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” that has totally transformed the way we inhabit the planet is globally understood in its socio-economic rationales but is less frequently questioned as a spatio-temporal process. However, the cities, because they are intrinsically linked in a game of competition for resources and development, self organize in “systems of cities” where their future becomes more and more interdependent. The high frequency and intensity of interactions between cities explain that urban systems all over the world exhibit large similarities in their hierarchical and functional structure and rather regular dynamics. They are complex systems whose emergence, structure and further evolution are widely governed by the multiple kinds of interaction that link the various actors and institutions investing in cities their efforts, capital, knowledge and intelligence. Simulation models that reconstruct this dynamics may help in better understanding it and exploring future plausible evolutions of urban systems. This would provide better insight about how societies can manage the ecological transition at local, regional and global scales. The author has developed a series of instruments that greatly improve the techniques of validation for such models of social sciences that can be submitted to many applications in a variety of geographical situations. Examples are given for several BRICS countries, Europe and United States. The target audience primarily comprises research experts in the field of urban dynamics, but the book may also be beneficial for graduate students.

The field of Urban Dynamics itself is based on the systems engineering concept that all complex systems (and cities and urban areas are no exception) are comprised of independent and often smaller, more understandable sub-components with relationships to one another. This allows for the system as a whole to be modeled, using knowledge of the individual subsystems and their behaviors. In this instance, urban dynamics allows for the modeling and understanding of land use, the attractiveness of space to residents, and how the ageing and obsolescence of buildings affects planning and economic development, as well as population movements, with the urban landscape. The book adopts a trans-disciplinary approach that looks at the way residential mobility, commuting patterns, and travel behavior affect the urban form. It addresses a series of issues dealing with the accessibility of urban amenities, quality of life, and assessment of landscape residential choices, as well as measurement of external factors in the urban environment and their impact on property values.

Presents a modern and interdisciplinary perspective on cities that combines new data with tools from statistical physics and urban economics.

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.

A Coming of Age: Geospatial Analysis and Modelling in the Early Twenty First Century Forty years ago when spatial analysis first emerged as a distinct theme within geography’s quantitative revolution, the focus was largely on consistent methods for measuring spatial correlation. The concept of spatial au- correlation took pride of place, mirroring concerns in time-series analysis about similar kinds of dependence known to distort the standard probability theory used to derive appropriate statistics. Early applications of spatial correlation tended to reflect geographical patterns expressed as points. The perspective taken on such analytical thinking was founded on induction, the search for pattern in data with a view to suggesting appropriate hypotheses which could subsequently be tested. In parallel but using very different techniques came the development of a more deductive style of analysis based on modelling and thence simulation. Here the focus was on translating prior theory into forms for generating testable predictions whose outcomes could be compared with observations about some system or phenomenon of interest. In the intervening years, spatial analysis has broadened to embrace both inductive and deductive approaches, often combining both in different mixes for the variety of problems to which it is now applied.

This textbook provides an innovative pedagogy to students who will be the policy makers of tomorrow. It provides thoughts on sustainability and the complexity among its different dimensions. It guides students through experience, processes of complex decision making, and sharpen their clarity of thought, to enhance their communication abilities and help them develop critical thinking. It provides key competencies to address the complexities of sustainable development. By combining game-based learning with an analytical style of education, supplemental materials are provided to make the definitions of various sustainability aspects more concrete and allows students to experiment in a consequence-free environment, with scenario examples. Board Game and a hypothetical management course, dealing with various topics like transportation sustainability, societal metabolism, etc. as well as with decision making under those contexts, will formalize the mathematics needed to make robust decisions.