Urban texture and space syntax : some inconsistencies

This paper reports on a number of inconsistencies that appear in space syntaxöa well-known technique of urban analysisöwhen dealing with certain geometrical configurations. At a simple level, the analysis of regularly gridded urban textures (such as Manhattan's) reveals the difficulty of accepting the claim that space syntax allows the modelling of pedestrian choice making. In more complex cases, the distortion of two ideal textures produces a topological discontinuity, leading to the unacceptable situation where one single urban configuration produces two conflicting outcomes when analysed with space syntax tools. Several other points are also discussed, such as the difficulty of space syntax to take into account building height and land use, and its sensitivity to boundary conditions. Conclusions seem to suggest that the topological representation of cities, on which space syntax is based, discards precious metric information and is rather limiting. It is envisaged that with current increases in computational power new algorithms might allow a deeper understanding of urban texture, based on the full exploration of its metric and topological properties. This would contribute to answer the fascinating question which space syntax has helped to frame: what is the influence of urban configuration on social life? If you have not received one, it can be downloaded from http://www.pion. co.uk/ep/reprints.pdf DOI:10.1068/b3019 (1) Churchill is reported to have used this statement twice: first in 1924 at the Architectural Association in London, then in 1943 when requesting that the bombed-out British Parliament be rebuilt exactly as before. The quote appears in Brand (1994). Various measures of urban configuration are correlated with aspects of social life. In its initial form, space syntax focused mainly on patterns of pedestrian movement in cities. This has subsequently been extended to a number of other aspects, such as modelling urban traffic, predicting air pollution levels, assessing the occurrence of burglaries in different neighbourhoods, and estimating the potential for retail development in streets (see Space Syntax, http://www.spacesyntax.com). In recent years this versatile method of urban analysis started being used in simulation mode, in order to support experimentation and inform architectural and urban design. Usually, different options of a project are tested with space syntax and subsequently compared. This provides valuable feedback to designers and has already resulted in a significant portfolio of analysed projects, including major schemes by the architects Richard Rogers and Norman Foster. However, despite the growing (and glowing) success of space syntax and the fascinating questions on the use of space that it has raised, some of its findings remain controversial in the academic community. The discussion focuses mostly on the support used for simulations: a simplified representation of urban texture in just two dimensions, which does not take into account the dimensional property of streets (later referred to as `metric') but only the way they connect to each other. How is it possible to tell so many things about the urban environment with such a limited amount of informationöthat is, after having dismissed data such as the height of buildings and the size of streets? Hillier (1999) argues against these questions in a paper entitled `̀ the hidden geometry of deformed grids: or, why space syntax works, when it looks as though it shouldn't''. Some questions, however, remain open and are reviewed in this paper. 2 Space syntax basics Let us start with a brief review of space syntax. Major references in the field are the books by Hillier and Hanson (1984), Hillier (1996), and Hanson (1998), as well as the proceedings from the First, Second, and Third International Space Syntax Symposia held in London, Brasilia, and Atlanta, respectively. Selected papers from the symposia were reprinted over the years mainly in Environment and Planning B: Planning and Design and will be quoted below when relevant to the discussion. In this section the review will focus on the most used space syntax technique at urban level, the axial map. According to Hillier (1999, page 169): `̀ In the study of cities, one representation and one type of measure has proved more consistently fruitful than others: the representation of urban space as matrix of the `longest and fewest' lines, the `axial map', and the analysis of this by translating the line matrix into a graph, and use of the various versions of the `topological' (that is, nonmetric) measure of patterns of line connectivity called `integration'. '' How does the axial analysis work? The algorithm is simplicity itself. Imagine starting with an axial map, that is, a simple line representation of the street network made just of lines, as shown in figure 1 (the way to derive an axial map from a piece of urban texture will be discussed below). Then select a line (a street) as a starting point. This line will be intersected by a number, n, of other lines, which are labelled depth 1. Each of these n lines will then be intersected by m lines, which are labelled depth 2. And so on. In other terms, each line in the map is numbered according to how many changes of direction separate it from the starting line. This measure is generally referred to as depth and is a kind of distance: it represents the minimum number of changes of direction to go from the origin to any other segment in the network. 2 C Ratti