int. j. geographical information science, 1998, vol. 12, no. 7, 651± 671

Review Article

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

DANIEL Z. SUIDepartment of Geography,Texas A&M University,College Station, TX 77843-3147, USAe-mail: D-Sui@tamu.edu

Abstract. This paper reviews the practices, problems, and prospects of GIS-based urban modelling. The author argues that current stand-alone and variousloose/tight coupling approaches for GIS-based urban modelling are essentiallytechnology-driven without adequate justi® cation and veri® cation for the urbanmodels 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 modellingdeveloped in parallel with few interactions. The integration of GIS with urbanmodelling did not take place until the late 1980s, as a part of the GIS community’se� orts to improve the analytical capabilities of GIS (Goodchild et al. 1992, Anselinand Getis 1992, Fischer and Nijkamp 1992, Fotheringham and Rogerson 1994,Fischer et al. 1996). Nowadays, GIS users and urban modellers have increasinglyrecognized the mutual bene® ts of such an integration from the preliminary successesof the past ten years. Various urban modelling techniques have enabled GIS usersto go beyond the data inventory and management stage to conduct sophisticatedmodelling and simulation. For urban modeling e� orts, GIS has provided modelerswith new platforms for data management and visualization (Nyerges 1995). Themassive di� usion of GIS in society has the potential to make models more transparentand to enable the communication of their operations and results to a large group ofusers. The growing literature on the integration of GIS with urban modelling atteststhe recognition of such mutual bene® ts (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 ofGIS-based urban modelling; (2) to identify the existing problems of current e� ortsto link GIS with urban modelling; (3) to discuss a new research agenda from theemerging geographical information science (GISci ) perspective.

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

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This paper is organized into ® ve sections. After a brief background introductionin section one, the current practices of GIS-based urban modeling are reviewed insection two. Section 3 discusses the existing problems of coupling GIS with urbanmodelling. Future prospects of urban modelling from the perspective of geographicalinformation 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 capabilitieswas one of the major de® ciencies in the current generation of GIS technology(Openshaw 1991). Several recent research initiatives in North America and Europefocus on the improvement of spatial analytical and modelling capabilities of GIStechnology. The integration of GIS with urban modelling was part of these broadresearch e� orts to link spatial analysis and modelling with GIS. Although overlappingwith many other GIS modelling e� orts in terms of the general methodology, GIS-based urban modelling has a set of substantially di� erent conceptual issues fromGIS-based environmental modelling (Goodchild et al. 1993, 1996). Current practicesof GIS-based urban modelling thus deserve a separate scrutiny.

Generally speaking, four di� erent approaches have been widely used to integrateGIS with urban modelling ( ® gure 1). My discussions here are con® ned to method-ological issues only. Those interested in the details of speci® c models are referred toWegener (1994).

1. Embedding GIS-like functionalitie s into urban modelling packages . Thisapproach aims to embed GIS functionalities in urban modelling packages, and hasbeen adopted primarily by urban modellers and spatial statisticians who think ofGIS essentially as a mapping tool. Usually no commercially available GIS softwarepackages are involved, as illustrated by Putnam (1992) in the US, the Leeds groupin the UK (Clarke 1990, Birkin et al. 1996), and Haslett’s SPIDER system (Haslett1990), etc. This approach usually gives system developers maximum freedom forsystem 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 andvisualization capabilities of these urban modelling software packages are in no waycomparable to those available in commercial GIS and programming e� orts alsotend to be intensive and sometimes redundant. Also, we should recognize that mosturban modelling software packages were developed by individual researchers gearedtoward speci® c projects. Although they possess certain conceptual commonalties,these urban modelling packages use a great variety of data structures, programmingtools, and hardware platforms that make this approach extremely di� cult 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 e� orts to improve the analytical and modelling capabilities of theirproducts. Pioneered by the urban data management system (UDMS) (Robinson andCoiner 1986), several commercial software vendors have developed stand-alone GISsoftware packages with functions that can be used for a variety of urban modelingneeds (Ferguson et al. 1992 ). Certain urban modelling functions have been embeddedin leading generic GIS software packages such as TransCAD, ArcView’s SPATIAL/

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

NETWORK Analysts, and SPANS etc. This approach builds on top of a commercialGIS software package and takes full advantage of built-in GIS functionalities, butthe modeling capabilities are usually simplistic and calibrations must take placeoutside of the package. Also because the market for modelling capabilities is stillmuch 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 astatistical package (e.g. SAS or SPSS). Urban modelling and GIS are integrated, viadata exchange using either ASCIII or binary data format, among several di� erentsoftware packages without a common user interface. The advantage of this approachis that redundant programming can be avoided, but the data shuƒ ing and conversionbetween di� erent packages can be tedious and error prone (Sui and Lo 1992, Shaw1993, 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 usersto conduct modelling work.

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4. T ight coupling . This approach embeds certain urban models with a commercialGIS software package via either GIS macro or conventional programming (Miller1991, 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 programmingcapabilities so that users can lump a series of individual commands in a batch modeor develop a customized user interface for speci® c applications. Such languages areseldom powerful enough to implement sophisticated models, however, an alternativemethod is to incorporate user-written routines into a GIS. Several software packageshave already developed mechanisms to allow user-developed modelling libraries orroutines to be called within the normal pull-down menu of a particular softwarepackage. This approach, however, requires a well-de® ned interface to the datastructures held by the GIS. The challenge will be to develop new mechanisms for allusers 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 e� ort to software developers, usershave minimal involvement in the technical aspects of the integration whereas thethird and fourth approach put the technical task of integration squarely on theshoulders of the users. Although GIS software vendors have increasingly recognizedthe importance of analytical and modelling capabilities, most of the recent GIS-baseurban modelling e� orts are made via the loose or tight coupling approach (Anselinand Bao 1997 ).

Although conventional urban models, such as di� erent versions of the Lowry-Garin models and monocentric population density models, still dominate currentpractices, two other features of the recent GIS-based urban modelling e� orts areworth noting.

1. T he development and introduction of a series of new concepts and techniques inurban 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, Kirtlandet al. 1994, Openshaw 1994, Clarke and Gaydos 1998). Such e� orts mark a dramaticshift from conceiving cities based upon predominantly physical metaphors asmachines to conceptualizing cities using a biological metaphor as organisms. Whilethe traditional urban models based upon gravity or entropy maximization favoursa top-down approach emphasizing global patterns, the new urban models based upcellular automata and fractals take a bottom-up approach stressing local rules andvariations. Although to what extent this shift represents progress in modelling urbanreality is still debatable, research interests in these biologically inspired modelscontinue to grow among urban modellers. This kind of biologically motivatedthinking is not just con® ned to urban modelling but is permeating the entire intellec-tual terrain, and some even argue that this marks the rise of a new biologicalcivilization (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 aboutspace 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 ofapplications, we have witnessed a gradual decline and even a phasing out (such asin 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 strategicplanning by government agencies has increasingly been replaced by short-termexpediencies dominated by data collection and information management e� orts(Batty 1989). This dramatic shift of urban modelling e� orts from public to privatehas profound social implications given the wide adoption and di� usion of GIStechnology in society (Pickles 1995). Private sector modelling e� orts tend to be morepro® t-driven rather than motivated by grand socio-economic goals of e� ciencyand equity.

These e� orts 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, andhence 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 hasbeen 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 wayswe 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. Manyassumptions behind current GIS-based urban modelling e� orts should be criticallyscrutinized. Dazzling technical progress tends to blind us to more critical issues suchas 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 hasbeen 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 inthe 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 needto be re-evaluated. With the massive transformation from an industrial to an informa-tional society, the urban models integrated with GIS via various strategies outlinedabove fail to adequately describe the new urban forms and processes in Westernsociety. These models were developed for the industrial cities with the goal ofcontrolling land use and containing the impacts of the automobile, and they areinappropriate for modelling cities in the information age. For example, variousmodi® ed versions of the Lowry-Garin model for land use and transportation planningrepresent a fusion of gravitational concepts underpinning spatial interaction withmacro-economic theory as re¯ ected 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 uponKeyenesian economics) . Besides those vocal critics of urban modelling, such asDouglas Lee (1973) and Andrew Sayer (1979 ), modelers themselves have begun toadmit that this type of model represents a rather narrow conception of cities (Batty1989). Lowry-Garin models characterize cities as being comprised of distinct landuse 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 representedby zones at the census tract level. Spatial interaction and trip-making were embodiedin gravitational analogues while model structure was conceived along simple econo-metric lines. The assumptions of the economic base model as being unidirectionalin causation have been challenged by several researchers, and the division betweenthe basic versus the non-basic sector is arbitrary. With the transition to a post-industrial society, the growth of multinational corporations, and the sharp declineof 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, wehave even witnessed the wholesale disappearance of the traditional basic sector forsome time. With this fundamentally di� erent urban reality, urban models must bereconceived 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 Wilson’s entropy maximization or McFadden’s random utility maximization,and the introduction of numerous new mathematical techniques such as catastrophetheory, chaos theory, and self-organizing concepts (Bertuglia et al. 1990, Nijkampand Reggiami 1992, Roy 1996). However, these techniques pertain mostly to modelestimation and speci® cation. They tend to be technique-based rather than substance-based, focusing more on the syntax than the semantics of urban modelling. Thosenew urban modelling e� orts based upon cellular automata and fractals, althoughconceptually interesting, are still at an experiential stage and to what extent thosee� orts may contribute to our understanding of urban forms and urban processesremains to be seen. E� orts 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 a� ord to remain oblivious to the conceptual de® ciencies of these urbanmodels even though they have been successfully integrated with GIS and may bestill applicable in some developing countries. There is a crying need for models thatcan 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 (Harrisand Batty 1993, Burrough and Frank 1995). Consequently, the representationschemes and analytical functionalities in GIS are geared toward map layers andgeometric 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 overlappingfeatures (Gazelton et al. 1992). Perhaps more importantly, as so many GIS theoristshave pointed out, underneath this crude map metaphor in the current generation ofGIS 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 spaceis 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 strategiesoutlined in the previous section, GIS and urban models are not really integratedbecause of the di� erent spatial data representation schemes involved (Abel et al.1994). Therefore, in order to accomplish the seamless integration of GIS and urbanmodels, we need to conduct research at a higher level, that is to develop andincorporate novel approaches to conceptualizing space and time.

Obviously, the current practices of integrating GIS and urban modelling areessentially technical in nature and have not touched upon the more fundamentalissues in either urban models or GIS. We have succeeded only in putting old winesin new bottles Ð an improved means for unimproved ends. Simply being able to runa Lowry type model in Arc/Info improves neither the theoretical foundation nor theperformance of the model. GIS-based urban modeling, like GIS-based environmentalmodeling (Raper and Livingstone 1995), has resulted in a tremendous amount ofrepresentational compromise. Such problems call for a fresh look at the integrationof GIS with urban modelling. We must think above and beyond the technical domainon this issue. Instead of being dictated by GIS technology, the emerging geographicalinformation science (GISci ) itself should drive the next round of urban modellinge� orts.

4. GISci-based urban modelling: future prospects

Problems in the current practices of GIS-based urban modelling can not beresolved if we continue to treat the integration of GIS with urban modelling asessentially a technical issue. Instead, we must challenge the implicit assumptionsbehind urban models and GIS, and shift our research e� orts to more fundamentalissues in conceiving and representing the urban reality in the appropriate spatial-temporal framework during the information age. We need to switch our researche� orts to a broader conceptual basis and frame our future research agenda from ageographical information science perspective in order to avoid being trapped in thenarrowly de® ned technical issues researchers have pursued so far. To set up thecontext for GISci-based urban modelling, it would be instructive to take a quicklook 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 theimportance of transcending the limits of GIS technology to focus on the more genericissues in spatial data handling. During the past ® ve years, the GIS community hasresponded enthusiastically to Goodchild’s call, as evidenced by the establishment ofthe new university consortium of geographical information science in the US, thedevelopment of the new on-line GISci. curriculum, and the publication of severalnew journals in GISci. Although still in its infancy, and the disciplinary status maybe debatable, the three core elements of a geographical information science asarticulated 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 representationsis currently incomplete. The ® rst area GISci should investigate is how keygeographical concepts such as space and time have been conceptualized by

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

di� erent people and di� erent 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 bestcomputational strategy for the implementation of various conceptualizationsof space will promote interoperability among di� erent computational models.

3. Geographies of the information society. This element focuses on the positiveand negative impacts of technology on individuals, organizations, and society.GISci examines what kinds of new spatial relationships are emerging in thenew information society and what the societal impacts are by introducingGIS into various facets of our social practices. These three core areas inGISci provide us a broad guideline for the future research of GISci-basedurban modelling. I believe that the success of GISci-based urban modellingwill depend upon how successfully we have developed new urban models,new conceptualizations of space and time, and their e� cient/interoperableimplementations on various new computing platforms ( ® gure 2).

4.2. T he development of new urban modelsThis 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 capturethe form, process, and policy aspects of this new reality. It is generally concededamong social scientists that a technological revolution of historic proportions isdramatically transforming the fundamental dimensions of urban society (Grahamand Marvin 1996, Couclelis 1996). The voluminous recent urban literature on worldcities, especially North American cities, is replete with assertions that a majorreorganization of the spatial structure of cities is underway. A series of distinctivenew 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 gentri® ed inner city, and the deepening spatial mismatch between jobsand 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, rangingfrom going back to a more compact pedestrian-based urban form, to stimulating thedevelopment of a completely footloose electropolis.

In order to weave all these di� erent aspects of urban studies into a coherentresearch agenda, we need to develop and articulate a new, eclectic, and inclusiveconceptual framework. I believe that the new theoretical framework should havethree integral components (Sui 1996). First, it should enable us to describe the newemerging urban forms in more comprehensive ways. Second, it should empower usto explain the underlying processes contributing to the emerging new urban forms.Third, it should o� er us new insights to prescribe e� ective urban policies to redirectthe underlying processes to promote the most desirable urban forms. It is beyondthe 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 urbanresearch framework ( ® gure 3).

4.2.1. Urban formsA metropolis in the twenty-® rst century will be a tale of three di� erent, but

interrelated, cities. The speci® c urban forms will be determined by the interplay ofthe following three components:

E T echnopolis . Scholars have used a variety of di� erent names to refer to thisemerging technopolis, ranging from ’electropolis’ and ’wired cities’ to ’city ofbits’, ’computational city,’ and ’virtual community’. Technopolis, narrowlyde® ned, refers to the constellation of massive transportation, telecommunica-tions, and information networks to move goods, people, and information; itis a combination of wheels, wires, and air waves. Technopolis, especially the

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city of bits, or the on-line virtual community, has attracted considerableattention in recent years, but our knowledge of the wired cities remainsnothing more than futuristic prophecies, as presented in Mitchell’s City ofBits (Mitchell 1995). Concerted research e� orts are needed for understandingthis emerging new urban form. Because of the partial invisibility of thetechnopolis (such as the information ¯ ow through the telecommunicationnetwork), modelling and understanding it poses a new challenge for urbanscholars.

E Ecumonopolis . Ecumonopolis is also known as the sustainable city or theecological city. Daunting urban environmental problems have caused plannersto rethink the development policies of the past. The development of ecumeno-polis, with its goal of seeking harmony between human beings and theirsurrounding environment, has increasingly become an integral part of urbandevelopment 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 bethe residents in the cities. To make future cities become anthropopolis is tomake future metropolis become truly the city of/for the people. The conceptof anthropopolis emphasizes the satisfaction of human needs and the qualityof 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 designedso 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, wherewe live and shop, and where we go to entertain ourselves) as enjoyable aspossible. Telecommunications and computer technologies have played increas-ingly important roles in these activities, and yet we are not sure to whatextent they are substitutive, complementary, or synergistic to traditionalmeans of conducting them.

With these three interrelated metropolis in mind, we should make concertedresearch e� orts to understand the optimal urban forms for the cities in the nextmillennium. Do we want the relentless urban sprawl to continue, as facilitated bythe development of new transportation, communication, and information technolo-gies? Or should we go back to more compact pedestrian-oriented urban forms asproposed by some leading urban planners in order to better ful® ll the ideal sense ofcommunity, sustainability, and social equity? Our understanding of the new urbanforms will de® nitely 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 pasttwo 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 intothe following three levels:

E Micro-level processes. This is the individual level process using a behavioralapproach from theories and concepts of neo-classical economics andbehavioral geography (Golledge and Stimson 1997).

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E Meso-level processes. At this intermediate level, attention should be paid tothe roles and behaviors of private and public institutions. We need to examinehow such institutions shape urban development trajectory and thus result indi� erent urban forms.

E Macro-level processes. At this level, we should bring the general societal trendsinto consideration, putting urban development into perspectives of politicaleconomy, economic transformation, long wave rhythms, and world systems.

4.2.3. Urban policiesI believe future policy goals should strive to achieve balance among the following

objectives:

E Economic e� ciency. To develop policies to intervene at the individual, institu-tional, and societal levels to optimize economic e� ciency in technopolis atboth 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 thatthe metropolis will become a city for everybody, with equal access to alldi� erent kinds of information and services and equal shares of environmentalburdens.

E Environmental sustainability . To initiate policies to intervene at the individual,institutional, and societal levels to make the ecumenopolis environmentallysustainable, with plenty of safe water, clean air, and diversi® ed urban nat-ural habitat.

Indeed the information city poses new challenges for us and entails additionalspatial and temporal dimensions of social and economic activities. New urbanrealities demand new urban models. These models should incorporate processes atthe individual, institutional, and societal levels to achieve the goals of economice� ciency, environmental sustainability, and social equity for the metropolis of thetwenty-® rst century in which the technopolis, ecumonopolis, and anthropopolis aresynergistically and artfully integrated. This new type of city demands that we mustdevelop 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 timeThe telemediated cities not only assume new urban forms, undergo fundamentally

di� erent 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 generationof GIS must incorporate multiple dimensions of space and time in order to becomea ¯ 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 importantcornerstones for the implementation of the next generation of GIS.

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4.3.1. Alternative conceptualizations of spacePhilosophers from Aristotle to Kant have developed drastically di� erent views

of space, with varying degrees of objectivity and subjectivity and di� erent concep-tualizations regarding the relationship between space and substance (Sack 1980,Couclelis 1993, Curry 1996 ). Based upon Penrose’s concepts of three worlds (Penrose1994), I would like to group the di� erent 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 ofspaces, the formal/mathematical space is perhaps logically the most consistentand conceptually the most elegant. Although philosophers and scientists alikestill have a hard time explaining the ontological status of these abstractrepresentations, various formal/mathematical spaces have framed our waysof viewing the world since the dawn of civilization. From Euclidean geometryto N-dimensional algebraic spaces, from Hamilton’s state/phase space togeometrical behaviour of vectors in Hilbert space, from cellular automata tofractal geometry, each of these inventions or discoveries of new mathematicalspaces have drastically reshaped our perspectives toward the physical andsocial-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, di� erent kinds of physical/socio-economic spaces havedi� erent manifestations. The major dividing line is the absolute versus. therelative conceptualization of space. The Newtonian (absolute) view treats

Figure 4. Three Worlds and Three Di� erent Kinds of Spaces (Modi® ed after Penrose [1994]).

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space as an empty container, independent of the objects within. Whereas theLeibnizian (relative) view of space contends that space and substances areinseparable, and space is primarily de® ned by the interrelationships amongthe objects. Einstein’s theory of relativity injected not only the Leibnizianview of space but also a novel conception of time or space-time into thetwentieth century consciousness. The shift from the Newtonian absolute viewof space and time to Einstein’s relative view of space-time has exerted far-reaching in¯ uence in our e� orts to understand socio-economic processes insociety. Thrift and Olds (1996) nicely summarized how the shift to di� erentconceptualizations of space may assist us in recon® guring our views of thefundamental changes of economic processes in information society. The fourtopological propositions they discussed in terms of bounded regions, networks,¯ ows, and non-locality will have profound implications on how we actuallyconceptualize the emerging new socio-economic process (Thrift and Olds1996 ).

E Subjective /Experiential spaces. This is the space in the human mind. Howspace is manifested in the human mind has always been a major scholarlyinterest. Some philosophers, such as Kant, even speculated that space is asynthetic a priori Ð an innate precondition of human intellect that makes ourunderstanding the world possible. According to many Kantian and neo-Kantian scholars, space is not another thing in the world, but a frameworkcreated in our mind by the interaction of human reason with the world.Human perceptions of space can be very di� erent from the mathematicalspaces or physical spaces. Studies in cognitive science, behavioural geography,and recent research e� orts on the so-called ’naive geography’ exploring thecommon sense model of the real world have revealed new dimensions of spacein the human mind (Parks and Thrift 1980, Frank et al. 1992, Egenhofer andMark 1995, Mark and Egenhofer 1996) . In the meantime, critical socialtheorists have been arguing that space is produced entirely by various socialprocesses Ð the social production of space (Lefebvre 1991).

All these alternative conceptions of space have developed di� erent 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 timeThe representation of time in GIS is almost non-existent in the current generation

of GIS. Although many researchers have devoted their e� orts toward incorporatingthe temporal element in GIS (Langran 1992, Peuquet 1994, Al-Taha et al. 1994 ),

Table 1. Three spaces and their sample terminologies (Modi® ed 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/DomainCon® guration Distribution/Flows World/Spatial Layout

D. Z. Sui664

alternative ways of conceptualizing time should also be explored (Worboys 1995).Similar to space, time can also be conceptualized by dramatically di� erent structures( ® gure 5). For example, time can be either conceptualized as a discrete or a continuousvariable ( ® gure 5 (a)); time may be linearly or partially ordered or may form atemporal cycle exhibiting periodicities ( ® gure 5 (b)); or time may be associated withtime 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 thepsychological arrow(the direction in which we perceive time pass). In a sense, thesethree temporal models parallel the three major types of spaces. Besides these lineartime models, we should also explore the implications of various non-linear cyclicmodels that may be more appropriate for many phenomena we are trying to model.

These alternative views of space and time will broaden the theoretical foundationsof GIS technology. So far GIS is based upon a Newtonian absolute representationof space coupled with the crude conception of linear time slicing. GISci-based urbanmodeling should explore the new dimensions of space and time, and take a holisticapproach about the multidimensionality of space and time in order to more realistic-ally capture the new urban dynamics during the information age. Modeling the newurban realities demands that we shift our conceptions of space and time tonew dimensions such as the Leibnizian and Kantian view of space and a non-linearconception of time. Perhaps, what is more challenging is how to operationalize theconcept of space-time instead of the Cartesian/Newtonian concept of space and time.These alternative representation schemes for space, time, and space-time will notonly lay a new conceptual foundation for GIS technology, but also turn out to bemore e� ective in many speci® c applications, such as applications of various subject-ive/experiential conceptualizations of space in car navigation systems and navigationaids for the visually impaired, etc. Several new research initiatives are already movingtowards these new directions, such as NCGIA’s initiative 19 on GIS and Society;initiative 21 on NaõÈ ve, etc. Geography (Frank et al. 1992, NCGIA 1996 b, Raperin press).

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

GIS-based urban modelling 665

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

4.4. Computational implementation strategiesTo 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 weknow it today. Although the development of quantum computers may blaze a newholy grail in computation (Deutsch 1997), our understanding of the new urbanreality will be ultimately based upon a combination of computers and humanjudgment. But for those urban models and alternative spatial-temporal concepts thatcan be computerized, we should strive to develop the best computational model fortheir implementations. In the near future, I believe that the implementation of newurban models will hinge on two core concepts Ð the feature-based GIS and theinteroperable GIS. To transcend the static, two- dimensional map metaphor, as beingcurrently implemented in GIS, Lynn Usery’s feature-based GIS (FBGIS) modelseems to be a promising strategy to implement new urban models and the multi-

D. Z. Sui666

dimensions of space-time (Usery 1996). Unlike the layer-based GIS in which we tryto ® 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 andvarious new models depicting the physical and socio-economic processes in the realworld (Tang et al. 1996 ). In a feature-based GIS, space, time and themes are de® nedas integral parts of a geographical feature instead of referencing all the entities intoan arbitrary Cartesian grid. By providing direct access to spatial, temporal andthematic attributes, the FBGIS is not constrained to map and layered representationsof geography and thus supports multiple dimensions of spatial/temporal events.However, there is a crucial element missing from the current version of Usery’sFBGIS Ð the de® nition of operations on a feature. The FBGIS model should befurther expanded to incorporate the dual aspects of the object-oriented paradigmÐthe simultaneous de® nition of state and functionality for an object ( Worboys 1994).The de® nition of operations on a feature should be included as an integral part ofa feature. As some preliminary results have indicated (Ralston 1993, Raper andLivingston 1995), the inclusion of operations in the feature de® nition, together withits capabilities of encapsulation, inheritance/composition, overloading, and poly-morphism, can greatly facilitate the implementation of various spatial analysis andmodelling techniques.

The other very important computing trend is to cultivate the interoperability ofsoftware products across distributed computing platforms (DCPs) according to theconcept of the Open Geo-data Interoperability Speci® cation (OGIS) (McKee 1996).The concept of OGIS and interoperablity has already stimulated new softwaredevelopment trends in the industry, and is also gaining attention among academicresearchers (Egenhofer and Goodchild 1997, Evans 1997 ). Instead of developing afully integrated GIS, software vendors and researchers are exploring new ways ofdeveloping a much leaner core module with numerous more task speci® c, embeddablemodules. These object-oriented, embeddable modules can not only be easily integ-rated into a core GIS package but also be seamlessly integrated with other applicationprograms. 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. ESRI’sMapObjects and the new map server on the Internet are an important step towardfull interoperability. As evidenced by Lin and Zhang (1998), new platform-independent software development tools such as Java de® nitely provide us thepotential 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 thepast ten years, the integration of GIS with urban modeling is essentially technology-driven without adequate justi® cation for the validity of the models and the suitabilityof the spatial-temporal framework embedded in the current generation of GIS. Byreframing the future research agenda from a geographical information science per-spective, the author contends that the integration of urban modelling with GIS mustproceed 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

GIS-based urban modelling 667

of a feature-based strategy for the implementation of these new urban models andspatial-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 andthe rigid spatial-temporal framework embedded in the current generation of GIS.This paradigm shift in urban modelling will enable us to think above and beyondthe technical issues that have occupied us during the past ten years.

Last, but not least, I would like to emphasize that our future research e� ortsneed to be tied more closely to urban policies. There have been growing disparitiesbetween what we purport to describe and manipulate using sophisticated theoreticalframeworks and technical tools in virtual reality and our ability to say anythingmeaningful 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 thehidden structure the model was speaking within (p. 61)’. The new research agendamust strike a balance between the sophistication of our techniques/methods and thereal 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 modelsinto 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 policyimplications using state-of-the-art techniques. Otherwise, our research e� orts maybecome another self-indulging academic exercise.

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