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int. j. geographical information science, 1998, vol. 12, no. 7, 651671

Review Article

GIS-based urban modelling: practices, problems, and prospects

DANIEL Z. SUI

Department of Geography,Texas A&M University,College Station, TX 77843-3147, USAe-mail: [email protected]

Abstract. This paper reviews the practices, problems, and prospects of GIS-based urban modelling. The author argues that current stand-alone and various

loose/tight coupling approaches for GIS-based urban modelling are essentiallytechnology-driven without adequate justication and verication for the urban

models being implemented. The absolute view of space and time embodied in thecurrent generation of GIS also imposes constraints on the type of new urbanmodels that can be developed. By reframing the future research agenda from ageographical information science (GISci) perspective, the author contends thatthe integration of urban modelling with GIS must proceed with the developmentof new models for the informational cities, the incorporation of multi-dimensionalconcepts of space and time in GIS, and the further extension of the feature-basedmodel to implement these new urban models and spatial-temporal conceptsaccording to the emerging interoperable paradigm. GISci-based urban modellingwill not only espouse new computational models and implementation strategiesthat are computing platform independent but also liberate us from the constraintsof existing urban models and the rigid spatial-temporal framework embedded inthe current generation of GIS, and enable us to think above and beyond thetechnical issues that have occupied us during the past ten years.

1. Introduction

For almost two decades in the 1960s and the 1970s, GIS and urban modelling

developed in parallel with few interactions. The integration of GIS with urban

modelling did not take place until the late 1980s, as a part of the GIS communityseorts to improve the analytical capabilities of GIS (Goodchild et al. 1992, Anselin

and Getis 1992, Fischer and Nijkamp 1992, Fotheringham and Rogerson 1994,

Fischer et al. 1996). Nowadays, GIS users and urban modellers have increasingly

recognized the mutual benets of such an integration from the preliminary successes

of the past ten years. Various urban modelling techniques have enabled GIS usersto go beyond the data inventory and management stage to conduct sophisticated

modelling and simulation. For urban modeling eorts, GIS has provided modelers

with new platforms for data management and visualization ( Nyerges 1995). Themassive diusion of GIS in society has the potential to make models more transparent

and to enable the communication of their operations and results to a large group of

users. The growing literature on the integration of GIS with urban modelling atteststhe recognition of such mutual benets (Brail 1990, Birkin et al. 1990, Batty 1992,

Brooks et al. 1993).

The objective of this paper is three-fold: (1) to review the current practices of

GIS-based urban modelling; (2) to identify the existing problems of current eorts

to link GIS with urban modelling; (3) to discuss a new research agenda from the

emerging geographical information science (GISci) perspective.

1365-8816/98 $12.00 1998 Taylor & Francis Ltd.


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This paper is organized into ve sections. After a brief background introduction

in section one, the current practices of GIS-based urban modeling are reviewed in

section two. Section 3 discusses the existing problems of coupling GIS with urbanmodelling. Future prospects of urban modelling from the perspective of geographical

information science are covered in 4, followed by concluding remarks in 5.

2. GIS-based urban modelling: current practices

By the early 1990s, it was (and perhaps still is) a general consensus within theGIS community that the lack of sophisticated analytical and modelling capabilities

was one of the major deciencies in the current generation of GIS technology

(Openshaw 1991). Several recent research initiatives in North America and Europe

focus on the improvement of spatial analytical and modelling capabilities of GIS

technology. The integration of GIS with urban modelling was part of these broad

research eorts to link spatial analysis and modelling with GIS. Although overlappingwith many other GIS modelling eorts in terms of the general methodology, GIS-

based urban modelling has a set of substantially dierent conceptual issues from

GIS-based environmental modelling (Goodchild et al. 1993, 1996). Current practices

of GIS-based urban modelling thus deserve a separate scrutiny.

Generally speaking, four dierent approaches have been widely used to integrate

GIS with urban modelling (gure 1). My discussions here are conned to method-ological issues only. Those interested in the details of specic models are referred to

Wegener (1994).

1. Embedding GIS-like functionalities into urban modelling packages. This

approach aims to embed GIS functionalities in urban modelling packages, and has

been adopted primarily by urban modellers and spatial statisticians who think ofGIS essentially as a mapping tool. Usually no commercially available GIS software

packages are involved, as illustrated by Putnam (1992) in the US, the Leeds group

in the UK (Clarke 1990, Birkin et al. 1996), and Hasletts SPIDER system (Haslett

1990), etc. This approach usually gives system developers maximum freedom for

system design. Implementation is not constrained by any existing GIS data structures,

and usually this approach is capable of incorporating the latest development inurban modelling. The downside of this approach is that the data management and

visualization capabilities of these urban modelling software packages are in no way

comparable to those available in commercial GIS and programming eorts also

tend to be intensive and sometimes redundant. Also, we should recognize that most

urban modelling software packages were developed by individual researchers gearedtoward specic projects. Although they possess certain conceptual commonalties,

these urban modelling packages use a great variety of data structures, programming

tools, and hardware platforms that make this approach extremely dicult forother users.

2. Embedding urban modelling into GIS by software vendors. Although still pre-

dominantly an academic pursuit, a few leading GIS software vendors in recent yearshave made extra eorts to improve the analytical and modelling capabilities of their

products. Pioneered by the urban data management system (UDMS) (Robinson and

Coiner 1986), several commercial software vendors have developed stand-alone GIS

software packages with functions that can be used for a variety of urban modeling

needs (Ferguson et al. 1992 ). Certain urban modelling functions have been embedded

in leading generic GIS software packages such as TransCAD, ArcViews SPATIAL/


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GIS-based urban modelling 653

Figure 1. Integrating GIS with urban modelling: current practices.

NETWORK Analysts, and SPANS etc. This approach builds on top of a commercial

GIS software package and takes full advantage of built-in GIS functionalities, but

the modeling capabilities are usually simplistic and calibrations must take place

outside of the package. Also because the market for modelling capabilities is still

much smaller than that for data management and mapping, most GIS softwarevendors have not been very enthusiastic in integrating sophisticated modeling capab-

ilities in the their software products.

3. L oose coupling. This approach usually involves a standard GIS package (e.g.Arc/Info) and an urban modelling program (e.g. TRANSPLAN or TRIPS) or a

statistical package (e.g. SAS or SPSS). Urban modelling and GIS are integrated, via

data exchange using either ASCIII or binary data format, among several dierentsoftware packages without a common user interface. The advantage of this approach

is that redundant programming can be avoided, but the data shuing and conversion

between dierent packages can be tedious and error prone (Sui and Lo 1992, Shaw

1993, Brooks et al. 1993; Geertman and van Eck 1995). Because computer program-

ming is minimal, this approach may be the most realistic method for most GIS users

to conduct modelling work.


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D. Z. Sui654

4. T ight coupling. This approach embeds certain urban models with a commercial

GIS software package via either GIS macro or conventional programming (Miller

1991, Batty and Xie 1994 a, 1994 b, Ding and Fotheringham 1992, Anselin et al.1993). With the recognition of the users need to develop customized applications,

more and more GIS software vendors are providing macro and script programming

capabilities so that users can lump a series of individual commands in a batch modeor develop a customized user interface for specic applications. Such languages are

seldom powerful enough to implement sophisticated models, however, an alternativemethod is to incorporate user-written routines into a GIS. Several software packages

have already developed mechanisms to allow user-developed modelling libraries or

routines to be called within the normal pull-down menu of a particular software

package. This approach, however, requires a well-dened interface to the data

structures held by the GIS. The challenge will be to develop new mechanisms for all

users to access spatial data without needing to know about the particular datastructures used in the GIS (Goodchild et al. 1992).

The rst two approaches lend the integration eort to software developers, users

have minimal involvement in the technical aspects of the integration whereas the

third and fourth approach put the technical task of integration squarely on the

shoulders of the users. Although GIS software vendors have increasingly recognized

the importance of analytical and modelling capabilities, most of the recent GIS-baseurban modelling eorts are made via the loose or tight coupling approach (Anselin

and Bao 1997).

Although conventional urban models, such as dierent versions of the Lowry-Garin models and monocentric population density models, still dominate current

practices, two other features of the recent GIS-based urban modelling eorts are

worth noting.

1. T he development and introduction of a series of new concepts and techniques in

urban modelling. These concepts and techniques include, but are not limited to,

cellular automata, fractals, neural networks, parallel processing, and genetic algo-

rithms (Batty and Xie 1994 c, Batty and Longley 1994, Gimblett et al. 1994, Kirtland

et al. 1994, Openshaw 1994, Clarke and Gaydos 1998). Such eorts mark a dramaticshift from conceiving cities based upon predominantly physical metaphors as

machines to conceptualizing cities using a biological metaphor as organisms. While

the traditional urban models based upon gravity or entropy maximization favours

a top-down approach emphasizing global patterns, the new urban models based up

cellular automata and fractals take a bottom-up approach stressing local rules andvariations. Although to what extent this shift represents progress in modelling urban

reality is still debatable, research interests in these biologically inspired models

continue to grow among urban modellers. This kind of biologically motivatedthinking is not just conned to urban modelling but is permeating the entire intellec-

tual terrain, and some even argue that this marks the rise of a new biological

civilization (Kelly 1994). Perhaps, what is more important is that the new modelshave not only been implemented using GIS, such as cellular automata in a raster-

based GIS (Itami 1994), but also have stimulated discussions of new concepts about

space and time which can be used to redesign GIS (Couclelis and Takeyama 1995).

2. T he rise of urban modelling applications in the private sector. In terms of

applications, we have witnessed a gradual decline and even a phasing out (such as

in the UK) of urban modelling applications in the public sector, and a rapid increase


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in the private sector applications relating to marketing and geodemographic analysis

(Longley and Clarke 1995, Birkin 1996, Birkin et al. 1996). Long term strategic

planning by government agencies has increasingly been replaced by short-termexpediencies dominated by data collection and information management eorts

(Batty 1989). This dramatic shift of urban modelling eorts from public to private

has profound social implications given the wide adoption and diusion of GIStechnology in society (Pickles 1995). Private sector modelling eorts tend to be more

prot-driven rather than motivated by grand socio-economic goals of eciencyand equity.

These eorts toward integrating GIS with urban modelling, coupled with emer-

ging computer networks such as the Internet for various social economic activities,

have fundamentally transformed our conceptions of cities and urban life (Sui 1997).

Almost everything in our cities is becoming digital or is digitally presentable, and

hence easier for all kinds of manipulation and simulation. Popular urban simulationgames such as SimCity are at the nger tips of ve-year olds. This phenomenon has

been referred to as `computable cities (Batty 1995). According to Batty (1995, 3),

`Within 50 years, everything around us will be some form of computer and the ways

we will access this and use it to interact with each other will be through software.

However, I think we should not uncritically accept the computability of cities. Many

assumptions behind current GIS-based urban modelling eorts should be criticallyscrutinized. Dazzling technical progress tends to blind us to more critical issues such

as what it is we are trying to model and why.

3. Computable cities and the computability of cities: existing problems

With cities becoming increasingly computable, the computability of cities has

been challenged by numerous social theorists (Lake 1993, Pickles 1995). Besidesphilosophical critiques at the ontological, epistemological, methodological, and eth-

ical levels (Sui 1994), I would like to discuss the following two substantive issues in

the current practices of GIS-based urban modelling.

3.1. Problems of the urban models.

Although conventional urban modelling coupled with GIS is still practiced world-wide ( Batty 1994, Wegener 1994), the fundamental assumptions in these models need

to be re-evaluated. With the massive transformation from an industrial to an informa-

tional society, the urban models integrated with GIS via various strategies outlined

above fail to adequately describe the new urban forms and processes in Western

society. These models were developed for the industrial cities with the goal ofcontrolling land use and containing the impacts of the automobile, and they are

inappropriate for modelling cities in the information age. For example, various

modied versions of the Lowry-Garin model for land use and transportation planningrepresent a fusion of gravitational concepts underpinning spatial interaction with

macro-economic theory as reected in input-output and economic base models.

These models are essentially spatial interaction models ( based upon Newtoniansocial physics) coupled with a crude economic base mechanism ( based upon

Keyenesian economics). Besides those vocal critics of urban modelling, such as

Douglas Lee (1973) and Andrew Sayer (1979), modelers themselves have begun to

admit that this type of model represents a rather narrow conception of cities (Batty

1989). Lowry-Garin models characterize cities as being comprised of distinct land

use types that can be articulated in measurable economic and demographic activities.


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The model was designed to locate such activities in spatial units usually represented

by zones at the census tract level. Spatial interaction and trip-making were embodied

in gravitational analogues while model structure was conceived along simple econo-metric lines. The assumptions of the economic base model as being unidirectional

in causation have been challenged by several researchers, and the division between

the basic versus the non-basic sector is arbitrary. With the transition to a post-industrial society, the growth of multinational corporations, and the sharp decline

of the manufacturing base (Castells 1989), the basic and non-basic split in the localeconomy is becoming more ambiguous, if not meaningless, and in some areas, we

have even witnessed the wholesale disappearance of the traditional basic sector for

some time. With this fundamentally dierent urban reality, urban models must be

reconceived in order to be useful in the planning and decision making process.

Several advances have been made in the formation of spatial interaction models,

such as Wilsons entropy maximization or McFaddens random utility maximization,and the introduction of numerous new mathematical techniques such as catastrophe

theory, chaos theory, and self-organizing concepts (Bertuglia et al. 1990, Nijkamp

and Reggiami 1992, Roy 1996). However, these techniques pertain mostly to model

estimation and specication. They tend to be technique-based rather than substance-

based, focusing more on the syntax than the semantics of urban modelling. Those

new urban modelling eorts based upon cellular automata and fractals, althoughconceptually interesting, are still at an experiential stage and to what extent those

eorts may contribute to our understanding of urban forms and urban processes

remains to be seen. Eorts are also being made to model urban development usingderived land use units instead of the xed census tract boundaries (Landis 1995),

but these models still inherit the conceptual foundations that have long been aban-

doned by urban planners and policy makers. In sum, it is quite obvious that wecannot aord to remain oblivious to the conceptual deciencies of these urban

models even though they have been successfully integrated with GIS and may be

still applicable in some developing countries. There is a crying need for models that

can capture the new urban reality of the information age.

3.2. Problems of GISWith its historical roots in computer cartography and digital image processing,

the development of GIS to date has relied upon a limited map metaphor (Harris

and Batty 1993, Burrough and Frank 1995). Consequently, the representation

schemes and analytical functionalities in GIS are geared toward map layers and

geometric transformations. The layer approach implicitly forces a segmentation ofgeographical features (Peuquet 1988, Raper and Livingstone 1995). This representa-

tion scheme is not only temporally xed but is also incapable of handling overlapping

features (Gazelton et al. 1992). Perhaps more importantly, as so many GIS theoristshave pointed out, underneath this crude map metaphor in the current generation of

GIS is an implicit conceptualization of absolute space based upon Newtonian mech-

anics (Couclelis 1991, Gatrell 1991). The absolute conceptualization of space hasforced space into a geometrically indexed representation scheme via planar enforce-

ment. In contrast, embedded in various urban models is essentially a relative/

relational conceptualization of space, as manifested in various kinds of spatial struc-

ture, spatial dynamics, and spatial organization models. This relative view of space

is not compatible with the notion of space built into commercially available GIS,

either as an inert assembly of polygons or as a lattice of raster cells. Although


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technically we can plug in various urban models into GIS through the strategies

outlined in the previous section, GIS and urban models are not really integrated

because of the dierent spatial data representation schemes involved (Abel et al.1994). Therefore, in order to accomplish the seamless integration of GIS and urban

models, we need to conduct research at a higher level, that is to develop and

incorporate novel approaches to conceptualizing space and time.Obviously, the current practices of integrating GIS and urban modelling are

essentially technical in nature and have not touched upon the more fundamentalissues in either urban models or GIS. We have succeeded only in putting old wines

in new bottlesan improved means for unimproved ends. Simply being able to run

a Lowry type model in Arc/Info improves neither the theoretical foundation nor the

performance of the model. GIS-based urban modeling, like GIS-based environmental

modeling (Raper and Livingstone 1995), has resulted in a tremendous amount of

representational compromise. Such problems call for a fresh look at the integrationof GIS with urban modelling. We must think above and beyond the technical domain

on this issue. Instead of being dictated by GIS technology, the emerging geographical

information science (GISci) itself should drive the next round of urban modelling

eorts.

4. GISci-based urban modelling: future prospects

Problems in the current practices of GIS-based urban modelling can not be

resolved if we continue to treat the integration of GIS with urban modelling as

essentially a technical issue. Instead, we must challenge the implicit assumptionsbehind urban models and GIS, and shift our research eorts to more fundamental

issues in conceiving and representing the urban reality in the appropriate spatial-

temporal framework during the information age. We need to switch our researcheorts to a broader conceptual basis and frame our future research agenda from a

geographical information science perspective in order to avoid being trapped in the

narrowly dened technical issues researchers have pursued so far. To set up the

context for GISci-based urban modelling, it would be instructive to take a quick

look at the core elements of GISci.

4.1. Elements of geographical information science (GISci)

Since Goodchild (1992) rst raised the banner of a new discipline called geo-

graphic information science, the GIS community has increasingly recognized the

importance of transcending the limits of GIS technology to focus on the more generic

issues in spatial data handling. During the past ve years, the GIS community hasresponded enthusiastically to Goodchilds call, as evidenced by the establishment of

the new university consortium of geographical information science in the US, the

development of the new on-line GISci. curriculum, and the publication of severalnew journals in GISci. Although still in its infancy, and the disciplinary status may

be debatable, the three core elements of a geographical information science as

articulated in a recent NCGIA proposal are crucial for a research agenda on GISci-based urban modelling (NCGIA 1996 a). These three core elements in GISci. are:

1. Cognitive models of geographical space. NCGIA contends that our under-

standing of key geographical concepts and their appropriate representations

is currently incomplete. The rst area GISci should investigate is how key

geographical concepts such as space and time have been conceptualized by


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Figure 2. GISci-based urban modelling: major tasks.

dierent people and dierent disciplines. As ease of use is increasingly import-

ant in the information age, studies on fundamental geographical conceptswill be critical for us to better understand the geographical world around us.

2. Computational implementations of geographical concepts. This area concen-

trates on building new computational models of geographical spaces and thesocial and environmental processes that operate in them. Exploring the best

computational strategy for the implementation of various conceptualizations

of space will promote interoperability among dierent computational models.3. Geographies of the information society. This element focuses on the positive

and negative impacts of technology on individuals, organizations, and society.

GISci examines what kinds of new spatial relationships are emerging in the

new information society and what the societal impacts are by introducing

GIS into various facets of our social practices. These three core areas in

GISci provide us a broad guideline for the future research of GISci-basedurban modelling. I believe that the success of GISci-based urban modelling

will depend upon how successfully we have developed new urban models,

new conceptualizations of space and time, and their ecient/interoperable

implementations on various new computing platforms (gure 2).

4.2. T he development of new urban models

This is closely related to the topic of geographies of the information society in

GISci. Since the urban models developed so far no longer adequately describe theurban reality in the information age, we need to develop new models that capture

the form, process, and policy aspects of this new reality. It is generally conceded

among social scientists that a technological revolution of historic proportions isdramatically transforming the fundamental dimensions of urban society (Graham

and Marvin 1996, Couclelis 1996). The voluminous recent urban literature on world

cities, especially North American cities, is replete with assertions that a major

reorganization of the spatial structure of cities is underway. A series of distinctive

new urban forms is emerging from a complex interplay among social, economic,

political, and cultural forces (Bourne 1991). It has been argued that these new forms


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Figure 3. Elements of an integrated model for informational cities.

are characterized by the continued decentralization of both population and employ-

ment, the increasing levels of social diversity and spatial polarization, the emergenceof an elite gentried inner city, and the deepening spatial mismatch between jobs

and labour. These new urban forms have been attributed to societal, institutional,

and individual decision making processes. Numerous policy proposals have beenmade for various development scenarios for cities in the twenty-rst century, ranging

from going back to a more compact pedestrian-based urban form, to stimulating the

development of a completely footloose electropolis.In order to weave all these dierent aspects of urban studies into a coherent

research agenda, we need to develop and articulate a new, eclectic, and inclusive

conceptual framework. I believe that the new theoretical framework should have

three integral components (Sui 1996). First, it should enable us to describe the new

emerging urban forms in more comprehensive ways. Second, it should empower us

to explain the underlying processescontributing to the emerging new urban forms.Third, it should oer us new insights to prescribe eective urban policiesto redirect

the underlying processes to promote the most desirable urban forms. It is beyond

the scope of this paper to present detailed discussions on this synthetic framework.

Instead, the following is a broad-brush outline of the crucial elements of this urban

research framework (gure 3).

4.2.1. Urban forms

A metropolis in the twenty-rst century will be a tale of three dierent, butinterrelated, cities. The specic urban forms will be determined by the interplay of

the following three components:

E T echnopolis. Scholars have used a variety of dierent names to refer to this

emerging technopolis, ranging from electropolis and wired cities to city of

bits, computational city, and virtual community. Technopolis, narrowly

dened, refers to the constellation of massive transportation, telecommunica-

tions, and information networks to move goods, people, and information; it

is a combination of wheels, wires, and air waves. Technopolis, especially the


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D. Z. Sui660

city of bits, or the on-line virtual community, has attracted considerable

attention in recent years, but our knowledge of the wired cities remains

nothing more than futuristic prophecies, as presented in Mitchells City ofBits (Mitchell 1995). Concerted research eorts are needed for understanding

this emerging new urban form. Because of the partial invisibility of the

technopolis (such as the information ow through the telecommunicationnetwork), modelling and understanding it poses a new challenge for urban

scholars.E Ecumonopolis. Ecumonopolis is also known as the sustainable city or the

ecological city. Daunting urban environmental problems have caused planners

to rethink the development policies of the past. The development of ecumeno-

polis, with its goal of seeking harmony between human beings and their

surrounding environment, has increasingly become an integral part of urban

development policy all over the world. The technopolis should be developedin harmony with the environment and ultimately to become an ecumenopolis.

E Anthropopolis. The central component of the metropolis of the future will be

the residents in the cities. To make future cities become anthropopolis is to

make future metropolis become truly the city of/for the people. The concept

of anthropopolis emphasizes the satisfaction of human needs and the quality

of urban life as the ultimate goal for all future endeavors. We should striveto make technopolis and ecumenopolis serve this goal. Transportation net-

works, communication networks, and urban environments should be designed

so as to stimulate the kind of life we would like to live. The goal of developingan anthropopolis is to make all human activities (i.e., where we work, where

we live and shop, and where we go to entertain ourselves) as enjoyable as

possible. Telecommunications and computer technologies have played increas-ingly important roles in these activities, and yet we are not sure to what

extent they are substitutive, complementary, or synergistic to traditional

means of conducting them.

With these three interrelated metropolis in mind, we should make concerted

research eorts to understand the optimal urban forms for the cities in the nextmillennium. Do we want the relentless urban sprawl to continue, as facilitated by

the development of new transportation, communication, and information technolo-

gies? Or should we go back to more compact pedestrian-oriented urban forms as

proposed by some leading urban planners in order to better fulll the ideal sense of

community, sustainability, and social equity? Our understanding of the new urbanforms will denitely help us to answer these questions.

4.2.2. Urban processesThe processes contributing to the formation of urban forms are extraordinarily

complex, and numerous theoretical perspectives have been developed during the past

two decades to explain them. I believe that future urban theory should take a moreholistic approach. The hierarchical theory I am proposing can be broken down into

the following three levels:

E Micro-level processes. This is the individual level process using a behavioral

approach from theories and concepts of neo-classical economics and

behavioral geography (Golledge and Stimson 1997).


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E Meso-level processes. At this intermediate level, attention should be paid to

the roles and behaviors of private and public institutions. We need to examine

how such institutions shape urban development trajectory and thus result indierent urban forms.

E Macro-level processes. At this level, we should bring the general societal trends

into consideration, putting urban development into perspectives of politicaleconomy, economic transformation, long wave rhythms, and world systems.

4.2.3. Urban policies

I believe future policy goals should strive to achieve balance among the following

objectives:

E Economic eciency. To develop policies to intervene at the individual, institu-tional, and societal levels to optimize economic eciency in technopolis at

both the intra and inter-urban levels to facilitate the ows of goods, people,

and information.E Social equity. To design policies to intervene at the individual, institutional,

and societal levels to make the anthropopolis truly socially equitable so that

the metropolis will become a city for everybody, with equal access to alldierent kinds of information and services and equal shares of environmental

burdens.

E

Environmental sustainability. To initiate policies to intervene at the individual,institutional, and societal levels to make the ecumenopolis environmentally

sustainable, with plenty of safe water, clean air, and diversied urban nat-

ural habitat.

Indeed the information city poses new challenges for us and entails additional

spatial and temporal dimensions of social and economic activities. New urban

realities demand new urban models. These models should incorporate processes at

the individual, institutional, and societal levels to achieve the goals of economiceciency, environmental sustainability, and social equity for the metropolis of the

twenty-rst century in which the technopolis, ecumonopolis, and anthropopolis are

synergistically and artfully integrated. This new type of city demands that we must

develop alternative spatial-temporal representation frameworks in the digital envir-

onment in order to model the urban reality realistically.

4.3. Alternative conceptualizations of space and time

The telemediated cities not only assume new urban forms, undergo fundamentallydierent urban processes, and demand new urban policies, but also stimulate dra-

matic changes in the spatial/temporal rhythms of society (Graham and Marvin 1996,

Castells 1997) . The rigid spatial-temporal framework embedded in the current genera-tion of GIS is too restrictive to capture the current urban reality. The next generation

of GIS must incorporate multiple dimensions of space and time in order to become

a exible platform to implement various new urban models simulating the informa-

tion cities. The alternative conceptualization of space and time that is more compat-

ible with the new spatial-temporal rhythms will be one of the most important

cornerstones for the implementation of the next generation of GIS.


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D. Z. Sui662

4.3.1. Alternative conceptualizations of space

Philosophers from Aristotle to Kant have developed drastically dierent views

of space, with varying degrees of objectivity and subjectivity and dierent concep-tualizations regarding the relationship between space and substance (Sack 1980,

Couclelis 1993, Curry 1996). Based upon Penroses concepts of three worlds (Penrose

1994), I would like to group the dierent conceptualizations of spaces into threemajor groups for the clarity of discussion (gure 4):

E Formal/mathematical spaces. This is the space in the Platonic world of forms,

usually based upon mathematical axioms. Among the three major type of

spaces, the formal/mathematical space is perhaps logically the most consistent

and conceptually the most elegant. Although philosophers and scientists alike

still have a hard time explaining the ontological status of these abstract

representations, various formal/mathematical spaces have framed our waysof viewing the world since the dawn of civilization. From Euclidean geometry

to N-dimensional algebraic spaces, from Hamiltons state/phase space to

geometrical behaviour of vectors in Hilbert space, from cellular automata to

fractal geometry, each of these inventions or discoveries of new mathematical

spaces have drastically reshaped our perspectives toward the physical and

social-economic processes in the empirical world.E Physical/Socio-Economic Spaces. This is the space created by various discip-

lines in both physical and social sciences. Although closely tied to formal/

mathematical spaces, dierent kinds of physical/socio-economic spaces havedierent manifestations. The major dividing line is the absolute versus. the

relative conceptualization of space. The Newtonian (absolute) view treats

Figure 4. Three Worlds and Three Dierent Kinds of Spaces (Modied after Penrose [1994]).


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space as an empty container, independent of the objects within. Whereas the

Leibnizian (relative) view of space contends that space and substances are

inseparable, and space is primarily dened by the interrelationships amongthe objects. Einsteins theory of relativity injected not only the Leibnizian

view of space but also a novel conception of time or space-time into the

twentieth century consciousness. The shift from the Newtonian absolute viewof space and time to Einsteins relative view of space-time has exerted far-

reaching inuence in our eorts to understand socio-economic processes insociety. Thrift and Olds (1996) nicely summarized how the shift to dierent

conceptualizations of space may assist us in reconguring our views of the

fundamental changes of economic processes in information society. The four

topological propositions they discussed in terms of bounded regions, networks,

ows, and non-locality will have profound implications on how we actually

conceptualize the emerging new socio-economic process (Thrift and Olds1996).

E Subjective/Experiential spaces. This is the space in the human mind. How

space is manifested in the human mind has always been a major scholarly

interest. Some philosophers, such as Kant, even speculated that space is a

synthetic a priorian innate precondition of human intellect that makes our

understanding the world possible. According to many Kantian and neo-Kantian scholars, space is not another thing in the world, but a framework

created in our mind by the interaction of human reason with the world.

Human perceptions of space can be very dierent from the mathematicalspaces or physical spaces. Studies in cognitive science, behavioural geography,

and recent research eorts on the so-called naive geography exploring the

common sense model of the real world have revealed new dimensions of spacein the human mind (Parks and Thrift 1980, Frank et al. 1992, Egenhofer and

Mark 1995, Mark and Egenhofer 1996) . In the meantime, critical social

theorists have been arguing that space is produced entirely by various social

processesthe social production of space (Lefebvre 1991).

All these alternative conceptions of space have developed dierent vocabulariesto describe the world (table 1). Can these alternative views about space be imple-

mented in a digital environment?

4.3.2. Alternative conceptualizations of time

The representation of time in GIS is almost non-existent in the current generationof GIS. Although many researchers have devoted their eorts toward incorporating

the temporal element in GIS (Langran 1992, Peuquet 1994, Al-Taha et al. 1994),

Table 1. Three spaces and their sample terminologies (Modied after Couclelis (1992)) .

Formal/Mathematical Physical/Socio-Economic Subjective/Experiential

Point ( 0-D) Location/Origin Place/LandmarkLine (1-D) Network/Route Way/PathArea ( 2-D) Region Territory/NeighborhoodSurface ( 3-D) Plain Environment/DomainConguration Distribution/Flows World/Spatial Layout


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D. Z. Sui664

alternative ways of conceptualizing time should also be explored (Worboys 1995).

Similar to space, time can also be conceptualized by dramatically dierent structures

(gure 5) . For example, time can be either conceptualizedas a discrete or a continuous

variable (gure 5 (a)); time may be linearly or partially ordered or may form a

temporal cycle exhibiting periodicities (gure 5 (b)); or time may be associated with

time points, intervals (durations) or disjoint unions of time intervals (gure 5 (c)).Stephen Hawking (1996) eloquently presented three views of linear time models,

from the cosmological arrow (the direction in which the universe increases in size)

to the thermodynamic arrow (the direction in which disorder increases) to the

psychological arrow(the direction in which we perceive time pass). In a sense, these

three temporal models parallel the three major types of spaces. Besides these linear

time models, we should also explore the implications of various non-linear cyclic

models that may be more appropriate for many phenomena we are trying to model.

These alternative views of space and time will broaden the theoretical foundations

of GIS technology. So far GIS is based upon a Newtonian absolute representation

of space coupled with the crude conception of linear time slicing. GISci-based urban

modeling should explore the new dimensions of space and time, and take a holistic

approach about the multidimensionality of space and time in order to more realistic-

ally capture the new urban dynamics during the information age. Modeling the new

urban realities demands that we shift our conceptions of space and time to

new dimensions such as the Leibnizian and Kantian view of space and a non-linear

conception of time. Perhaps, what is more challenging is how to operationalize the

concept of space-time instead of the Cartesian/Newtonian concept of space and time.These alternative representation schemes for space, time, and space-time will not

only lay a new conceptual foundation for GIS technology, but also turn out to be

more eective in many specic applications, such as applications of various subject-

ive/experiential conceptualizationsof space in car navigation systems and navigation

aids for the visually impaired, etc. Several new research initiatives are already moving

towards these new directions, such as NCGIAs initiative 19 on GIS and Society;

initiative 21 on Nave, etc. Geography (Frank et al. 1992, NCGIA 1996 b, Raper

in press).

Figure 5. Alternative conceptualizations of temporal structure (After Worboys [1995]).


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Figure 6. Dimensions of a feature-based urban GIS (modied after Usery ( 1996)) .

4.4. Computational implementation strategies

To implement these new urban models and spatial-temporal concepts, we need

to develop new computational models and implementation strategies. It should berecognized, however, that not all of the new urban models and alternative concep-

tualizations of space and time can be implemented using the Turing computer as we

know it today. Although the development of quantum computers may blaze a newholy grail in computation ( Deutsch 1997), our understanding of the new urban

reality will be ultimately based upon a combination of computers and human

judgment. But for those urban models and alternative spatial-temporal concepts thatcan be computerized, we should strive to develop the best computational model for

their implementations. In the near future, I believe that the implementation of new

urban models will hinge on two core conceptsthe feature-based GIS and the

interoperable GIS. To transcend the static, two- dimensional map metaphor, as being

currently implemented in GIS, Lynn Userys feature-based GIS (FBGIS) model

seems to be a promising strategy to implement new urban models and the multi-


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D. Z. Sui666

dimensions of space-time (Usery 1996). Unlike the layer-based GIS in which we try

to t a map layer containing geographical entities into a Cartesian coordinate system

(an absolute conceptualization of space and time), the FBGIS lends us a newconceptual framework to implement those alternative views of space and time and

various new models depicting the physical and socio-economic processes in the real

world (Tang et al. 1996). In a feature-based GIS, space, time and themes are denedas integral parts of a geographical feature instead of referencing all the entities into

an arbitrary Cartesian grid. By providing direct access to spatial, temporal andthematic attributes, the FBGIS is not constrained to map and layered representations

of geography and thus supports multiple dimensions of spatial/temporal events.

However, there is a crucial element missing from the current version of Userys

FBGISthe denition of operations on a feature. The FBGIS model should be

further expanded to incorporate the dual aspects of the object-oriented paradigm

the simultaneous denition of state and functionality for an object ( Worboys 1994).The denition of operations on a feature should be included as an integral part of

a feature. As some preliminary results have indicated (Ralston 1993, Raper and

Livingston 1995), the inclusion of operations in the feature denition, together with

its capabilities of encapsulation, inheritance/composition, overloading, and poly-

morphism, can greatly facilitate the implementation of various spatial analysis and

modelling techniques.The other very important computing trend is to cultivate the interoperability of

software products across distributed computing platforms (DCPs) according to the

concept of the Open Geo-data Interoperability Specication (OGIS) (McKee 1996).The concept of OGIS and interoperablity has already stimulated new software

development trends in the industry, and is also gaining attention among academic

researchers (Egenhofer and Goodchild 1997, Evans 1997). Instead of developing afully integrated GIS, software vendors and researchers are exploring new ways of

developing a much leaner core module with numerous more task specic, embeddable

modules. These object-oriented, embeddable modules can not only be easily integ-

rated into a core GIS package but also be seamlessly integrated with other application

programs. In addition, with explosive growth of both the Internet and the Intranet,

the development of web-based software tools is necessary so that whoever has accessto the Internet can run the program regardless of the location of the user. ESRIs

MapObjects and the new map server on the Internet are an important step toward

full interoperability. As evidenced by Lin and Zhang (1998), new platform-

independent software development tools such as Java denitely provide us the

potential to develop GIS-based urban modelling and simulation tools as easilyaccessible and user friendly as SimCity (Macmillan 1996).

5. Concluding remarks: beyond models, beyond technologies

This paper has reviewed the practices, the problems, and the prospects of GIS-

based urban modelling. Although we have seen some technical progress during the

past ten years, the integration of GIS with urban modeling is essentially technology-driven without adequate justication for the validity of the models and the suitability

of the spatial-temporal framework embedded in the current generation of GIS. By

reframing the future research agenda from a geographical information science per-

spective, the author contends that the integration of urban modelling with GIS must

proceed with the development of new models for the informational cities, the incorp-

oration of multi-dimensional concepts of space and time in GIS, and the expansion


17/21


of a feature-based strategy for the implementation of these new urban models and

spatial-temporal concepts using object-oriented and web-based programming tools.

GISci-based urban modelling will not only equip us with new computational modelsand implementation strategies that are interoperable and embeddable across comput-

ing platforms, but also liberate us from the constraints of existing urban models and

the rigid spatial-temporal framework embedded in the current generation of GIS.This paradigm shift in urban modelling will enable us to think above and beyond

the technical issues that have occupied us during the past ten years.Last, but not least, I would like to emphasize that our future research eorts

need to be tied more closely to urban policies. There have been growing disparities

between what we purport to describe and manipulate using sophisticated theoretical

frameworks and technical tools in virtual reality and our ability to say anything

meaningful about what actually happens in urban reality. Just as Gunnar Olsson

(1974) put it so aptly 20 years ago: `what the analysis yielded was not more knowledgeof the phenomena the model was speaking about: what it revealed was instead the

hidden structure the model was speaking within(p. 61). The new research agenda

must strike a balance between the sophistication of our techniques/methods and the

real world phenomena we are talking about. We need new frameworks, new models,

and new concepts, but we must strive to translate these new structures and models

into meaningful policies and languages that society can appreciate and understandand thus help us to build a more human urban society. Rigorous conceptual frame-

works should be coupled with meticulous empirical analysis and realistic policy

implications using state-of-the-art techniques. Otherwise, our research eorts maybecome another self-indulging academic exercise.

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