Is there a system of Russian cities? Generic properties and specificities in the description and modeling of Russian cities’ interactions

In the context of GeoDiverCity, generic properties of city systems are looked for as stylized facts that apply to these particular objects over the world and over time. Examples of those properties lay in the hierarchy of city sizes (expressed by Zipf’s law), or the process of urban growth (as described by Gibrat in 1931). Using those regular patterns, modeling of the co-evolution of cities becomes possible and useful.

Russian cities oppose several obstacles to the observation of such regularities. The spatial limits of the system varies over time, which complicates  the choice of urban definition, and the collection of reliable data. Moreover, the historical object of Russia and the Soviet Union exhibits strong specificities related to its (supposed absolute) control over urban definition, development, interactions and inner organization. Our work aims at distinguishing the specific from the generic behavior of the Russian system of cities from the urban transition up to now, in order to model its evolution and propose possible projections with the help of Multi-Agent Models.

This project[ref] PhD project of Clémentine Cottineau, under the supervision of Denise Pumain (founded by University Paris 1 Panthéon-Sorbonne) [/ref] begins with the harmonization of urban definitions. Theoretical and data collection constraints led us to consider agglomerations of 10.000 inhabitants and more between 1840 and 2010. Agglomerations have been composed of administrative units which take part in the same built-up area in 2010. Since the boundary of the system is not obvious over the XIX and XXth centuries, its larger extension (the Former Soviet Union) is tested along with its present configuration (the Russian Federation).

Generic models (Zipf, Gibrat) are tested and compared with the results obtained in other geographical contexts. Europe, North America, South Africa, India, China and Brazil are represented in the research fields of GeoDiverCity, sharing the same principles of data harmonization, which helps us in the process of comparison. Other tools are used to explore and explain the specificities of the system of Russian cities (analysis of urban trajectories and financial links between cities with the ORBIS Database produced by Bureau van Dijk, 2010 and augmented by C. Rozenblat).

The characteristics of the Russian system learned from these studies, coupled with the experience accumulated within Géographie-Cités and GeoDiverCity will help modeling the system and simulating its possible futures.

Clémentine Cottineau

How to explore the future of cities? An evolutionary theory including urban dynamics and territorial history

Within the framework of the GeoDiverCity programme we are attempting at modelling the future evolution of cities. As cities are very complex systems, any exact prediction is impossible. However, the exploration of plausible futures is possible, with an increasing approximation according to the length of time duration.

The theory behind our modelling is that cities have to be considered not as isolated entities but as interdependent systems being embedded in complex situations summarised by three major aspects:

–       the system of cities with which they have most of their interactions

–       the territory to which they belong

–       the historical period under consideration

Cities are depending on multiple interactions that occur with other cities in multiple networks for all kind of urban activities from local to global scales – that is why we always consider them as part of systems of cities; cities also are rooted in administrative and political territories that generate specific rules and constraints for their development, at local, regional, national and international levels; during the about ten thousands years period of their existence, the type of relations that cities have had with their environment has changed and despite its rather massive common features the urbanisation process has taken a wide range of variations in different parts of the world.

Analysing the evolution of systems of cities from large urban data bases, we suggest recognising that they share many common features but also exhibit a fundamental geo-diversity that is the expression of path dependence in their development. We can model the common dynamics of systems of cities from the interactions between cities, but for understanding and predicting their differentiated evolution we have to take into account their history.  This does not mean building a narrative of successive events but a careful selection of a few specific historical regimes that contextualise the development of systems of cities all over the world (including for instance quality of natural environment, steps of the demographic transition, or relative situation in innovation networks), as well as a restricted set of events that may have more specifically occurred during the history when trying to predict the evolution of any individual city.

Denise Pumain