Empowering Urban Governance through Urban Science: Multi-Scale Dynamics of Urban Systems Worldwide

Abstract

Cities are facing many sustainability issues in the context of the current global interdependency characterized by an economic uncertainty coupled to climate changes, which challenge their local policies aiming to better conciliate reasonable growth with livable urban environment. The urban dynamic models developed by the so-called “urban science” can provide a useful foundation for more sustainable urban policies. It implies that their proposals have been validated by correct observations of the diversity of situations in the world. However, international comparisons of the evolution of cities often produce unclear results because national territorial frameworks are not always in strict correspondence with the dynamics of urban systems. We propose to provide various compositions of systems of cities in order to better take into account the dynamic networking of cities that go beyond regional and national territorial boundaries. Different models conceived for explaining city size and urban growth distributions enable the establishing of a correspondence between urban trajectories when observed at the level of cities and systems of cities. We test the validity and representativeness of several dynamic models of complex urban systems and their variations across regions of the world, at the macroscopic scale of systems of cities. The originality of the approach resides in the way it considers spatial interaction and evolutionary path dependence as major features in the general behavior of urban entities. The models studied include diverse and complementary processes, such as economic exchanges, diffusion of innovations, and physical network flows. Complex systems dynamics is in principle unpredictable, but contextualizing it regarding demographic, income, and resource components may help in minimizing the forecasting errors. We use, among others, a new unique source correlating population and built-up footprint at world scale: the Global Human Settlement built-up areas (GHS-BU). Following the methodology and results already obtained in the European GeoDiverCity project, including USA, Europe, and BRICS countries, we complete them with this new dataset at world scale and different models. This research helps in further empirical testing of the hypotheses of the evolutionary theory of urban systems and partially revising them. We also suggest research directions towards the coupling of these models into a multi-scale model of urban growth.

Urban Intelligence for Planetary Health

“…Nevertheless, urban intelligence only partially exists in a few rich and well-developed cities, primarily within the scope of an individual city. More partnerships on urban intelligence are needed in the future to support information exchange protocol, open data standards, policy alliances, and a long-term synergy of actions at both local-and global-scale [49]. This research may support a global consortium of urban intelligence for planetary health by promoting collective worldwide urban intelligence in the future.…”

Spatial patterns of urbanising landscapes in the North Indian Punjab show features predicted by fractal theory

“…For the foreseeable future urbanisation will continue worldwide and will further expand into rural regions. Hence there is a need to better understand the urbanisation processes not only in urban, but also in rural and transitional regions, and develop strategies to make urban systems more sustainable at national to global scales 39 , 43 , 44 . Theory-based perspectives may enrich the discourse currently dominated by empirical and planning approaches.…”

Spatial dynamics of complex urban systems within an evolutionary theory frame

“…The different models we describe below were benchmarked and applied to several systems of cities worldwide by (Raimbault et al, 2020a). They rely on the same fundamental assumptions and share a common basic structure and formulation: (i) agents are cities, characterized a main state variable which is population; (ii) building on the Gibrat model, these add to endogenous growth additional processes which account for space and spatial interactions; (iii) they simulate not stochastic distributions of city sizes, but their average in time, and are thus specified on these averages only.…”

“…This theory is based on empirical observations and tested with dynamic models that are designed for simulating urban development at various spatial and temporal scales. We summarize here the methodology and results already obtained in the GeoDiverCity project (Pumain et al, 2015;Cura et al, 2017;Pumain and Reuillon, 2017), including USA, Europe and BRICS countries, and the work of Raimbault et al (2020a) completing them with new datasets at world scale and other types of models. These models are designed for explaining urban growth and city size distributions with an increasing deepening in the complexity of the implemented processes Cottineau et al (2015a).…”

“…Eric Denis (2020) already explored the source statistically for comparing urban sprawl trends in the countries of the world. Raimbault et al (2020a) calibrate four different models of urban growth on both sets of data, across different regions of the world, and analyze their results and assess for each their possible contribution to the theory of urban complex systems. We recall here the structure of these models, in relation to the question of how to build integrated urban theories.…”