Urban dynamics and simulation models

• Main Authors: Pumain, Denise (Author), Reuillon, Romain (Author)
• Format: Electronic eBook
• Language: English
• Published: Cham, Switzerland : Springer, [2017]
• Series: Lecture notes in morphogenesis.
• Subjects: Urbanization > Mathematical models.; City planning > Mathematical models.; elektronické knihy; electronic books
• ISBN: 9783319464978; 9783319464954
• Physical Description: 1 online resource

This monograph presents urban simulation methods that help in better understanding urban dynamics. Over historical times, cities have progressively absorbed a larger part of human population and will concentrate three quarters of humankind before the end of the century. This "urban transition&q...

Table of Contents:

• Acknowledgements; Contents; Introduction; Why Model Cities?; Originality of the Book; Complex Cities and Complex Models; Book Proposition: Exploring Multiple Parsimonious Models; Book Content; Sec5; 1 Is Urban Future Predictable?; 1.1 Emergence; 1.2 Generic Dynamic Features of Systems of Cities; 1.2.1 The Hierarchical Differentiation of City Sizes; 1.2.2 The Meta-Stability of Urban Hierarchies; 1.2.3 A Regular Quasi-stochastic Process of Growth; 1.2.4 Hierarchical Diffusion of Innovation Waves and Functional Specializations; 1.3 Variety in the Evolution of Urban Systems.
• 1.3.1 A Simplified Typology of Systems of Cities1.3.2 Systematic Variations in the Rhythm of Urban Growth; 1.4 Urban Future: Models and Scenarios; 1.4.1 Challenges in Building Scenarios About Urban Evolution; 1.4.2 Challenges in Model Validation; References; 2 The SimpopLocal Model; 2.1 Introduction; 2.2 Purpose of SimpopLocal; 2.3 Entities, State Variables and Scales; 2.4 Processes Overview and Scheduling; 2.4.1 Population Growth Mechanism; 2.4.2 Apply Innovation Mechanism; 2.4.3 Create and Diffuse Innovation Mechanisms; 2.5 Initial Conditions; 2.6 Input.
• 2.7 Running the Model for Parameter Estimates: Calibration2.8 Simulation Results and Return on Observations; References; 3 Evaluation of the SimpopLocal Model; 3.1 Quantitative Evaluation; 3.1.1 Stopping Criterion; 3.1.2 Expectations; 3.1.3 Handling the Stochasticity; 3.2 Automated Calibration; 3.2.1 Optimization Heuristic; 3.2.2 Adaptation of NSGA2 to a Stochastic Model; 3.2.3 Experimental Setup; 3.2.4 Results; 3.3 Calibration Profiles; 3.3.1 Algorithm; 3.3.2 Guide of Interpretation; 3.3.3 Result Analysis; 3.4 Conclusion; References.
• 4 An Incremental Multi-Modelling Method to Simulate Systems of Cities' Evolution4.1 Introduction; 4.2 Methodological and Technical Framework for Multi-modelling Systems of Cities; 4.2.1 Complementary and Competing Theories; 4.2.2 A Methodology for Implementing Multi-models; 4.2.3 Exploiting the Results of a Family of Models; 4.3 A Family of Models of (Post- ) Soviet Cities: MARIUS; 4.3.1 Ordering Possible Causes of Evolution from the Most Generic to the Most Specific; 4.3.2 Implementing Modular Mechanisms; 4.4 Geographical Insights on (Post- ) Soviet City Growth from Multi-modelling.
• 4.4.1 Mechanisms' Performance4.4.2 Parameter Values; 4.4.3 Residual Trajectories; 4.5 VARIUS: A Visual Aid to Model Composition and Interpretation; 4.5.1 Building the Model Online; 4.5.2 Running the Model Online; 4.5.3 Analyzing Results Online or 'How Close Are We?'; 4.6 Conclusion; References; 5 Using Models to Explore Possible Futures (Contingency and Complexity); 5.1 Models as Artefacts of Historically Contingent Complex Systems; 5.2 A Method to Foster Diversity in a Model Outcomes; 5.2.1 The Pattern Space Exploration Algorithm: Principles and Implementation.