Urban Dynamics and Simulation Models

Urban Dynamics and Simulation Models | ERC GeoDiverCityNew book, published by Springer International.

Pumain D., Reuillon R. (eds.), 2017, Urban Dynamics and Simulation Models, Springer, 123p.
DOI 10.1007/978-3-319-46497-8

Authors. Chapron P., Chérel G., Cottineau C., Cura R., Leclaire M., Pumain D., Rey-Coyrehourcq S., Reuillon R., Schmitt C., Swerts E.

Abstract. 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.

Key-words. Simulation, Simulation models, Simpop, Systems of Cities, Complexity, Urban systems, Urban systems dynamics, BRICS.

Link. http://www.springer.com/us/book/9783319464954

How large are Chinese and Indian cities?

Reliable figures of cities’ population sizes are a great and useful by-product of comparative geographical analysis. We have identified which are now the major urban concentrations in the largest two countries of the world. Table 1 below provides the list of the population in top 30 Indian cities in 1981 and 2011 and top 30 Chinese cities in 1982 and 2010. In this table the last column on the right side enables comparing our results with figures that are given in official censuses of each country.

Table 1. Population of the 30 largest cities in India 1981 and 2011 and in China in 1982 and 2010Population 30 largest cities India ChinaSource: E. Swerts, 2013, for India : Indiacities database and Indian census; for ChinaCities database and Chinese Census


Towards mega-cities and megalopolises of a new kind

The multisecular Chinese and Indian urban development that intensified since the 1980’s fascinates the observers, largely because it has produced supersized cities, as Shanghai, Delhi and Beijing counting each around 20 million inhabitants. These cities are and will remain on the list of the 10 largest Urban Agglomerations in the World. They do not yet reach the size of formerly developed urban concentrations around Tokyo (38 millions in 2015 according to the United Nations, 43 according to PopulationData.net) or even New York (19 millions in 2015 according to the United Nations, 23 according to PopulationData.net ) but due to their growth rate it is very likely that during the next decades, gigantic conurbations will organize around them: in China three megalopolises are already forming between Beijing and Tianjin, from Shanghai to Nanjing and between Guangzhou and Hong-Kong (including Shenzhen, Dongguan and Zhuhai) (figure 1). In India, the same could occur around Delhi and Kolkata, and from Mumbai to Pune (figure 2). In Kerala the deviations between our database and the census in tentative sizing the agglomerations of Kochi or Thiruvananthapuram reflects the very peculiar expansion of urbanization in that region, which tend to mix very dense urban and rural areas in a way slightly different from Indonesian or Chinese “desakota” (McGee, 1991).

Figure 1. The 30 Largest Cities in China in 201030 largest cities ChinaSource: Chinacities database, E. Swerts (2013)


Figure 2. The 30 Largest Cities in India in 201130 largest cities IndiaSource: Indiacities database, E. Swerts (2013)


Safer data for research as well

Gigantic efforts have been made by many authors for establishing safer figures on the size of urban agglomerations in a comparable way and avoiding big mistakes as in papers electing Chongqing as the largest “city” in the world. Chongqing was supposed to reach from 32 to 34 million of inhabitants 1 because of a confusion in translating the Chinese word for “municipality” that may indeed denote a “province” (in that case covering 82 300 km2, approximately the size of Austria!) whereas the population of the agglomeration, although already large enough, oscillate between 7 or 10 millions according to different sources.

Of course for comparing cities and assessing dynamic urbanization processes building data base where the size of cities is comparable in time and space is absolutely necessary and this step of the work was duly accomplished in GeoDiverCity’s work, for Europe (Rozenblat, 1992; Guerois et al. 2009), Former Soviet Union (Cottineau, 2014), India (Swerts, 2013), China (Swerts, 2013), United States (Bretagnolle et al., 2015), Brazil (Ignazzi, 2015) and South Africa (Baffi, 2016, Vacchiani-Marcuzzo, 2005). All these data bases will be made freely accessible in due time, including detailed information about their methodology and metadata. The methodology employed by Elfie Swerts for building the data bases on India and China is made explicit in the annex in the full post.

Elfie Swerts

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Multilevel comparison of large urban systems

New publication, in Cybergeo, European Journal of Geography

Pumain D., Swerts E., Cottineau C., Vacchiani-Marcuzzo C., Ignazzi C.A., Bretagnolle A.,  Delisle F., Cura R., Lizzi L., Baffi S., 2015, « Multilevel comparison of large urban systems », Cybergeo : European Journal of Geography [En ligne], Systèmes, Modélisation, Géostatistiques, document 706, URL : http://cybergeo.revues.org/26730 ; DOI : 10.4000/cybergeo.26730

Abstract. For the first time the systems of cities in seven countries or regions among the largest in the world are made comparable through the building of spatio-temporally standardised statistical databases. We first explain the concept of a generic evolutionary urban unit (“city”) and its necessary adaptations to the information provided by each national statistical system. Second, the hierarchical structure and the urban growth process are compared at macro-scale for the seven countries with reference to Zipf’s and Gibrat’s model: in agreement with an evolutionary theory of urban systems, large similarities shape the hierarchical structure and growth processes in BRICS countries as well as in Europe and United States, despite their positions at different stages in the urban transition that explain some structural peculiarities. Third, the individual trajectories of some10,000 cities are mapped at micro-scale following a cluster analysis of their evolution over the last fifty years. A few common principles extracted from the evolutionary theory of urban systems can explain the diversity of these trajectories, including a specific pattern in their geographical repartition in the Chinese case. We conclude that the observations at macro-level when summarized as stylised facts can help in designing simulation models of urban systems whereas the urban trajectories identified at mico-level are consistent enough for constituting the basis of plausible future population projections.

Key-words. Urban systems, Zipf, Gibrat, Cities trajectories, BRICS