Network Visualization Tools for Urban Planners *

4 Network Visualization Tools for Urban Planners *

“Nowadays, we are no longer living in cities governed by principles of axiality formed from a hierarchy of clearly defi ned spaces – avenues, squares, streets, and so on – but in a graph. We are moving around in a map [and] big cities can only be designed, planned, developed and equipped through an abstract approach” (Teyssot, 1988). What means of representation do urban planners have, to make allowance for the exact status of the various connections inherent to the network city?

First there is the map. Networks have long fi gured in maps, which provide an adequate visualization tool for certain uses in certain conditions (Steinberg & Husser, 1988). Nothing has really replaced the road map in the eyes of a driver embarking on a long journey into unfamiliar territory. André Michelin, the man who championed and pioneered motor car use of the road network in France, codifi ed the appropriate representation (Ribeill, 1992). Its two-dimensional representation gives a now familiar means of picturing that network’s topology, conveying the potential kinetics it allows by means of the thickness and colour of the lines. Only its adaptability remains poorly represented. Which is precisely the problem. Road maps adequately represent the operator’s command over geometry, homogeneity and so on. But they do not purport to represent how the road system can, according to Fishman (1990), provide urbanites with opportunities to build the architecture of their own networks. Teyssot (1988) hints at the nature of the problem: “in New York, we are given no more than a split second to choose between a ‘Van Wyck Expwy’ and an ‘Interboro Pkwy’ before the interchange sucks us onto a one-way road to an unknown or unwanted destination”.

Maps are bound to give a fi xed, geometrical picture of the network. They have great trouble representing the density of multiple networks, the importance of connector nodes and, more broadly, all of the various features likely to adapt the networks to the uses of the many diff erent operators. While the road map, for instance, may be ideal for depicting major road routes it struggles or gives up trying to represent the urban road network. It is a matter not just of the scale but also of the nature of the information. The network’s various uses in the city cannot be represented by means of fi xed geometry or even topology. Parking places, traffi

c lights, and more or less temporary traffi c restrictions are critical factors, but they are changing all the time. Combined with the ever-changing nature of city-dwellers’ transactional networks (see Chapter 2), that makes it an impossible task for conventional

map-making. Academic studies have shown clearly the kinds of limitations placed on the operators at the various network levels described in Chapter 2 and, hence, on urban planners (Akierman, 1988; Off ner, 1990).

Technical network operators have sought to come up with their own solutions by developing dedicated representations tailored to specifi c design or operations-related tasks. By and large, they give up trying to depict the whole network, with all of its characteristic features, and concentrate solely on the part needed to perform a given task. So they are found to design their networks with the help of a simplifi ed functional diagram that looks nothing like a map or even a graph, leaving its territorial role unstated (see illustration 4.1).

* Previously published as « Représentation des Réseaux ». In: Dupuy, G., 1991, L’Urbanisme des Réseaux: Théories et Méthodes . Paris: Armand-Colin, pp. 133-143. Included with permission.

Chapter 4: Network visualization tools for urban planners

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Illustration 4.1 Samuel Insull’s representation of the Chicago electricity network, where the main aim was to show the full range of needs of the consumers connected to the network.

Source: Hughes (1983)

When work is to be done on the physical network, plans will be needed to pinpoint the networks’ various constituent parts together with their simplifi ed characteristic features: a certain diameter

cable, a certain type of valve, a power line of a particular voltage, a particular kind of transformer … in a particular place, at a particular depth beneath the road and so on. Those plans used to be hand- drawn, which made them especially painstaking to update. Nowadays, this is the quintessential realm of the geographic information systems that are thriving in the market thanks to advances in the fi eld of information technology (see illustrations 4.2 and 4.3).

These computer-generated models lend themselves well to the changes in scale needed to refl ect the network topology. However, they exclude most of the kinetic and adaptive features the operator needs just to manage network operations. The management centres have a block diagram displaying the network’s key points and linkages designed to provide a rapid grasp of an emergency situation. But representations such as these are clearly inadequate on their own, and need supplementing with partial schematizations (position of a signal, an open or closed valve, and so on), fi gures or even still or moving images (state of a crossroads in regard to road traffi

c, for instance) presented on demand, in

real time, on computer screens. Finally, highly schematized maps – often based on the more static than dynamic model of the road map – are proposed for communication with the user, which usually tends to be limited (illustrations 4.4 and 4.5).

When it comes to visualizing not the network itself but the eff ects of its topology, kinetics and adaptability on the user, it emerges that they can be displayed clearly on a map highlighting the major eff ects of network connectedness, connectivity and homogeneity: areas well-served by one or more

Urban Networks – Network Urbanism

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Illustration 4.2 Generative logic-based representation of a road network used by the French Institut Géographique National to build a geographic information system.

Source: Salgé & Sclafer (1989)

Chapter 4: Network visualization tools for urban planners

Illustration 4.3 Network plan produced by a localized GIS showing the wealth of detailed graphic information supplied just to depict the networks’ morphology.

Source: ARCINFO MAPS, ESPI Redlands, California (1988)

Illustration 4.4

The Tokyo subway and suburban rail networks made ‘simple’

Source: Supplement of Bulletin d’Informations Architecturales n o 133 (October 1989)

Urban Networks – Network Urbanism

Illustration 4.5

Montreal subway network (circa 1990)

networks, grey areas, isoaccessibility curves and so on (Steinberg & Husser, 1988). But this is a tricky form of representation to handle as it means having to focus on a particular aspect of those eff ects,

e.g. service quality or speed of access; and the fact is that this selectivity is hard to reconcile with the network’s wide variety of uses. Indeed, it is bound to draw attention to spaces benefi ting more than others according to the aspect selected, thus generating feelings of unfairness that hardly conduce to dispassionate communication with the users. So this type of representation tends to be confi ned to network design and evaluation procedures (see Dupuy, 1991a).

Does the urban planner fi nd in this panoply of representation models the right tools to carry out his or her work? Clearly, while it may be useful at times to refer to the representations used by the operators, urban planners need tools better suited to their assigned task. The fact is that they cannot do without even a simplifi ed means of visualizing the network’s relevant features and how its coverage area interrelates with others – entry/exit points, terminals, nodes, its relationships with other networks,

Chapter 4: Network visualization tools for urban planners Chapter 4: Network visualization tools for urban planners

The polar network is a representation tool devised chiefl y for the network design stages, meaning that it can be useful to operators and to urban planners alike. A simplifi ed model is produced by boiling the network down to a diagram depicting an intermediate state between the virtual and real network. It shows a series of points representing either key nodes within the network – vis-à-vis fl ows, how the network is used and so on – or poles located partially or entirely outside, and illustrating its relationship with other geographical areas. The points can be joined up with linking arcs that, when interlinked, form paths.

The points and arcs are given attributes. There is, for instance, a hierarchy of points – key points and the rest, to put it simply – and several relatively precise attributes for the arcs, or paths, including a Boolean attribute indicating, as in a regular graph, the presence or absence of a link between two points. In most cases, however, other attributes are added to denote the network’s kinetics or adaptibility. Depending on the attributes selected, the polar network can come in a variety of forms to arrive at an intermediate state between the virtual and real networks. What is interesting about this kind of

representation is that the graphics remain simple, supplemented with more or less extensive fi les of attributes. It facilitates the work of producing variations to help design infrastructure networks that will be better coordinated with virtual networks, and fi rst-level networks that are better coordinated with second and third-level networks (see illustration 2.4); or strike a balance between networks and areolar coverage areas.

Stathopoulos (1990) describes a full- scale study carried out to test this concept on the Paris area bus network. The representation here is confi ned to around twenty points, or poles, selected in the light of their importance to the urban fabric of the suburbs, to the bus network itself, or to its links with other such networks as the RER suburban rail service. Connecting arcs, incorporated in order to form paths, are given a frequency attribute represented visually by the thickness of the line, and diversifi ed by means of a fi le highlighting each line’s frequency during fi ve periods of the day: morning peak, morning off -peak, afternoon off -peak, evening peak, and evening off -peak (illustration 4.6).

Illustration 4.6 Representation of a public transport system based on the polar network concept.

Source: Stathopoulos (1990)

Urban Networks – Network Urbanism Urban Networks – Network Urbanism

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Illustration 4.7

Polar network representation in the PRAO model. Source: Michon (1989)

Chapter 4: Network visualization tools for urban planners

The polar network concept can also be used to produce a visual representation of cable, water, drainage, postal delivery or electric power supply networks, for instance. Let us take the case of the latter. The PRAO computer-aided network planning model of the French national electricity company, EDF, enables various network development strategies to be compared on the basis of the operator’s capital costs and the energy losses stemming from the fact that the network is relatively undersized (Michon, 1989) (see illustration 4.7). At each stage – at the end of one simulated year – the computer redesigns the network in the light of the new needs arising due to increased consumption, further urbanization, enterprise start-ups and so on. It also detects newly emerging constraints likely to hinder the network’s performance. A multicriteria optimization function is then applied to the network utilization plan in an attempt to remove the drawbacks without incurring additional capital costs. If that does not work, investments must be proposed. These are subjected to a series of iterations over a given time period geared to testing the various strategies and comparing the associated costs. Illustration 4.7 shows the original network with an initial representation of the demand forecast scenarios, followed by a comparison of two strategies after a period of three years.

The representation displayed in the two utilization plans, which corresponds perfectly to the polar network-type model devised by Amar and Stathopoulos (1987), is what serves to underpin strategic decision-making in the network study. It highlights the network supply stations together with the

connection points (residential areas, enterprise zones, and so on). These points and the arcs representing the electricity lines feature the kinds of attributes comparable to the ones that the computer uses to assist in the work of the network developer.

Progress in the fi eld of information technology has provided a fast and eff ective means of producing full- colour, 3D and dynamic representations that are so conducive to interactivity that on-screen displays are often the preferred option in place of printed maps and plans. Although the technology only does what it is asked to do, network designers now have access to a highly useful range of visualization tools; and planners will soon be able to use maps showing the territorial impacts of one or more networks,

e.g. train plus transport from stations: bus, metro, taxi and so on. But there is still the problem of network representations for the user, i.e. for ordinary citizens. Technology

can help. One such example is the in-car satellite navigation system allowing the driver to see a real- time visualization of the part of the road network he or she is using. Is this blend of interactivity and realism the right route to follow, or would it be better to stick with simple, sound tools – easy-to- read maps and plans – that clearly remain as popular as ever? Or else, instead of trying to produce new representations for network users, should they be left to build their own representations from the appropriate information? Such is the approach now made possible by the Internet or, at an even simpler level, mobile telephony. Regarding the latter, the part of the network that is useful to mobile phone users boils down to the personal directories containing all of the numbers they are in the habit of calling, i.e. the potential links they can activate whenever and wherever the need may arise. Above and beyond the mobile phone itself, is this not a highly promising avenue of research as far as network visualization is concerned?

Urban Networks – Network Urbanism

Part II

Network Territoriality: Golden Age and Crises in Cities Around the World

Intermezzo: cummings plans qualities

Shifting Sense