Syntactic Analyses of Settlements


Santiago. Chile
Santiago, Chile


B. Hillier, University of Cambridge

Professor Bill Hillier.
Bartlett School of Graduate Studies. University College London..
e-mail: b.hillier@ucl




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A way of looking at the social, economic and environmental functioning of cities on a common basis.


This paper proposes that in addition to urban research which seeks to provide answers to policy questions involving the built environment, there is also a need for research which directly addresses the physical and spatial complexity of the built environment itself as the main variable of interest, and explores any effects it may in itself have on the functioning of the urban system. This type of research reflects the questions architects and urban designers typically ask, rather than those that preoccupy planners. For such research to be effective, the physical complexity variable must be controlled at the level at which real design decisions are made. Space syntax research attempts to do this by treating built environments as systems of space, analysing them 'configurationally', and trying to bring to light their underlying patterns and structure. Results from space syntax research into the structure and functioning of cities show a consistency which suggests that space can be used in this way as a general means of investigating the structure and function of cities, that is, it may be the common language of the city. On the basis of this common language, it is argued, it should be possible to build a domain theory of built environments as structural and functional entities in themselves, and this will lend greater precision to studies of its interactions with other domains.

Some questions and answers about complexity

The first sentence in any discussion about the science of cities usually contains the word 'complexity'. One of the most obvious forms this takes is the sheer physical and spatial complexity of the city as an object. There is, however, in most urban research, a strange silence on this aspect. The reason is simple: no one knows how to control the physical complexity variable. There is no formal language is which differences between one form of complexity and another can be described with the required rigour and consistency, and without controlling the variable we cannot measure its effects. What we cannot measure we prefer not to discuss.

Space syntax research about cities (1) seeks to redress this balance. It addresses first a problem of description: how can the physical complexity of the city be described with sufficient rigour and consistency to permit it to be controlled as a variable in research ? It gives what to some is a surprising answer: that it is best captured by representing it not as as physical stuff, but as the system of space created by the physical stuff. This is not as odd as it sounds. Buildings are physical things, but their purpose is to create the spaces and interconnections that we use. The effect of every physical intervention is to create or modify these space patterns. Cities may be aggregates of physical stuff, but space is the universal stuff which holds the physical stuff together and gives it its overall form.

On the basis of spatial representations (it turns out that more than one are needed) of the city, space syntax then asks one question: does the form the spatial complexity of the city takes make a difference, and if so, what does it make a difference to ? It seeks answers by one strategy: it analyses spatial representations of the physical city to try to understands their structure, and then investigates in what ways this structure is related to observable function. To the extent that results are consistent, theoretical explorations become possible. Movement, land use patterns, social and economic performance, crime patterns, and many other aspects of function have all been investigated using this method, with results that suggest that its may be possible to think of it as a general means for investigating the relation between the structure and function of cities. Space may indeed be the common language of the city.

The idea of space syntax originated not in planning but in architecture, with its need to answer questions about what impact different design choices about physical and spatial structure are likely to have. The question addressed by space syntax research is always: what, if any, is the effect of the built environment in itself on what happens in cities. The approach can be contrasted with policy-oriented urban research which seeks to understand what variables, including built environment variables, are involved in seeking overall social goals (such as energy conservation), the answers to which are are more likely to be found in regulation or behavioural change rather than through change to the built environment, with the protracted timescales that entails.

But although the space syntax research programme originates at the architectural scale, the questions is addresses are increasingly relevant to cities as we now see them: that is, not as once-for-all planned objects in a stable end-state, but as complex global structures which emerge from innumerable local decisions over a long time scale. In seeking to describe and analyse space, space syntax seeks to understand the emergent structure of the physical city, and to account for both its constructive functional logic and its functional impacts. Although the main applications of space syntax today (60 major projects in the past 5 years through UCL's Space Syntax ) are in predicting the likely effects of architectural and urban design choices, all this is predicated on its prior ability to analyse urban spatial structure in a way which is informative about function. Without theoretical knowledge at this level, applications would be guesswork.

Analysing spatial complexity

Research which seeks to investigate the impacts of built environments in themselves requires the built environment variables to be controlled with much greater precision than would be normal in policy-oriented research. The level of precision is easy to specify. It is the level at which design decisions are made in real world projects. Taking a spatial approach allows us to do this. Space syntax models work by taking some pattern of real space - in cities usually the full street network - and analysing it using simple mathematical tools that typically relate all elements to all others up to some limit. We call this approach 'configurational', defining this as the study of relations which take into account other relations in a complex (Hillier 1996a, Chapters 1 and 3). This simple strategy turns out to be quite unexpectedly powerful in detecting patterns in what might otherwise appear as inchoate complexity. For example :

Axial Map of Central London

It's a representation of part of the street network of London as the 'fewest and longest' (i.e. street names are irrelevant) lines that cover the system. As so often with spatial structures in grown cities, there appears to be no obvious geometric order, or indeed any other kind.

In fact it has a powerful interior logic, which is brought to light by analysing the system not on the normal basis of treating the nodes as spatial elements and the street sections between them as (weighted) links, but by taking the lines as (unweighed) elements, and asking simple topological questions about their interrelationships, using graph theory.
For example:

Global Integration of Central London

It's a simple 'syntactic' analysis in which each line is picked up in turn and the 'complexity distance' calculated (that is the minimum number of intervening lines that must be used, in whole or in part, to go from one line to another) to all other lines in the system (that is, the limit of the measure, or 'complexity radius', is in this case no limit, or radius-n). The map is then shaded dark to light (red to blue in the colour version) according to the total sums: the lower the total the darker the line (2).

The smallest total in this case is for Oxford Street, which happens to be the main shopping street (the busiest in Europe) and the next smallest totals are for the lines that link Oxford Street to the City of London (the historic core and current financial centre), with the next few linking these towards the edges of the system in several directions. We say that this measure indexes the 'global integration' value (its integration with respect to all others) of each line, and that the structure brought to light by this measure is the 'integration core' of the city for radius-n. The pattern shown in Figure 2 seems to correlate with the intuitive idea we have of the large scale structure of London , with the West End as the most integrated area, followed by the City, then a series of areas to the west, south and west. Little of this 'integration core' is south of the river. Overall, the analysis seems to make some kind of limited sense in terms of both how London is structured and how it functions.

The picture is suggestive, but evidently partial. It omits far more that it includes.

Local Integration of Central London

However is the same analysis but carried out with a restriction of three lines on the radius of the measure. This measure is called 'local' or 'radius-3' integration, because it picks out a much more localised structure, though still with Oxford Street and the West End area dominant. Rather than give a picture of the gross area structure, the measure seems to give a more detailed picture of the movement structure, even the sinuous wandering routes that every Londoner knows are often the best ways from a to b.

These are interesting structures, but they are only pictures. Do they actually make any functional sense ? It turns out that they do, and in many different ways. To understand this, we must explain a key result of space syntax research, one that seems to be implicated in many other results: that the pattern of spatial integration is in the urban grid is a prime determinant of movement patterns if the system. This sounds improbable, so the type of study that leads to the conclusion needs to be explained.

A key result

The technique is simple. An axial map of an urban area and its context (which must be large enough to account for the pattern of movement into and out of the area) is constructed and analysed :

Baltic House Area; Global Integration

It shows a case study in the City of London in connection with a major architectural project. First, the axial map is analysed and a range of numerical values, including integration at different radii, are assigned to each line element, indexing by colour (or shading in black and white) for graphical clarity in the usual way. Observations are then made at different times of day of movement flows along each street segment by counting people passing through imaginary 'gates', and indexing them in flows per hour through that gate.

Baltic House Area; Rush Hour Average (Adults/ ph)

The various spatial values for the lines are then compared to the movement flows by simple and multiple regression.

Correlation b'teen Global Integration and Rush Hour Movement

It shows the degree of agreement between global integration and rush hour movement rates, with an r-squared of .77. Midday rates correlate similarly with radius-3. This is a fairly typical result. In most studies the best performing spatial variable is radius-3 integration (in the City case study the good correlation with radius-n during the rush hour is due the to location of the main transport interchanges on globally important lines), with R-squared values usually between .65 and .8, depending on the smoothness of the built forms surface, that is the degree to which the built forms and infrastructure which attract and generate the movement are uniformly distributed throughout the grid. Where they are not - for example there is a main shopping street - then normally this extra attraction will have occurred on a key movement line, and the multiplier effect that the extra attraction has on movement is captured by taking the square root or logging the movement variable. The degree of transformation required to linearise the movement indicates the degree to which extra attractors are present in the system. In general the only other variable required to model movement is knowledge of these special attractors. This may be as simple as average building height in an area.
Significant results also exist for vehicular movement. For example in a recent study of five areas of London (Penn et al 1998) the r-squared for all the areas taken together and correlated against the axial map of the whole of London was .68 for 477 observed location, with much higher values for some areas taken individually. Combining this with net road width (road width minus car parking: not truly an independent variable because it will have been adjusted in the light of flows) the r-squared rises to .84.


In a more recent study of 16 areas in Santiago de Chile (see below for account of study) the r-squared for spatial configuration alone was .54 for 212 locations without taking net road width into account, again with much higher values within most areas taken separately (though on the basis of the same axial analysis).

These results are now supported by dozens of similar studies, mainly of pedestrian movement in different parts of the world, showing that under normal circumstances (essentially a reasonably homogeneous distribution of built forms) the spatial configuration of the urban grid is in itself a consistent factor in determining movement flows. Some key studies are reported in Hillier et al 1987, Peponis 1990, Hillier et al 1993, and Read 1997. The robustness of this relation is in fact tested at least once a week in the work of the Space Syntax Limited, since most design applications involve a movement study. For example the recent World Squares for All masterplan for the Whitehall area of London with Sir Norman Foster, including the re-engineering of Trafalgar Square, was done on the basis of a syntactic study of the spatial structure and pedestrian movement patterns in the area.

Theoretical developments

The purpose of this research, however, has never been to build a model for accurately predicting pedestrian or vehicular flows, but to estimate the degree to which the urban grid configuration in itself influences movement. It is the independent effect of the built environment that we seek to clarify. From the results we have, two theoretical propositions have been developed concerning the nature and functioning of urban grids, both of which have proved of great usefulness for design. The first is the theory of natural movement , which proposes that to the degree that the distribution of the built forms which generate and attract movement in an area is homogeneous, then, other things being equal, movement in the spatial system linking the buildings will be determined by the grid configuration itself (Hillier et al 1993). The 'natural movement' in a system is thus the proportion of observable movement along lines that is produced by the structure of the grid itself rather than special attractors. There is a problem of course. Surely movement will itself attract attractors ? This leads is to the second theoretical proposition: the theory of the 'movement economy' (Hillier 1996a).

This proposes that there is a 'central dynamic' to the spatial growth of cities, which links the evolving grid structure and its natural movement to the distribution of land uses and built form densities, and even gives rise (though in different ways in different 'spatial cultures') to the local area structures that are found in historically grown cities. The mechanism is that as the accumulation of new built forms creates new spaces in the expanding settlement, the emerging structure of the spatial pattern gives rise to a natural movement pattern. Land uses which seek movement, such as markets and retail, then naturally gravitate towards higher movement locations, while others equally natural prefer low movement locations. The extra attraction in the high movement spaces then creates a multiplier effect on movement, which then attracts more, and more diverse, movement-seeking uses, and vice versa. In this way, the settlement pattern naturally evolves towards a seamless network of busy and quiet areas, with the busiest in the spatially most integrated areas, the whole process being initiated in the first place by the spatial configuration of the grid. While the theory of natural movement notes a regularity, the theory of the 'movement economy' tries to account for the process by which the apparent affinity between grid structure, movement, land uses and even building densities appears (as Figures 2 and 3 suggested) to to arise in naturally evolved urban grids like London.

Sites and serves settlement in Santiago : a case study in the movement economy

A recent study in which the theory of the movement economy proved useful was a study of the evolution of 'sites and services' settlements in Santiago , Chile funded by the European Union. This research began with the suspicion amongst Chilean social scientists and architects studying the development over time of 'sites and services' settlements in Santiago that spatial, locational and design factors were implicated in the very different levels to which settlements had developed since their common foundation in the early nineteen seventies. From similar origins, some had become well consolidated and seemed to be thriving, while others remained much less consolidated and others seemed to have developed social problems. The aim of the study was to ascertain how far and in what way spatial factors might have contributed to these differences. The research strategy was to combine the social scientific expertise and experience of the Universidad Catolica de Chile in the investigation of the social and physical aspects of settlement performance, with the spatial modelling and observational techniques of the Space Syntax .

The analysed map of Santiago , indicating the 17 settlements originally studied (one was later eliminated as a special case) is given here :

Santiago; Location of Site and Services Settlements

The research procedure was:

- the construction of indices for settlement consolidation (including innovative use of the Delphi technique, leading to aseparate publication - Greene, Iacobelli & Ortuszar, 1997) covering housing, communities and neighbourhoods, and the combination of all three, a questionnaire to 553 respondents, and a full survey of 17 settlements;

- the direct observation of the functioning of the settlements, covering land uses, commercial and social activity, and pedestrian and vehicular movement patterns;

- the construction of a 'space syntax' computer model of the whole of Santiago , including all the settlements;

- the construction and analysis of data tables for 553 individuals and 17 settlements, each covering all aspects.

The key results were at the settlement level. Data analysis was in two stages. First, a correlation study was carried out to establish which variables were prima facie involved in each aspect of settlement consolidation. Then multiple and stepwise regression were used to seeks answers to specific questions about the patterns of influence, and in this way to build a picture of any possible process by which spatial, locational and land use factors might have played a role in the pathways of development of the settlements. Correlation matrices are given in :

Santigo; Correlation Matrices

The first stage analysis showed that social factors as varied as income, education, spending patterns, age profiles, numbers in household, numbers of children, and vehicle ownership were virtually uncorrelated with the consolidation variables. Spatial factors, on the other hand, were suggestively correlated with all four indices, and space use and movement factors even more so. Strikingly, the strongest correlations of all for the consolidation indices were with the degree to which informal business activity developed on the outward facing edges of the settlement. This 'edge commercial activity' was associated not only with greater consolidation of houses and a higher level of community development (these were the strongest elements in its correlation with the 'general consolidation index'), but also with lower reported experience of crime in the settlement, and (as might be expected) higher overall levels of informal economic activity in the settlement as a whole.
It shows a case where 'edge commercial activity' is strong :

Santiago; Caupolican-Las Torres, Macul.

and a case where it is weak :

Santiago; Villa El Rodeo, Huechuraba

with most informal commercial activity in the interior of the settlement serving the needs of local streets.

Why the difference ? The answer is quite simple; vehicular movement. The correlation between edge commercial activity and vehicular movement is the most powerful in the whole data set (R-squared .888), and is at the same time totally uncorrelated with vehicle ownership in the settlement itself :

Santigo; Scattergrams

What then is the determinant of vehicular movement rates ? The answer is equally clearly: the spatial structure, and in particular how the settlement is embedded in its local area. The best measure we have so far found (work is continuing) we call 'local spatial advantage'. This is calculated by taking a circular area up to 1.5 kilometres from the settlement edges, and calculating local integration on the basis of this metrically uniform system (regardless of the degree to which this area was developed). This is illustrated in :

Santiago; Caupolican-Las Torres, Macul.

for the 'weak edge' case and figure for the 'strong edge' case :

Santiago; Villa El Rodeo, Huechuraba

In effect, local spatial conditions create more or less local vehicular movement, edge commercial activity then takes advantage of this to the degree that it is available, this increases the overall level of informal commercial activity in the settlement, and it is this complex that is associated with higher levels of housing and community consolidation - a clear case, it would seem, of the movement economy process in action, as well as of petit bourgeois virtue !

Why then is this process not correlated with income ? Earlier studies at the larger scale of the 'local authority areas' had shown that average incomes for areas in Santiago were almost wholly a function of mean education levels (r-squared .964), although spatial integration was also a strong correlate. In these settlements too income was correlated strongly with both education levels and 'local spatial advantage', with the two between them accounting equally for over 70% of the variance in the mean per capita income for households in the settlement. Edge commercial activity was positively correlated with income, but weakly so and below the threshold of significance. Income and education were then either uncorrelated with or negatively correlated with the consolidation variables. At the same time, income and education both correlated quite strongly with the purchase of consumer durables ?

At this stage (again, work is still continuing) our belief is that two processes are in operation in the settlements, one spatial and the other independent of space: on the one hand, there is a spatial process led by the edge oriented economy, which leads to greater activity within the settlement, and then to greater security and settlement consolidation where this is successful; on the other, a nonspatial process led by education levels, and associated with working outside the settlement (more 'professional' jobs), and contributing to the settlement more as a consumer than as a producer. Local spatial advantage plays a role in both processes. For educated people, local spatial advantage is associated with greater opportunities working outside the settlement, while for those with less education local spatial advantage provides informal economic opportunities. The former process is associated with greater income but less settlement development, and vice versa. The chief factor in consolidation seems to be the degree to which economic activity within the settlement gives people a stake in the settlement, and leads them to invest in its future, and this is governed by a process which is initiated by space. More educated people work outside the settlement, invest in it less, and buy more consumer goods, presumable because they intend to leave the settlement and invest in movable rather than fixed goods.

Can spatial design be implicated in the social decline of new housing areas ?

Movement has also been shown to be critical in studies of the decline of new housing areas, though in a very different way.

Maiden Lane Estate

That's an axial map of the area of central London around the Kings Cross Railway Lands site (3). The housing estate to be discussed here is ringed above the site. It has a certain notoriety because it went from being a much-praised award-winning design to being described by the police as a 'ticking time-bomb' in less than four years. The axial map of the estate shows a number of properties that are very common in social housing: the axial scale of space is dramatically reduced; the spatial pattern is very much more complex; and the estate overall displays structural segregation, meaning that there is no pattern of integrated lines linking the interior of the estate to the surrounding area. Are there consequence for people from this type of spatial pattern, and can it in any way be implicated in the rapid decline of the estate ?

To suggest an answer, we must first be clear how this estate differs structurally from normal street based urban areas. In inner London , for example, most named areas have a structure similar to that found for London as a whole: an integration core composed of a partial grid at or near the centre linked by strong lines to the edge in different directions, with the quieter, more exclusively residential areas lying in the interstices formed by this pattern. Figure 16. This turns out to be expressible statistically. Figure 16a. The lines that connect edge to centre, and the centre itself, are stronger local integrators than other lines in the area, while the interstitial areas are less so. The means that if we plot local against global integration for those lines against a scattergram for the whole of London (Figure 16a) we find that well-formed areas tend to have a linear scatter crossing the main regression line at a steeper angle. The linearity of this scatter, its slope, and its location in the overall scatter are powerful numerical indicators of the characteristics of an area. However, if we take the ringed housing estate we find a scatter which is layered rather than linear :


with each layer more or less vertical (each line corresponding to one step of axial depth into the estate), and is bottom left in the scatter meaning strongly segregated, and so on.

This type of spatial structure creates a local situation in which there is no relation between internal and external movement, the average background encounter rate is reduced by an order of magnitude (from about 2.7 people per minute to .27 people per minute, or one person every four minutes), and the lack of natural space occupancy becomes associated with the social misuse of these 'structurally abandoned' spaces. The mechanism by which the social misuse of space is facilitated by spatial design is that in most street-based areas, the space structure is such that natural movement leads to all social groups - men and women, adults and children, inhabitants and strangers, and so on - using the space pattern in a similar way, so that all spaces are used by all categories. This yields a background pattern of natural co-presence and mutual surveillance between categories. This can be merely pleasurable, but is can also become important when it is between inhabitants and strangers or adults and children. In overly complex housing estates there are virtually no strangers (the scale and complexity of the space excludes it from local natural movement networks) and far fewer inhabitants. In such circumstances strangers, who seem normal in streets, become a source of fear, because their presence is unexpected.

However, because the space structure is much more complex in housing estates, and because relatively little of it is used, the way is open to exploitation of the empty spaces by groups who take a different view of space. For example, children and teenagers tend to form larger groups, and occupy not the spaces that are used for adult movement, but those that are not. This has a critical effect: the natural surveillance from adults to children and teenagers is broken. Compared to streets, children spend more time in larger groups and out of contact with adults in complex housing estate. Greater vandalism tends to be found in and around these spaces. This process increases fear on the estate, which is already increased by the very low background encounter rate, and this is in turn exacerbated by the social misuse of the spaces which are not ordinarily used. This creates the sense that the estate has problems, and this decreases its desirability for incoming tenants. From then on the estate is on the way to stigmatisation. Thus a social process can be initiated by a spatial one. In a sense, the symptoms bring about the disease. Once again we see that space structure and its impact on movement are critical to the link between the built environment and its social functioning. This process is described in greater detail in (Hillier 1996a, Chapter 5).

Does urban layout affect the pattern of urban crime ?

In other urban issues the mechanisms of influence from space to behaviour are less complex, but no less critical. In trying to detect any effect of urban layout on the spatial distribution of crime, for example, the mechanisms would be expected to be simply what design factors would cause a criminal to think one location was more vulnerable than another. Even so, there is much confusion about the matter. There is a widespread tendency for people to think that the mechanism is that the more people pass your front door the more likely one of them is to be a thief. Those who have read about 'defensible space' (Newman, 1972) will think that there is a theory that backs this. In fact, something like the opposite seems to be the case. Other people, including strangers, keep you safe.

The technique here is in two stages:

New Town X (Burglary in dwellings shown by red dots)

We take an area and first create a map in which dots indicate the exact locations of different kinds of crime - burglary in this case. We then create a space syntax model of the area in its context (subject to the same strictures as before), and carry out the various analyses. We then superimpose the crime map on the syntax map, and proceed in two ways: first, look for visual patterns, and their relation to the visual syntactic patterns; then correlate syntactic values with crime rates. It is important in these cases to consider the lack of crime as well as concentrations. More significantly we take take analysis beyond the simple analysis of 'clusters' and show that although spatially dispersed, certain crimes tend to occur in specific types of syntactic location on the layout. For example, in the map shown, a designed area of New Town X, crime seems to be highest where the urban grid is most broken up (in effect creating most local segregation), and lowest where the lines are longest, and in fact most integrated. The linear routes through the estate have least burglary, and the most broken up, locally enclosed spaces the most.

This (and other results) runs against the general belief that spatial segregation decreases crime. On the contrary, recent results at an area level show that other things being equal (for example one not being in the city centre and the other on the periphery) a more integrated area is likely to have less crime that a more segregated one. We also find that crime is higher where access is through spaces which are unrelated to building entrances. In other words it is not the surveillance of the space you are in that is critical, but surveillance by neighbouring groups of houses on the way to your space. This interdependency is critical. For example, the use of a general cul de sac layout tends to create vulnerability by increasing entrance-free space, and greater delinearisation of spaces. In general, safety seems to lie in linearity (including occasional short linear cul de sacs attached to streets, but not cul de sac complexes) and in the continuity of building entrances through all spaces (rather than focusing entrances on a selected space to create a supposed 'sense of community') coupled to the minimisation of rear and side access. This research is being presented as a keynote paper at the forthcoming UK Home Office Crime Prevention College Conference on What Really Works on Environmental Crime Prevention in October 1998.

What effect does the street network have on urban pollution?

Once we have the technique of regressing values representing the 'configurational' properties of locations with functional values (such as movement rates) for that location, then we can apply it to any functional phenomena which can be located exactly and expressed as a number. For example, recent work has used space syntax to look in great detail at the spatial diffusion of pollution emanating from vehicles, and how it is affected by the configuration of the street grid, thus potentially affecting pedestrians. In order to monitor pollution in enough locations, a simple 'streetbox' capable of measuring carbon monoxide, temperature, humidity, daylight and windspeed with an accuracy within 5%, and which could be fixed to a lamp post was developed by Dr Ben Croxford and data downloaded periodically to a Psion Organiser. A syntactic model of a local street system was made and tested against a sample of real flow points. Two early findings were that there were huge variations in pollution both according to time and space. For example, within tens of metres of very high pollution streets, rates on local streets were no more than background. The effects of wind were also examined, and again this showed great variation according to wind direction and side of street. Taking all these factors into account, pollution levels were related to traffic flows, and good predictions were also obtained from the syntax model, which was also experimentally modified to take account of the prevailing wind :

Urban Pollution

Work is continuing on the modelling aspects of this in order to predict pollution levels in the fine scale structure of the urban environment, with a view to better understanding the exposure of pedestrians to traffic pollution.

Can there be a spatial theory of the city ?

The consistency of these result across a whole range of urban phenomena suggest that space may indeed offer something like a common language of the city. Many if not most of the relations between the form of the city and the way it functions seem to pass through space in some sense, and many also involve the space-movement relation. The fact that the most important of our results are about the urban structure itself are also suggestive. Whatever functional phenomenon we pursue, the use of syntactic techniques seem to make some kind of sense out of apparently disorderly urban patterns, and shows they have functionally sensitive structures. It is, it seems, these spatial structures that characterise cities, and it is these that relate the form of the city to its function.

Can we then go on from here and build a spatial theory of the city ? The fact that the most important of our results are about the urban structure itself suggest that this might be possible. It is clear from the similarities of the forms of cities all over the world that they grow according to a certain logic. If we could capture this 'generative logic', then it is likely that we could also understand how the evolving form of the city relates to how it functions. The idea proposed here is that the 'generative logic' of the city is essentially about space: more precisely about how the now piecemeal now orderly aggregation of buildings creates a continuous pattern of space which links the buildings together into a system and in doing so constitutes in itself the essential structure of the city. By learning the language of this spatial evolution - a matter of understanding first of all what all cities have in common spatially, and then considering the range of differences - we can learn to ask questions of the city and get intelligible answers. But we can only have a common language of space to the extent that it is also a theoretical language, and we can only have a theoretical language to the extent that it is the language of the city itself.

Reflections on the need for a domain theory.

It is easy to see that this type of research can serve the needs of designers. But how does this fit into the overall pattern of urban research ? In the long run, it may be best seen as answering the emerging need for domain theories in the study of cities, that is theories which deal with autonomous laws within domains such as space which need to be understood if we are to understand the relations across domains - such as the relations between space and society - out of which urban complexity is made. Space syntax is an attempt to build a domain theory of the urban object itself. Let us be clear why we need this ?

Cities are the largest and most complex objects that human beings make. With a few exceptions, they come into existence not through once for all design but through a process of growth and change spread over tens, hundreds, or even thousands of years. Each generation examines what it inherits, then extends, substitutes, re-arranges and adapts according to its needs, before passing it on to the next generation. What we call the city at any one point in time is as much process as object: an emergent structure created by a large number of smaller scale decisions, one of the large class of artifacts (like languages and societies) which human beings create but which remain puzzles for us.

For much of the twentieth century we have tried to use science to improve our understanding of the city. Even where this has been successful, the consequences have not been unmixed. Often we have solved one problem only to create another. For example, we reacted to the environmental problems of traffic by turning away from streets, and as a result, down graded public space and the activity it supported, increasing the social isolation of some of our communities. Policy was driven by research, and research could only deal with one issue at a time. We could not deal with the systemic interactions between the very different kinds of phenomena that make urban life what it is.

More recently, under the urgent influence of problems like sustainability, some of our scientific effort has switched to a more systemic study of cities, with the object of understanding the interaction between the built environment aspects of the city and the social, economic and behavioural phenomena that animate it. This research is aimed at urban policy: how should we guide the development of our cities in the light of broad social objectives. For example, if we are to save energy, we need to know whether this could best be achieved by re-engineering our pattern of settlement, or simply by regulating and managing behaviour in existing settlements, for example by increasing fuel costs or road pricing.

Suppose however that built environment variables did turn out to be important. The fact is that the huge inertia of the existing built environment is such that the timescale for bringing about change makes effective policy implementation unrealistic. It can even lead to absurdity. We have for example in general in Europe adopted a compact city policy, on the grounds that this will reduce the length of journeys and thus save energy. Although it will be decades before this has a significant effect, we have recently heard from my new colleague Professor Steadman that one effect of the compact city policy may be to increase the price of land in city centres and drive out residents, thus creating longer journeys to work, and working against the policy. Changing urban policy is, it seems, like turning a tanker, but with an added twist: by the time the tanker is turned, knowledge has advanced and it is time to turn again. The form of movement that emerges from this process needs little clarification.

It is clear from this that a policy orientation is not the only useful framework for built environment research. We have long since abandoned the utopian notions of 'end-state' planning through massive urban re-engineering and replacement. Effectively we have reverted to the historic reality of the city as a distributed process in which the whole emerges from innumerable local actions. In western countries most urban initiative is now in the private sector, and the role of planning is a regulatory one, its effectiveness limited by the timescale factors we have noted, and by its weakness in playing any initiatory role in projects. The motor of urban change is now once again the privately initiated and privately funded design and development project.

This has created a knowledge emergency. New kinds of knowledge are needed to support design and development, and to ensure that it carries out its tasks in a socially and environmentally responsible way. For the most part, the knowledge that comes out of policy research is in the wrong shape to serve the knowledge needs of this sector. It is too nonspecific, too lacking in detail, and too little oriented to the variables that designers and developers can manipulate, namely the physical and spatial variables of the built environment itself. Designers and developers needs to answer immediate questions about the impact of built environments: what would be the social, economic and environmental impact of developing this area or this site with this design and this relation to the surrounding urban context ? What would be the accumulative impact of similar interventions on the urban system over time ?

We need, in effect, to move towards a science capable of supporting evidence-based design, that is design which takes place in the knowledge of the social, economic and environmental impact of different kinds of intervention. What kind of science is required for this ? The answer is simple: research which treats the built environment not as one of a number of intervening variables in a policy question, but as the principle variable, as it is in the real world design and development process. Research in support of evidence based design is research which seek to understand the impact of built environments on how people, organisations and communities live their lives, and the accumulative effects of built environment decisions on the larger scale pathways of our cities and the longer term pathways of our societies.

Research with built environment as the principle variable will theoretically come in three kinds:

- Type 1 research which treats the built environment as an autonomous variable , in which we ask such question as: what are the possible forms for cities to take, what are the laws of emergence from local decisions to global patterns - how in short does the built environment behave as a form of complexity in itself ? The current rapid spread of work on cellular automata, some aspects of fractal theory, and also syntactic approaches to computer generation of settlement forms (for example, Erickson and Lloyd Jones, 1997) are all relevant to this.

- Type 2 research which (preferably in the light of type 1 research) treats the built environment as the dependent variable , and asks what kinds of social, economic and cultural processes modify the autonomous processes and give rise to the different kinds of built environment complexity we associate with different types of society and culture; and

- Type 3 research which (preferably in the light of types 1 and 2 research) treats the built environment as the independent variable, and asks what follows functionally from selecting one 'complexity strategy' for the built environment rather than another.

These three forms of enquiry are cyclic in the sense that knowledge of the relation between spatial configuration and movement - a type 3 effect - can then be fed back as a constraint into type 1 research to see how movement affects the evolutionary patterns of space itself (Hillier 1996a, Chapter 9). Both of these are then involved in type 2 questions about why different kinds of society adopt different spatial forms. In this sense the theory of the city as a movement economy is cyclic: it deals in some way with all three aspects of the built environment process. Any domain theory of the built environment will eventually need to be cyclic in this sense.

bh 8.9.98


1 - Space syntax also address issues of space in buildings, from the largest quasi-urban complexes down to the cross cultural analysis of houses.

2 - The mathematical basis for these measures was first given in Hillier et al 1983, and then in Hillier & Hanson 1984, with further discussed in Hillier 1996, and numerous other texts, including Steadman 1983.

3 - One of the earliest urban design projects in which space syntax was used was the Norman Foster masterplan for the redevelopment of this site. As a consequence, the surrounding area came to be studied intensively.


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