I just finished reading "The Dynamics of Complex Urban Systems: An Interdisciplinary Approach" edited by Albeverio, S., Andrey, D., Giordano, P. and Vancheri, A. and I thought I would share my thoughts about it.
As we are all aware, cities play a crucial role in our lives, providing habitats for over half of the world?s population. However, understanding such systems is extremely complex as they are composed of many parts, with many dynamically changing parameters and large numbers of discrete actors interacting within space. The heterogeneous nature of cities makes it difficult to generalise localised problems from that of citywide problems. As Wilson (2000) writes, such understanding of cities represents "one of the major scientific challenges of our time". Such understanding how cities function is of crucial importance if we are attempting to tackle problems that such systems face (e.g. urban sprawl, congestion, segregation, etc.) or to make them more sustainable for future generations of inhabitants. One has to understand the complex interactions between urban systems in terms of internal factors (e.g. from the decisions of individuals such as deciding where to locate) to more external factors (such as international economics) along with social developments. Such underlying process can be slow or fast, acting locally or globally. Most urban theory until now has been based on the assumption of slowly varying spatial and social structures. However these notions are now being questioned giving rise to various types of models, such as those employing dissipative dynamics, stochastic cellular automata and agent-based models, fractal geometry, and evolutionary change models, and to further mathematically oriented approaches. In "The Dynamics of Complex Urban Systems", Albeverio et al. (2008) present a range of articles from leading scholars focusing on the above types of models and how approaches developed by different communities can be used to study urban systems and thus gain a greater understanding of how such systems operate.
"The Dynamics of Complex Urban Systems" book is a result of an international workshop which had clear sessions ranging from general dynamical models (e.g. urban growth, pedestrian dynamics), models from economics and models for megacities (e.g. large-scale city formation, socio dynamics), models from information science and data management (e.g. data mining, GIS, data availability), related mathematical and physical theories and models (e.g. neural networks, power laws and phase transitions), models of calibration/validation and forecasts (e.g. comparison of empirical data and simulations), and dynamical models and case studies of real world systems. The chapters presented within this book are arranged alphabetically because the editors of the book believed that there was much overlap between the sessions and the subsequent papers. The only exception is that of the first chapter by Mike Batty entitled "Fifty Years of Urban Modelling: Macro-Statics to Micro-Dynamics" which provides an extensive, chronological and conceptual overview of urban modelling over the last fifty years in the context of current developments and which subsequent chapters explore in greater depth. From reading the edited book this is a well-made decision by the editors. Many of the chapters cross many of the sessions and range from modelling individual movement such as pedestrian models through to traffic simulations and transport networks to the study of systems of cities and innovation processes along the way linking socio-economic and cultural factors (such as employment and housing) to various types of models.
Overall the book is well written and makes a good source of reference of current research, specifically for those interested in studying urban systems using a variety of computational modelling approaches. Furthermore, the book highlights the need for cross-disciplinary research between the natural (e.g. physics, mathematics, computer science, biology, etc) and regional sciences (e.g. geography, economics, architecture, etc) with respect to improving our understanding of the complexities seen within urban systems and how such systems operate.
As we are all aware, cities play a crucial role in our lives, providing habitats for over half of the world?s population. However, understanding such systems is extremely complex as they are composed of many parts, with many dynamically changing parameters and large numbers of discrete actors interacting within space. The heterogeneous nature of cities makes it difficult to generalise localised problems from that of citywide problems. As Wilson (2000) writes, such understanding of cities represents "one of the major scientific challenges of our time". Such understanding how cities function is of crucial importance if we are attempting to tackle problems that such systems face (e.g. urban sprawl, congestion, segregation, etc.) or to make them more sustainable for future generations of inhabitants. One has to understand the complex interactions between urban systems in terms of internal factors (e.g. from the decisions of individuals such as deciding where to locate) to more external factors (such as international economics) along with social developments. Such underlying process can be slow or fast, acting locally or globally. Most urban theory until now has been based on the assumption of slowly varying spatial and social structures. However these notions are now being questioned giving rise to various types of models, such as those employing dissipative dynamics, stochastic cellular automata and agent-based models, fractal geometry, and evolutionary change models, and to further mathematically oriented approaches. In "The Dynamics of Complex Urban Systems", Albeverio et al. (2008) present a range of articles from leading scholars focusing on the above types of models and how approaches developed by different communities can be used to study urban systems and thus gain a greater understanding of how such systems operate.
"The Dynamics of Complex Urban Systems" book is a result of an international workshop which had clear sessions ranging from general dynamical models (e.g. urban growth, pedestrian dynamics), models from economics and models for megacities (e.g. large-scale city formation, socio dynamics), models from information science and data management (e.g. data mining, GIS, data availability), related mathematical and physical theories and models (e.g. neural networks, power laws and phase transitions), models of calibration/validation and forecasts (e.g. comparison of empirical data and simulations), and dynamical models and case studies of real world systems. The chapters presented within this book are arranged alphabetically because the editors of the book believed that there was much overlap between the sessions and the subsequent papers. The only exception is that of the first chapter by Mike Batty entitled "Fifty Years of Urban Modelling: Macro-Statics to Micro-Dynamics" which provides an extensive, chronological and conceptual overview of urban modelling over the last fifty years in the context of current developments and which subsequent chapters explore in greater depth. From reading the edited book this is a well-made decision by the editors. Many of the chapters cross many of the sessions and range from modelling individual movement such as pedestrian models through to traffic simulations and transport networks to the study of systems of cities and innovation processes along the way linking socio-economic and cultural factors (such as employment and housing) to various types of models.
Overall the book is well written and makes a good source of reference of current research, specifically for those interested in studying urban systems using a variety of computational modelling approaches. Furthermore, the book highlights the need for cross-disciplinary research between the natural (e.g. physics, mathematics, computer science, biology, etc) and regional sciences (e.g. geography, economics, architecture, etc) with respect to improving our understanding of the complexities seen within urban systems and how such systems operate.
References
Albeverio, S., Andrey, D., Giordano, P. and Vancheri, A. (Eds.)(2008), The Dynamics of Complex Urban Systems: An Interdisciplinary Approach, Physica-Verlag Heidelberg, NY.
Wilson, A.G. (2000), Complex Spatial Systems: The Modelling Foundations of Urban and Regional Analysis, Pearson Education, Harlow, UK.
Wilson, A.G. (2000), Complex Spatial Systems: The Modelling Foundations of Urban and Regional Analysis, Pearson Education, Harlow, UK.