The book Cities and Complexity: Understanding Cities with Cellular Automata, Agent-Based Models, and Fractals provides an in-depth exploration of the dynamic, interconnected, and adaptive nature of urban systems. Cities are not simply collections of buildings and infrastructure; they are complex systems shaped by the interactions of individuals, institutions, and natural processes. This book emphasizes computational and theoretical approaches that help readers understand how local interactions, agent behaviours, and spatial patterns generate the emergent forms and functions of cities. A central theme of the book is the use of Cellular Automata (CA) to model spatial diffusion and urban growth. By dividing urban space into discrete cells governed by simple rules, CA illustrates how small, localized changes can lead to complex city-wide patterns, offering valuable insights into land-use dynamics, urban sprawl, and infrastructure development. Agent-Based Models (ABMs) complement this perspective by focusing on the behaviours and decision-making of individual actors. Through ABMs, readers learn how heterogeneous agents, acting according to preferences and rules, collectively produce emergent phenomena such as residential segregation, traffic congestion, and the evolution of neighbourhoods. The book also explores fractal analysis, which provides a quantitative framework for understanding the structural complexity and self-similarity of cities. Fractals reveal hierarchical patterns, density distributions, and clustering across multiple scales, linking urban form to function and efficiency. By integrating these approaches, the book offers a multi-scale and multidimensional perspective on urban complexity.
Jamie Wood is a leading scholar in the study of urban complexity, spatial modeling, and computational approaches to understanding cities. With extensive experience in urban planning, geography, and systems science, Wood has dedicated much of their research to exploring how cities function as dynamic, adaptive systems. Their expertise spans Cellular Automata (CA), Agent-Based Models (ABMs), and fractal analysis, which are key methodologies for modeling spatial dynamics, emergent behaviours, and structural patterns in urban environments. Wood's work bridges the gap between theoretical urban science and practical planning applications. They have contributed significantly to the development of computational frameworks that allow researchers, planners, and policymakers to simulate urban growth, test policy interventions, and analyze the emergent outcomes of complex interactions among individuals, infrastructure, and institutions. Through research, publications, and teaching, Wood emphasizes the importance of multi-scale modeling, integrating local behaviours with global urban patterns, and understanding the self-organizing properties of cities. As an educator and mentor, Jamie Wood is recognized for making sophisticated computational models accessible to students, urban practitioners, and interdisciplinary researchers. Their work not only advances academic knowledge but also provides actionable insights for sustainable urban planning, smart city development, and resilience strategies. Wood's contributions highlight the critical role of computational tools in interpreting, managing, and designing cities in the face of rapid urbanization and increasing complexity.
| Preface Chapter 1. Cities as Complex Adaptive Systems Complexity Theory and Urban Studies From Mechanistic to Systems Thinking in Cities Nonlinearity, Feedback, and Emergence Self-Organization in Urban Environments Scale, Hierarchy, and Urban Structure Order, Chaos, and Urban Dynamics Limits of Traditional Urban Models Integrating Complexity into City Analysis Chapter 2. Foundations of Urban Modeling Evolution of Urban Models and Simulations Mathematical and Computational Approaches Spatial Representation of Cities Time, Process, and Urban Change Calibration and Validation of Urban Models Data Sources and Urban Observations Visualization and Interpretation of Results Ethical and Practical Considerations Chapter 3. Cellular Automata and Urban Growth Origins and Principles of Cellular Automata Cells, States, and Transition Rules Spatial Diffusion and Urban Expansion Modeling Land-Use Change Edge Growth and Urban Morphology Constraints, Boundaries, and Planning Rules Calibration with Remote Sensing Data Strengths and Limitations of CA Models Chapter 4. Agent-Based Models in Urban Systems Concept of Agents and Autonomous Behavior Decision-Making and Adaptive Agents Interaction, Learning, and Feedback Modeling Households, Firms, and Institutions Residential Location and Segregation Models Mobility, Transport, and Daily Activity Patterns Policy Experiments and Scenario Testing Validation and Interpretation of ABM Results Chapter 5. Fractals and the Geometry of Cities Fractal Theory and Urban Form Self-Similarity and Scaling Laws Measuring Fractal Dimensions of Cities Urban Density and Spatial Patterns Road Networks and Fractal Geometry Growth Processes and Fractal Evolution Comparing Cities through Fractal Analysis Critiques and Methodological Challenge |
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$280.00