ABSTRACT
Metro Regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278 19.3 The Design of IDUEM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281
19.3.1 The Conceptual Structure of IDUEM . . . . . . . . . . . . . . . . . . . . . . . 282 19.3.2 Augmentation of Cell Attributes and Space . . . . . . . . . . . . . . . . . . 283 19.3.3 Tightness of Coupling with Urban and Regional Planning Models 286 19.3.4 CA Space-Filling and New Subdivision Development . . . . . . . . . 287 19.3.5 An Object-Based Simulation and Programming Approach . . . . . . 288
19.4 Next Steps: Current Development and Future Plans . . . . . . . . . . . . . . . . . . 291 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 292
19.1 INTRODUCTION
Urban areas have long been recognized as displaying nonlinear, dynamic properties with respect to their growth (Crosby, 1983). Capturing their dynamics, however, is one of the most delicate problems in urban modeling. Only very recently have the conceptual and mathematical foundations for substantive inquiry into urban dynamics been made possible due to our growing understanding of open systems and the way
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human decision processes feed back into one another to generate the kinds of nonlinearity that characterize urban growth and change. Applications have been made possible by fundamental advances in the theory of nonlinear systems, much of it inspired by theories of dissipative structures, synergetics, chaos, and bifurcation in the physical sciences. In fact, many of the originators of these new approaches have seen cities as being a natural and relevant focus for their work. Prigogine’s work on dissipative structures, for example, has been applied to urban and regional systems by Allen (1997) while Haken’s work on self-organization has been implemented for city systems by Portugali (2000) and Weidlich (2000). Many of these applications have built around traditional aggregate static approaches to urban modeling pioneered in the 1950s and 1960s, and were motivated as part of the effort to make these models temporally dynamic and consistent with new ideas in nonlinear dynamics (Wilson, 2000).
