urban area with reference to the located activities , space does matter but also its spatial pattern with reference to the whole urban grid and even its intrinsic spatial features actually influence the way the space itself is used, and concur in determining its level of marginality

5. The base of configurational theory Configurational analysis could hardly be considered as a general urban theory We’d better regard it as a complex of techniques based on two different points of view over urban phenomena The assumption of the urban grid as the primary factor in the formation of movement in the location of activities 1 2 The interest towards the urban grid with regard to its configuration valerio cutini

6. The base of configurational theory. The urban grid It’s the structure of the paths of an urban settlement what dictates the distribution of traffic flows and then, as a consequence, the preconditions for the activities location The urban grid, hence, implicitly contains the vocation of each area to house activities, according to the benefit they derive from the presence of traffic valerio cutini

7. Configurational vs interactional logic The urban grid merely provides the spatial impedance between couples of activities Configuration of the urban grid Distribution of movement and activities input output The urban grid is the primary element in movement production and in activities location Consistency and position of the located activities Flows distribution and intensity of mutual interactions valerio cutini

8. The base of configurational theory. The configuration To analyse the configuration of an urban grid means to define the characteristics of each of its spaces as resulting from the relations connecting it to all the other parts of the grid In a configurational approach, each space in a settlement is appraised on the base of its connections to all the others Down to the facts, it means to define, for each single element of the system, a set of numeric values correspondent to its configurational indices The relation between any two spaces depends on their relations to all the other spaces in the system valerio cutini

9. The solution of the configurational problem The solution of the configurational problem follows the following logic The model is processed The configurational indices , output of the model, are determined The urban grid is reduced into a system axial map visibility graph 1 2 3 Axial analysis V.G.A. valerio cutini

10. The axial analysis In axial analysis the system to analyse is the axial map A complex of lines (the longest and fewest ones) that connect all the convex spaces of the grid The most significant configurational parameter, that we recognise capable to reproduce the distribution of natural movement (and hence the attractiveness towards activities), is the integration value The mean depth of a line from all the other lines of the axial map valerio cutini

11. The solution of the configurational problem. An example : Siena From the urban grid ... to the axial map to the distribution of integration value Siena valerio cutini

12. A different configurational technique: the VGA As a matter of fact, the operational Space Syntax techniques show some limits some subjectivity in the construction of the system the invariability of each configurational index all along the line Since the late ’90s a different configurational technique has gone arising, so as to overcome such limits: the Visibility Graph Analysis the insensitivity towards the role of the open spaces valerio cutini

13. The VGA : features On the basis of the same configurational approach, the VGA is characterised by the way the system to analyse is actually constructed In Space Syntax, the system is assumed as a set of intersected elements ( lines ), which connect the convex spaces of the grid In VGA, the system is constructed as a mesh of points ( vertices ) in mutual visual connection The only discretionary element in the construction of the system is the density of the vertices , that’s to say the detail level we expect on the results valerio cutini

14. The configurational techniques. A small example: Palmanova From the urban layout … … to the urban grid valerio cutini

15. An example: the linear analysis of Palmanova . 1 From the urban grid … … to the axial map valerio cutini

16. An example: the axial analysis of Palmanova . 2 From the axial map … to the distribution of integration value valerio cutini

17. An example: the VGA of Palmanova . 1 to the distribution of integration value From the visibility graph… valerio cutini

18. An example: the VGA of Palmanova . 2 to the distribution of clustering coefficient From the visibility graph… to the distribution of neighborhood size to the distribution of interaction value valerio cutini K < 1.0 1.0 < K < 2.0 2.0 < K < 3.5 3.5 < K < 5.0 5.0 < K

19. Some previous results. The correspondence integration vs activities Siena The results show an excellent exponential correlation between the density of the located activities (resulting from direct observation) and the integration value, resulting from the processing of the map Volterra Such results prove configurational analysis capable to reproduce, by means of the integration value, the distribution of the levels of attractiveness within a settlement valerio cutini

20. The thesis of the research. 2 The thesis is that an edge urban area, commonly recognised as peripheral, is actually characterised by a specific spatial pattern Those features, setting aside any social, historic, economic functional and architectural aspect, allow to recognise such areas as peripheral Configurational analysis, as based on merely spatial elements, allows an easy identification of those elements Moreover, on such basis we can identify the possible ways of removing the spatial factors of marginalization, so as to mitigate them

21. Our case studies As our case studies, we’ve here selected the urban settlements of Pisa and Leghorn , with reference to their edge areas More in detail, we’ve analysed the social housing areas , focusing with specific attention on those commonly recognised as suffering from segregation and urban disease valerio cutini

22. The first case study: Pisa and its social housing settlements 1925-1940 1950-1965 1965-1980 1980-1995 “ I Passi” “ Gagno” “ CEP” valerio cutini

23. The axial analysis of Pisa . 1 to its axial map From the urban grid of Pisa… valerio cutini

24. The axial analysis of Pisa . 2 to the distribution of integration value From the axial map of Pisa… valerio cutini

25. Pisa: the selected areas and their configurational pattern “ CEP” social housing area Axial map of Pisa Distribution of global integration value Distribution of local integration value valerio cutini “ I Passi” social housing area “ Gagno” social housing area

26. Pisa: the selected areas and their local configurational pattern. 1 Axial map of Pisa Distribution of integration value valerio cutini “ CEP” social housing area “ I Passi” social housing area “ Gagno” social housing area

27. Pisa: the selected areas and their local configurational pattern. 2 “ Gagno” Distribution of interaction value K “ I Passi” “ CEP” valerio cutini K < 1.0 1.0 < K < 2.0 2.0 < K < 3.5 3.5 < K < 5.0 5.0 < K

28. The second case studies: Leghorn The axial analysis. 1 to its axial map From the urban grid of Leghorn… valerio cutini

29. The axial analysis of Leghorn . 2 to the distribution of integration value From the axial map of Leghorn… valerio cutini

30. Leghorn: the “Corea” area. Global and local configurational pattern Distribution of global integration value Axial map of Livorno “ Corea” social housing area Distribution of local integration value valerio cutini “ Corea” social housing area

31. Leghorn: the “Corea” and “La Rosa” areas. Local configurational pattern. 1 Distribution of integration value Axial map of Livorno valerio cutini “ Corea” social housing area “ La Rosa” social housing area

32. Leghorn: the “Corea” area. Local configurational pattern Distribution of interaction value Axial map of Livorno valerio cutini “ Corea” social housing area K < 1.0 1.0 < K < 2.0 2.0 < K < 3.5 3.5 < K < 5.0 5.0 < K

33. Leghorn: the “La Rosa” area. Local configurational pattern Distribution of interaction value Axial map of Livorno valerio cutini “ La Rosa” social housing area K < 1.0 1.0 < K < 2.0 2.0 < K < 3.5 3.5 < K < 5.0 5.0 < K

34. The configurational pattern of the edge areas On the basis of the results so far, the analysed edge areas appear to share some configurational features Poor mean values of global integration The lack of strong local integrators A weak hierarchy in the distribution of local integration (sameness of I R3 values) The lack of strong interaction spaces (poor K values) on a global scale on a local scale

35. Conclusions Such results give use a hint for possible lines we can guess, while discussing redevelopment plans on urban edge areas To increase their mean global integration To set up some strong local integrators To modulate the distribution of local integration so as to establish a marked hierarchy To set up some prominent interaction spaces on a global scale on a local scale

36. Thank you [email_address]