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 [ref] Links : http://www.lefigaro.fr/international/2016/04/06/01003-20160406ARTFIG00304-34-millions-d-habitants-chongqing-folle-megapole-chinoise.php, http://www.straitstimes.com/asia/east-asia/chongqing-picked-for-3rd-govt-to-govt-project, http://www.lejdd.fr/International/Asie/Actualite/Chongqing-34-millions-d-habitants-93658 and http://www.lesechos.fr/week-end/voyages/voyages/021666536748-aux-sources-de-lharmonie-1199824.php [/ref] 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


Annex: a comparative methodology for assessing the size of urban agglomerations

In China, cities (“Shi” 市) are fundamentally defined in an administrative way and do not delineate a “strictly urban” unit, as they administrate agricultural areas which are included within their administrative boundaries (Chan & Xu, 1982; Ma, 2005; Chan, 2010). As a consequence, considering the total population of Chinese cities equal to integrate in the counting of the cities population all the agricultural population living in land administrate by the city. Moreover, there are “Shi” at all the Chinese administrative levels[ref] From the lowest to the highest administrative level, there are:
– the Zhen (镇) commonly translated as Town
– the Xianjishi (县级市) or district level cities
– the Dijishi (地级市) or prefecture level cities
– the Zijiashi (直辖市) or Province level cities.[/ref], and the cities’ boundaries of higher administrative level include cities of lower administrative level. Because cities are embedded one in another, the use of the raw census data in statistical analysis leads to two types of error:

  • If the total urban population of the cities is considered, the population of district level cities is counted twice: once isolated, and once with the total urban population of the prefecture city to which the district level city belongs;
  • If the population of the city center (or “city proper” in the literature) is considered (i.e. the population of all the urban districts (Shiqu) for province and prefecture level cities, and those of the district for the district level cities), thus the population of the largest cities can be underestimated insofar as the cities dense urban built up area often extends beyond the boundaries delimited by the urban districts. Conversely, the population of the small district level cities could be over-estimated, the administrative limits of the districts being larger than the boundaries of the district level city.

In India, two types of cities coexist: the Statutory towns and the Census towns. The Statutory towns are cities designated through political arbitrations based on rules and thresholds that differ from State to State. As the State government’s decisions, local requests and political games and relations between local and regional powers strongly influence the designation of Urban Local body, an important interstate variability is observed regarding the urban classification. It particularly impact the smallest entities, in transition from rural to urban, but also to expand the large urban areas, either through their recognition as urban local bodies belonging to census defined Urban Agglomeration or through their inclusion partly or totally as Urban Outgrowth of existing Statutory or Census towns (Sivaramakrishnan et al., 2007; Ramachandran, 2011; Denis et al., 2012; Pradhan, 2012).
The recognition of Census Towns is based on statistical specifications (a threshold of population of at least 5,000 inhabitants, a minimum density of population of 400 inhab. per km2 and at least 75% of the male population engaged in non agricultural activities). These designation criteria are based on the data collected during the previous census, which was held ten years prior to their designation (Denis et al., 2011; Chandramouli, 2013). This led to a decadal underestimation of small towns.

The sources of national censuses are often insufficient for studying the urban phenomenon. This difficulty is first in the political nature of the appointment of cities and their administrative boundaries, which is often inappropriate to capture the spatial evolution of the urbanization process. Moreover, it does not allowed measuring the evolution of the cities over long period of time, and comparing the size and the evolution of the cities defined according to the same referent. Specifically for China, “ the lack of well-defined and standardized terms for urban settlements in China has created much confusion among Chinese as well as Western scholars regarding the size of China’s Urban Population and the nation’s urbanization level ” (Ma et MaCui, 1987). On the other hand, it is necessary to harmonize the definitions of the city as independently as possible of their administrative boundaries in order to enable international comparisons.

So it is necessary to harmonize the definitions of the city as independently as possible of their administrative boundaries in order to enable international comparisons. We have thus constructed two database, one for China called ChinaCities (Swerts, 2013) and one for India called Indiapolis, based on a definition of cities that are morphological agglomerations larger than 10,000 inhabitants (Moriconi-Ebrard, 1993).
The ChinaCities and IndiaCities databases was built by Swerts (2013) according to four steps:

  • In a first step, the continuous urban built area separated by less than 200 meters was delineated using Google Earth images from the year 2000 with a resolution of 7,000 feet (~ 2,134 m).
  • This perimeter was georeferenced and integrated in a Geographic Information System (GIS) and adjusted to entire districts where urban zone was dominant, whatever their urban/rural type (Qu/urban districts, Xian/rural district and Xianjishi/district level cities).
  • In a fourth step, when districts were too large to be contained in agglomeration, the smaller town’s level units (Zhen/towns and Xiang/township) were used to delineate the built-up area perimeter. The data of Zhen were available for 2000 and 2010 but not for previous periods. As a consequence, the urban areas are defined with more precision in 2000 and 2010 and they are more numerous (ChinaCities), but to permit the comparison with previous year, another database was built adapted at the level of districts (ChinaCities adapted to districts) (Tab.1).
  • Because some rural areas can be very dense, both in terms of population and urban built up, the number of towns could be overestimated, some “morphological agglomerations” including overwhelmingly workforce engaged in primary sector’s activities (agriculture, forestry, fishing). To bring a correction, an economic criterion has been added that refines the urban character of these observed morphological settlements. It allows excluding all agricultural morphological districts agglomerations from the database. This was possible by the integration of the demographic and economic data from official census of 1964, 1980, 1990, 2000 and 2010 of districts and associated to the continuous urban built area perimeters.

These databases will be published soon.


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