Albeverio / Andrey / Giordano The Dynamics of Complex Urban Systems

An Interdisciplinary Approach
1. Auflage 2007
ISBN: 978-3-7908-1937-3
Verlag: Physica-Verlag
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 484 Seiten

This book contains the contributions presented at the international workshop 'The Dynamics of Complex Urban Systems: an interdisciplinary approach' held in Ascona, Switzerland in November 2004. Experts from several disciplines outline a conceptual framework for modeling and forecasting the dynamics of both growth-limited cities and megacities. Coverage reflects the various interdependencies between structural and social development.

Autoren/Hrsg.

Albeverio, Sergio

Andrey, Denise

Giordano, Paolo

Vancheri, Alberto

Inhaltsverzeichnis

1;Preface;5
2;Table of Contents;9
3;Scientific Board;11
4;List of Contributors;12
5;Fifty Years of Urban Modeling: Macro-Statics to Micro-Dynamics;19
5.1;1 Historical Antecedents;19
5.2;2 The Time-Lines: Cities, Planning, Modeling;22
5.3;3 Deconstructing the Urban Modeling Time-Line;26
5.4;4 The Quest for Dynamics: The Macro Perspective;31
5.5;5 Towards Micro Dynamics: Agents, Cells and the New Social Physics;33
5.6;6 What Has Been Achieved: Retrospect and Prospect;35
5.7;References;36
6;Complexity: the Integrating Framework for Models of Urban and Regional Systems;39
6.1;1 Introduction;39
6.2;2 Evolutionary Complex Systems;40
6.3;3 Dynamic, Spatial Urban Models;46
6.4;4 Manufacturing Evolution;50
6.5;5 Structural Attractors;55
6.6;6 Conclusions;57
6.7;References;58
7;Ontogeny and Ontology in Complex Systems Modeling;60
7.1;1 Introduction;60
7.2;2 Dynamical Hierarchies;61
7.3;3 Ontogeny;63
7.4;4 The Network Model;66
7.5;5 Discussion;70
7.6;References;74
8;A Model for Asystematic Mobility in Urban Space;76
8.1;1 Introduction;76
8.2;2 The Mobilis in Mobile Model;77
8.3;3 Applications to Realistic Situations and Experiments;85
8.4;4 Conclusions;89
8.5;Acknowledgments;89
8.6;References;89
9;Preliminary Results of a Multi-Agent Traffic Simulation for Berlin;91
9.1;1 Introduction;91
9.2;2 The Model;92
9.3;3 Set-Up of the Berlin Simulations;98
9.4;4 Preliminary Results;103
9.5;5 Discussion;106
9.6;6 Summary and Conclusion;107
9.7;References;107
10;Hybrid Geographical Models of Urban Spatial Structure and Behaviour;111
10.1;1 Introduction;111
10.2;2 Microsimulation and Spatial Evolution;112
10.3;3 Simple Models of the Urban Labour Market;114
10.4;4 Semi-Aggregate Models of the Urban Labour Market;118
10.5;5 An Interacting Fields Model;120
10.6;6 Conclusions;123
10.7;References;124
11;Two Complexities and a Few Models;126
11.1;1 Premises;126
11.2;2 What Is a Good Model?;131
11.3;3 Why Planning Is (Still) a Necessity and Why It Needs Models;132
11.4;4 A Tool-Box for Planning;134
11.5;5 The Time Machine;144
11.6;Conclusions;153
11.7;References;154
12;Cities as Evolutionary Systems in Random Media1;157
12.1;1 Introduction;157
12.2;2 The Model;160
12.3;3 First-Order Quenched Moment;162
12.4;4 The Feynman–Kac Formula;163
12.5;5 Lyapunov Exponents for;164
12.6;6 Intermittency of;167
12.7;7 Higher-Order Quenched Moments;169
12.8;8 Adequacy of Moments;171
12.9;9 Concluding Remarks;172
12.10;Acknowledgements;173
12.11;References;174
13;Grilling the Grid: a Non-Ultimate (Nor Objective) Report on the Configurational Approach to Urban Phenomena;176
13.1;1 Introduction;176
13.2;2 The Configurational Approach: Conceptual Basis;178
13.3;3 The Configurational Approach: Techniques and Methods;182
13.4;4 Operational Techniques: the;182
13.5;5 Operational Techniques: the;189
13.6;6 Operational Techniques: Potentials, Limits and Integrations;191
13.7;6 Conclusions;194
13.8;References;195
14;Validating and Calibrating Integrated Cellular Automata Based Models of Land Use Change;197
14.1;1 Introduction;197
14.2;2 The Validation Problem;199
14.3;3 A Case Study of Calibration: ENVIRONMENT Explorer;207
14.4;4 Semi-Automatic Calibration and Validation of Environment Explorer;211
14.5;5 Results - The Pilot Case: ENVIRONMENT Explorer for the Netherlands;218
14.6;6 Discussion;220
14.7;7 Conclusions;221
14.8;References;222
15;Fractal Geometry for Measuring and Modelling Urban Patterns;224
15.1;1 Some Features of Urban Patterns;224
15.2;2 Fractal Models for Urban Patterns;229
15.3;3 Measuring Fractal Behaviour of Urban Patterns;234
15.4;4 Some Empirical Results;240
15.5;5 Urban Pattern Morphogenesis as Self-Organisation Process;245
15.6;5 Conceptual Conclusions;249
15.7;Acknowledgments;252
15.8;References;252
15.9;Cartographic Data Sources for Figures;254
16;The Dynamics of Complex Urban Systems: Theory and Application of the STASA-Model within the Scatter Project;255
16.1;1 Introduction;255
16.2;2 The Stuttgart Case City;256
16.3;3 The STASA Land-Use and Transport Modelling Framework;258
16.4;4 Results of the Simulated Scenarios;265
16.5;References;273
17;Study of Urban Developers’ Behavior in a Game Environment;275
17.1;1 Introduction;275
17.2;2 From “Memory” to “Delay:” Markov Process as a Landmark;276
17.3;3 Description of the Experiment;279
17.4;4 Analysis of the Experiment;282
17.5;5 From Transition Rules to Integral Description of Participants' Behavior;287
17.6;6 The Simulation Model of Participants' Behavior;288
17.7;8 Evaluation of Model Results;290
17.8;9 Behavior of the Human Participant Versus the Model;293
17.9;Acknowledgements;294
17.10;References;295
18;Self-Organization and Optimization of Pedestrian and Vehicle Traffic in Urban Environments;297
18.1;1 Spatio-Temporal Patterns in Pedestrian Flows;297
18.2;2 Trail Formation;307
18.3;3 Self-Organized Traffic Light Control;311
18.4;4 Summary and Conclusions;316
18.5;Acknowledgments;317
18.6;References;317
19;Multidimensional Events in Multilevel Systems;320
19.1;1 Introduction;320
19.2;2 Relations and Structure: Graphs and Networks Are Not Rich Enough;321
19.3;2 Simplicial Complexes and Emergence;323
19.4;3 Hierarchical Aggregation;324
19.5;4 Alpha- and Beta-Aggregations in Lattices Hierarchies;325
19.6;5 What Is a City?;326
19.7;6 Multidimensional Connectivity and Q-Analysis;330
19.8;7 Backcloth and Traffic in Multilevel Systems;332
19.9;8 Polyhedral Events and Order-2 Dynamics;333
19.10;9 Examples;336
19.11;10 Conclusions;342
19.12;Acknowledgement;343
19.13;References;343
20;The Simulation of Spatial Change: What Relation Between Knowledge and Modeling? A Proposal and Its Application;344
20.1;1 Introduction;344
20.2;2 What Knowledge to Build Knowledge?;345
20.3;3 The Application;349
20.4;4 Data and Results;353
20.5;5 Conclusions;362
20.6;Acknowledgements;363
20.7;References;363
21;A Structural-Cognitive Approach to Urban Simulation Models;366
21.1;1 Definitions;366
21.2;2 Justification;366
21.3;3 Forgotten Cities;367
21.4;4 Imagined Cities;369
21.5;5 The Ghost in the Machine;370
21.6;6 Problems;371
21.7;7 The Ghost Is the Machine;374
21.8;8 SIRN – Synergetic Inter-Representation Networks;376
21.9;9 Cognitive City;378
21.10;10 Concluding Notes;380
21.11;References;380
22;The Socio-Spatial Dynamics of Systems of Cities and Innovation Processes: a Multi-Level Model;382
22.1;1 Introduction ;382
22.2;2 An Evolutionary Theory of Systems of Cities;383
22.3;2 Multi-Agents Systems as Flexible Modelling Tools for Spatial Interaction;389
22.4;3 SIMPOP2 as a Multi-Level Model;391
22.5;4 Conclusion;395
22.6;References;396
23;The Great Return of Large Scale Urban Models: Revival or "Renaissance"?;399
23.1;1 Introduction;399
23.2;2 Evidences of OLSUMs’ Return;400
23.3;3 The Core Question: Revival or “Renaissance”;404
23.4;4 Six Challenges (Plus One) for a Renaissance of Models;406
23.5;5 Conclusion: the 7th Challenge;413
23.6;References;414
24;The Multi-Agent Simulation of the Economic and Spatial Dynamics of a Poli- Nucleated Urban Area;416
24.1;1 Introduction;416
24.2;2 The Model;419
24.3;3 Agents Interaction and Strategies;420
24.4;4 Global Dynamics;426
24.5;5 Experiments and Validation;427
24.6;6 Calibration of Parameters;430
24.7;7 The Interaction with Human Users and the Utilization of the Model;431
24.8;8 Conclusion;432
24.9;Acknowledgment;432
24.10;References;433
25;Modelling the Micro-Dynamics of Urban Systems with Continuum Valued Cellular Automata1;435
25.1;1 Introduction;435
25.2;2 Urban Structure of The Cellular Automaton;438
25.3;3 Stochastic Structure of the Cellular Automaton;444
25.4;4 Fuzzy Decision Theory for Urban Processes;447
25.5;5 Evolution Algorithm;454
25.6;6 The Artificial Case Study ArtCity and Simulations;456
25.7;7 Conclusions;460
25.8;References;460
26;Multiplicative Processes and City Sizes;463
26.1;1 Introduction;463
26.2;2 Multiplicative Processes in Human Populations;464
26.3;3 Zipf’s Law and City Sizes;466
26.4;4 Formulation of Simon’s Model;469
26.5;5 Extensions of Simon’s Model;473
26.6;6 Conclusion;476
26.7;Acknowledgments;477
26.8;References;477
26.9;Annex: Poster Sessions;479
27;The Features and Challenges of the Urbanization Course in China;480
27.1;1 The Fundamental Features of China’s Urbanization;480
27.2;2 The Encountered Challenges of the Virtuous Development of China’s Urban and Rural Systems;482
28;Introducing to Simulating Methodology of Urban Systems;484
28.1;1 Open Complex Giant Systems (OCGS);484
28.2;2 The Methodology of Research for the OCGS for OCGS;485
28.3;3 Metasynthesis May also Use Knowledge Engineering;486
28.4;4 The Meaning of the Research of OCGS;487
28.5;5 Complementary Remarks;488