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In 2050, urban India will be home to fourteen per cent of the world's urban population. In less than thirty years, half of India's population will have to cope with urban life and there will be tremendous transformation of landscape, economic structure and social life. In order to forecast India's urban future, we assumed that secular and contemporary growth trajectories of all individual urban agglomerations are key drivers of future urbanization trends. We demonstrate that India's city-system conforms to the distributed growth model and that its hierarchical distribution is evolving regularly. India's plurisecular city-system fits well with the canonical model that describes universally the system dynamics. It shares common characteristics with several mature urban structures around the world. We show also that the location of the town has little influence on its growth trajectory. Nevertheless, individual trajectories can be classified, either by the secular trend of towns (1901-2011) or on the basis of the more recent genesis of the contemporary urban agglomerations landscape (1961 to 2011). These classifications are structured over time and space according to subsystems and regional specificities.
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Draft Paper: not to be quoted without authors' permission
29 April 2013
The future of India's urbanization
Elfie Swerts, Denise Pumain, Eric Denis
In 2050, urban India will be home to fourteen per cent of the world’s urban population. In less
than thirty years, half of India’s population will have to cope with urban life and there will be
tremendous transformation of landscape, economic structure and social life. In order to
forecast India’s urban future, we assumed that secular and contemporary growth trajectories
of all individual urban agglomerations are key drivers of future urbanization trends. We
demonstrate that India's city-system conforms to the distributed growth model and that its
hierarchical distribution is evolving regularly. India's plurisecular city-system fits well with
the canonical model that describes universally the system dynamics. It shares common
characteristics with several mature urban structures around the world. We show also that the
location of the town has little influence on its growth trajectory. Nevertheless, individual
trajectories can be classified, either by the secular trend of towns (1901-2011) or on the basis
of the more recent genesis of the contemporary urban agglomerations landscape (1961 to
2011). These classifications are structured over time and space according to subsystems and
regional specificities.
More than half the world's population now lives in cities and the "urban transition" that began
early in the ninetieth century will take less than a hundred years to complete. The developing
countries, still in transition, are more populated than the developed countries where the
transformation is complete since two or three decades. Today, two-thirds of all city-dwellers
are found in less wealthy nations. While the tremendous surge towards urbanization in the
twenty-first century may be broadly envisaged, it is necessary to provide for multiple local
territorial expressions, especially for larger cities which are attracting lot of interest.
Simulation models, indispensable to predict the distribution of the urban growth, may be
based on known dynamics to the extent that they are similar and they converge increasingly
towards similar modalities, the similarity being explained by the networking of the cities
around the world with globalization of interaction. We propose a method to predict the
evolution of urban population that uses past trajectories of cities relative to the system they
belong to. The Indian subcontinent makes a good case study as it is still less urbanised and
has a long established and relatively reliable set up of statistical observation.
An earlier attempt shows that it is possible to estimate trends with reasonable accuracy.
Davis’ prediction in 1962 of the level of India's urbanization in the year 2000 is seen today to
be quite successful in his estimate of urban population and its share of the total population of
the country (Davis, 1962). His method was based on the classic hypothesis of universal linear
stages in urban transition with a direct reference to the pattern in the USA, adjusted later by
applying some logistic parameters. His estimate of India’s total population (1 billion in 2000
for the medium estimate) is fairly accurate and the predicted urbanization rate of 30.8% for
cities with 20,000 inhabitants or more is slightly higher than the official urbanization rate of
28% in the 2001 Census. However, his predictions for the biggest cities were extremely
uncertain and he overestimated their populations. For instance, Davis expected between 9 and
32 million inhabitants for Madras (that has since been renamed as Chennai) and between 32
and 66 million for Calcutta, whereas in 2001, there were only 6.5 million and 13 million
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29 April 2013
people in Chennai urban agglomeration (UA) and Kolkata UA respectively.
Metropolitanization has been slower than predicted by Davis, more regional and intermediary
cities, as well as smaller towns have emerged and forms of diffusion and concentrated
dispersion have prevailed. India’s level of urbanization remains low (31% in 2011) as
compared to China’s, for instance, where it is 50%. Residential migration toward cities does
not contribute very much to urban growth and has not increased in thirty years
(Sivaramakhrishnan et al., 2005; Chandrasekhar, 2010).
Nevertheless, one in ten city-dwellers of the world lives in India today. India's urban
population is already enormous. The agglomeration process makes it potentially even bigger
with 38% of India's population living in continuously built-up settlements with more than
10,000 inhabitants (Denis & Marius, 2011). This raises questions about the future expansion
of Indian cities, especially its large metropolises after the next decades of potentially very
high urban growth.
Projections of urban population for all countries and for a few large cities are available from
several UN organization sources (UN, 2012). They have been criticized for overestimating
urban growth, because they are based on linear inter-census growth rates, and because they do
not take into account the major trend in the expression of “urban transition” (Bocquier,
2004)coined by W. Zelinsky (1973) –although they use a logistic curve model for predicting
the evolution of total urban population. The more sophisticated population prediction methods
that are conceived for national and local systems rely mainly on demographic methods
including cohort-component, trend extrapolation, and structural models (Smith et al.,
2002).The method that we propose here is both structural (rooted in the dynamics of co-
evolution in urban systems) and extrapolation of trend and also includes reference to the stage
in demographic transition. Its aim is to provide a more diversified view of the future evolution
of individual cities. The large historical database required for this was constructed in
collaboration with several agencies (Swerts, 2013).
The main difference between our approach and that Davis is that, (using a very detailed
database incorporating all the urban settlements with their population from 1901 to 2011) we
have projected the population of each city considered as a separate entity whereas Davis
based his estimates on classes of towns except for the ten biggest metropolises, which he
treated individually. UN-Habitat, UN Population Division, as well as World Bank still use
city size classes to estimate future growth. Cities with “fewer than half a million inhabitants”
or even with 750,000 have no individual existence in their databases. Demographers, who
follow this method and ignore the disaggregated dynamics of the entire city-system, are
usually not able to predict the spatial distribution of urban future and always tend to
overestimate polarization toward “major metropolitan area”.
The two complementary geo-databases that we used are presented in section 1. In section 2,
we describe, the current Indian system of cities. We examine the urbanization trend of the last
century in section 3 and discern the genesis of the present spatial distribution. The earlier
trajectories (since 1901) partly explain this genesis whereas the more recent ones (since 1961)
constitute the reference for our prediction model in order to forecast the urbanization in 2050
(section 4). In section 5 we present the results of our projections based on the detailed
knowledge of the existing system of cities and its earlier trajectories. Our predictions are
finally compared with that of UN agencies and the future rate of urbanization is expound.
1 Harmonised data bases for the study of urbanization
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29 April 2013
The referential for our prediction exercise is composed of two complementary sets of data.
Both are geo-databases incorporating the whole Indian system of cities.
The first, called IndianCensus, is based on the official towns as given by the census series
since 1901. The current urban classification used in 2001 and 2011 includes: (a) all places
with a municipality, corporation, cantonment board or notified town area committee, etc.
irrespective of their demographic characteristics (called Statutory Town) and (b) all other
places that satisfied the three following criteria: i) a minimum population of 5,000; ii) at least
75 per cent of the male working population engaged in non-agricultural professions; and iii) a
density of population of at least 400 per sq. km (called Census Town). The last two criteria
are based on the previous census (2001) for 2011 Census towns.
Many authors have underlined the problem of comparing over time and space the urban
census data in India (Landy, 2002; Bhagat, 2005; Sivaramakrishnan et al., 2005;
Ramachandran, 1989; Denis et al., 2011; Denis et al., 2012; Pradhan, 2012). They point out
mainly the fuzziness of criteria that designate Statutory Town and Census Town as well as the
lack of homogeneity in their application by different Indian States and from one census to the
next since 1951.
The Indian Census database incorporates all the local units defined as urban by the Census
administration from 1901 to 2001, and those that have been downgraded to the status of
village for one or more decades between 1901 and 2001
, but still depends on the change in
the definition from Census to Census and its use from State to State. This database includes
3,545 cities of more than 10,000 inhabitants in 2001.
The second geo-database called Indiapolis is composed of 18,365 agglomerations with more
than 5,000 inhabitants in 2001 regardless of their census or administrative status, whether
urban or not. The existence and extent of physical agglomeration has been assessed and
delineated using satellite imagery considering continuously built up areas with less than 200
meters between constructions. The total population of an agglomeration is thus the sum of the
populations of all the census local units (towns and villages) falling within it. For all these
agglomerations and their components, the census population has been collected since 1961.
The population figures of 2011 consist of data provided by the census for towns with over
100,000 inhabitants and the estimates for each smaller unit included in the set of
agglomerations. These estimates are based on the number of households given by the 2011
Census for each urban settlements and the average size of households in urban area of each
district. All the physical agglomerations with at least 10,000 inhabitants are considered as
urban. This set of cities is affranchised of administrative boundary. Indiapolis is part of a
worldwide urban database, e-Geopolis, which uses the UN recommendations for the
definition of a city (Moriconi, 1993).
Indiapolis database is based on a raw fact, the observed settlement agglomeration existing in
the physical environment whereas official urban category is an institutional fact, the urban
classification being an assigned function conferred by intentionality within the government
apparatus. The Indiapolis urbanization rate determined from the urban agglomeration data
described above is 10% higher than the official rate (Denis & Marius, 2011). It is certainly
more suited to forecast the urbanization given the uncertainty of future urban-rural
This database is the product of François Moriconi-Ebrard, Sylvie Dubuc (1994), Joel Querci (2010) and Elfie
Swerts (2013) successive works.
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The approach chosen will permit to better envisage the future Indian city system, either when
restricted to the urban governance territory or when considering the more "natural" and larger
space of socio-economic investments that induce physical agglomeration.
The study of the evolution of the Indian system of cities in the twentieth century relies on a
combination of two databases: Indian Census between 1901 and 1951 and Indiapolis from
1961 up to 2011.
2 The structure of the Indian system of cities
Cities are strongly connected by material and non-material relationships and multiple spatial
and social interactions that give rise to interdependence and complementarity among them.
Hence they should not be considered as isolated entities, but as objects evolving together
within systems defined by their interactions, at regional, national and global levels (Pumain,
1982 ; 1997 ; 2006)
Several studies (Moriconi-Ebrard, 1993, Bretagnolle et al., 2007; Pumain et al., 2013
Geodivercity) show that the dynamic processes in systems formed by cities in different
regions of the world and the spatial organisation of these systems are universal. There exists a
regular hierarchical distribution of city size (Zipf's law) that is the result of a process of
distributed growth in which it is probable for all the cities to grow at the same rate in each
time interval (Gibrat model). However, beyond the common structures and dynamics, the
city-systems in various parts of the world present singularities resulting from their evolution
in historical and political contexts that are sometimes very different. Thus identification of
generic evolutionary mechanisms and processes peculiar to the Indian city-system should
enable better prediction of its future evolution (Pumain, 1982; 1997; 2006; Bretagnolle et al.,
The hierarchical distribution of Indian cities follows a rank-size rule, whichever be the period
or demographic database considered (Sharma, 2003; Schaffar and Dimou, 2012; Swerts and
Pumain, 2013).
Figure 1. Rank-size rule: India 1901-2011
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Source: Combination of census data for the period 1901-1951 and Indiapolis data for 1961-
The rank-size rule, when applied to Indian cities as defined in the Census, and to
morphological agglomerations as defined in Indiapolis, shows that the system of Indian cities
is not strongly hierarchical, which is characteristic of regions urbanized long ago and in which
small towns still survive (Denis et al., 2011). In 2001, the Indian slope is 0.89 with Indiapolis
data. In 2011, this value remains the same and 0.99 with Indian Census data.
This slope is close to that observed in Europe (0.96 in 2000), also a region where urbanization
is centuries old, and is in contrast to those observed in the USA (1.13) and South Africa (1.20)
where urbanization is relatively recent
(Moriconi-Ebrard, 1993; Bretagnolle et al. 2007,
The singularity of the distribution of Indian cities is caused by the preponderance of three
gigantic megalopolises: Delhi, Kolkata and Mumbai, of around 16 million people (Figure 1),
and by the presence of a set of "secondary cities " with large populations compared to all
other cities in the system: Thiruvananthapuram, Chennai, Hyderabad, Bangalore, Ahmadabad
and Pune having populations of between 3 and 7 million in 2001 (Shaw, 1999; Landy, 2002)
The comparison here is meaningful as it applies to a large number of urban entities that are similarly designed.
The hierarchical order of these cities as well as their population has evolved: in 2011 they counted between 4.5
million and 9.5 million inhabitants, the largest is Hyderabad, followed by Thiruvananthapuram, Bangalore,
Chennai, Kanpur, Pune and Ahmedabad.
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This configuration, which emerged in the twentieth century (Figure 1), is the combined result
of endogenous urbanization over several centuries (Delhi, Hyderabad and Ahmedabad) and
the influence of the colonial period (Mumbai, Kolkata and Chennai, the gateways to India by
sea) (Durand-Dastès, 2003).
3 The century-long history of Indian urban hierarchy
Along with the emergence of the large Indian metropolises, the hierarchical organization of
Indian cities has strengthened in favour of large cities first in the 1930s, marked by the onset
of the demographic transition and the rural exodus (Landy, 2002) and then, mainly in the
decade 1951-1961, after Independence, marked by the increased density of the Indian urban
This hierarchy has evolved at a regular pace over the last century, as shown by the rank-size
graph (figure 1), even though the size distribution of Indian cities is not strongly hierarchical.
The stability of the rank-size curve between 1901 and 2011 signifies that growth was
distributed among all the cities of the system, regardless of their size, with a slight bias
favouring the growth of large cities between 1931 and 1961. The Gibrat model is validated at
the national as well as at the regional levels regardless of the period or database considered
(Sharma, 2003; Schaffar and Dimou, 2009; Swerts and Pumain, 2013).
Despite this match with the stochastic model of "distributed growth", there are still
differences in the rates of change when the cities are sorted into size classes (Figure 2), some
of the variations being significant (Swerts and Pumain, 2013). However, from the year 1961
in the case of Indiapolis data and 1971 for Indian Census data, the rates of change of the urban
population of all size classes are less differentiated (Figure 2). Moreover, since 1961, the
rank-size curves show that hierarchical differentiation slows down considerably (Figure 1).
Figure 2: Growth by size class: 1901-2011
Source: Census data for the period 1901-1951 and Indiapolis data for the period 1961-2011.
4 Secular and more recent trajectories of Indian cities
It must be recalled that, in a complex system (Bretagnolle et al., 2006), the structure of the
urban system observed at a macro-geographic scale is produced by the multitude of individual
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29 April 2013
evolutions of cities at micro-geographic scale. In order to establish this connection, we
analyse the trajectories of Indian cities during the twentieth century, using a database that
combines the census data for the period 1901-1951 and the Indiapolis data for the period
. Using ascending hierarchical classification obtained by Chi-square distance,
which groups together cities with a similar evolution profile irrespective of city size, we
identify six classes describing the population evolution of 1,163 cities for which data are
available for the period 1901-2011. These trajectories are represented on Figure 3 by the
curve of the average population of each class, using absolute population figures on the left
side of the graph, (all curves are then upward due to the distributed growth) and relative
figures on the right side, obtained by dividing the average population of the class by the total
population of the city system at each date: the curves are then divergent, which helps to
differentiate their evolution.
Figure 3: Trajectories of Indian cities for 1901-2011
The significant increase of the slope of the rank-size curve between 1961 and 1971may be attributed to changes
in the criteria that define towns from 1961onwards (Sivaramakrishnan et al., 2005)
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Source: census data for the period 1901-1951 and Indiapolis data for the period 1961-2011
(Software: Trajpop : Robin Cura, 2011)
The trajectories of Indian cities can be divided into two phases. The first that extends from
1901 to 1961 is a period of rapid urban growth in which the hierarchical organization of
Indian cities favours large cities, which in terms of the trajectories results in an increased
weight of biggest cities, and surrounding towns (class A) within the system. Meanwhile, the
trajectories of cities in classes B and C are descending, a trend that is more marked in 1931
and 1951. From 1961, urban growth slows down, the rate of population growth by cities size
class becomes uniform and the hierarchical organisation slows down considerably.
Simultaneously, a phase of relatively stable trajectories of cities begins in 1961 for the cities
of class A and B. However, we note that from 1991, the weight of the cities of class A
increases slightly even as the trajectories of cities in class C take a new downturn.
It is in the region around Bangalore, in the "corridor" linking Hyderabad, Mumbai,
Ahmedabad and Delhi, in North-West Delhi and on the south coast of Andhra-Pradesh, that
the weight of the cities in the system has increased the most.
Finally, throughout the period, 42% of cities have seen their weight going up within the
Indian system (class A), while 68% have experienced a relative decline. Indian urban growth
thus seems to have been concentrated in a few large cities, spreading outward towards the
surrounding towns although this trend seems to have diminished significantly from 1961.
The secular trajectories of Indian cities explain most of the actual features of the structure of
the system of cities. However, in urban systems, the path dependence may be quite limited,
particularly because some radical changes occurred in the spatial distribution of activities
during the last decades. In order to improve the quality of projections, we need a more precise
view of the recent evolution that may prepare the future dynamics during the next decades.
The period must not be too short either, so as to avoid wide and usual random fluctuations of
urban growth rates measured over simple census intervals. That is why we conducted a new
analysis covering the period 1961 - 2011, on the evolution of 7,268 morphological
agglomerations that have more than 10,000 inhabitants in 2011. They are assembled into five
classes, on the same principles as those used for the analysis of city trajectories over the
period 1901-2001. For this period, major inflections are seen in 1991.
Figure 4: Trajectories of Indian cities between 1961 and 2011
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More than 45% of the cities have an overall upward relative trajectories (Classes A and D)
and 25% (Class B) a stable trajectory between 1961 and 2011. Class D contains 398 cities
(5.5% of the total number of cities) that are distinguished by their strong upward trajectory in
1991. Class D consists essentially of very small towns; towns with less than 25,000
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29 April 2013
inhabitants constitute 70% of it (against 65% of the entire dataset). It includes only 3 major
cities with a population of over a million (Pune, Amritsar and Salem).
Apart from those in class D, cities with a population of less than 25,000 inhabitants are
slightly under-represented in classes with ascending trajectories, especially in Class A (only
60%) and in contrast, slightly over-represented in classes with descending trajectories (class
C). 75% of Cities with a population of over a million have an upward trend, as also the capital
cities of states and districts. Among the cities with descending curves, we find Kolkata, large
towns of Kerala and very old cities such as Madurai, Varanasi and Mysore. Finally, the
location of a city has a smaller influence on its trajectory in the period 1961-2011 than in the
twentieth century as a whole. However, the cities situated on the coast are generally less
dynamic than those in the interior.
5 Projection method and results for the period2011-2050
The growth of urban population results from the growth of existing cities and the emergence
of new ones. For projecting the population up to 2050 for cities with over 10,000 inhabitants
in 2011, we determined the contribution of the growth rate of cities existing in 1961 to the
growth of the total urban population between 1961 and 2011, and then we calculated the
population of Indian cities using:
1) the same growth rate for all cities (proportional projection)
2) a growth rate proper to each class of cities identified by their trajectories between 1961
and 2011, ie the ratio between the average growth rates of cities in each class and the
growth rate of the total urban population
We then compare our results with those obtained by applying the growth rate predicted by the
UN for the 65 largest cities in India over the period 2010-2025
(table 1).
Table 1: Population of the 20 largest cities in 2025 and 2050 according to proportional,
segmented by 1961-2011 trajectories methods and UN projections
For a better precision, we use a partition in 5 classes to work on the cities’ population projection.
Draft Paper: not to be quoted without authors' permission
29 April 2013
5.1 Application of the same growth rate
If we apply the same growth rate to all Indian cities over the period 2011-2050, the
hierarchical distribution pattern is preserved. Delhi, Mumbai and Kolkata dominate the Indian
system, with populations of 37, 30 and 29 million respectively. The macrocephaly index value
between the third city (Kolkata) and the fourth largest city (Hyderabad) changes from 2 in
2011 and 2025 to 1.72 in 2050 (Table 1).
These largest metropolises are followed by secondary metropolises, Hyderabad,
Thiruvanantapuram, Chennai and Bangalore, with populations of 14-16 million in 2050. The
hierarchical distribution coefficient (rank-size slope), meanwhile, remains unaltered between
2011 and 2050 (0, 89) (Table 1).
5.2 Application of the growth rates segmented according to 1961-2011 trajectories
Application of growth rates differentiated according to type (above growth rate weighted with
the ratio of trajectory class growth rate to that for all Indian cities in the period 1961-2011),
yields results that are different from those obtained earlier, especially for cities at the top of
the hierarchy, which itself becomes more regular. The sizes of the three major cities Delhi,
Mumbai and Kolkata diverge with populations of 42, 32 and 26 million respectively. The gap
between these three major cities and secondary metropolises decreases significantly, the ratio
between the populations of the third city (Kolkata) and the fourth largest city (Hyderabad)
being only 1.35. However, a slight break in slope occurs between the 9
city (Pune) and 10
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29 April 2013
(Ahmedabad). Overall, the hierarchical distribution coefficient changes very little from 0.89
in 2011 to 0.90 in 2050.
When comparing population projections obtained with this method of segmented growth rates
and those resulting from an identical growth rate for all Indian cities, significant differences
appear at the top of the hierarchy and for cities with more than one million inhabitants. The
rank-size curve obtained with the projections based on the trajectory class growth rate is more
regular than that obtained with an identical growth rate (Table 1). While the three largest
metropolises follow more individualised paths each benefitting from its own earlier evolution,
secondary metropolises are catching up with them, reducing the gap between the two groups
at the top of the hierarchy.
5.3 Comparison with UN projections
Besides projecting the total urban Indian population until 2050, the UN in its “World
Urbanization Prospects 2011 Revision”, establishes population figures and growth rates from
2009 until 2025 only for cities with more than 750,000 inhabitants. Because of its focus on
the growth of big cities, UN has a tendency to underestimate the expansion of the whole city-
system. UN’s projections are very close to those obtained when we apply the same growth
rate to all cities.
It forecasts an urbanization rate in India of only 51.7% in 2050, while we obtain 55.9%.
Diffusion of growth within the city-system and its expansion appear under estimated by UN's
method. We predict more than 925 million Indians living in urban agglomerations in 2050
(Table 2); it is equivalent to the India’s entire population in 1993.The urban population will at
least double in 2050 from its value in 2011.
The major socio-economic challenge confronting the Indian government would be to generate
the infrastructure needed to accommodate about 484 million additional urban dwellers. In
2001, the urban population occupied 54,366 km
of continuous built up area which was
already one of the densest urban environments in the world with 8,100 inhabitants per square
kilometre. The cities will necessarily claim a larger share of the land for expansion until 2050
even if the regulation on Floor Space Index (FSI) is relaxed.
Table 2: Expected populations and urbanization rates until 2050 and their distribution
by city size class (growth rates segmented according to the trajectories of the period
Million Plus city
> 100,000
100,000 to 10,000
Total urban 441,144,573 537,846,781 658,852,416 791,403,475 925,264,993
Total India
Rate of urbanization
In %
Million Plus city
> 100,000
100,000 to 10,000
Total urban 100.0 100.0 100.0 100.0 100.0
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29 April 2013
In 2050, the number of Million Plus agglomerations will be 89, double the number in 2011.
Numerous towns with less than 100,000 inhabitants will accommodate 339 million people in
all. In a complementary development, India's city-system will continue to expand with the
emergence of new agglomerations and the growth of its largest cities.
In order to forecast India’s urban future, we assumed that secular and contemporary growth
trajectories of all individual urban agglomerations are key drivers of future urbanization
Our projection is firmly grounded on two diachronic databases, and takes into account the
individual trajectories of all the urban agglomerations existing in 2011 and the new
agglomerations likely to emerge until 2050.
We demonstrated that India's city-system conforms to the distributed growth model and that
its hierarchical distribution is evolving regularly. As seen in the rank-size distribution over
successive periods of time, growth of towns and urban agglomerations has been always well
distributed, for more than a century. India's plurisecular city-system fits well with the
canonical model that describes universally the system dynamics and shares common
characteristics with several mature urban structures around the world. We have also shown
that the location of the town has little influence on its growth trajectory. Individual trajectories
can be classified, without the loss of too much information, either by the secular trend of
towns (1901-2011) or on the basis of the more recent genesis of the contemporary urban
agglomerations landscape (1961 to 2011). These classifications are structured over time and
space according to subsystems and regional specificities (for instance, inland cities are
growing faster than coastal towns).
In less than thirty years, half of India’s population will have to cope with urban life and there
will be tremendous transformation of landscape, economic structure and social life.
Development of infrastructure in keeping with the pace of demographic urban growth is a
major concern for India. In 2050, urban India will be home to almost fourteen per cent of the
world’s urban population. The sustainability of India’s city-system has thus already become a
global challenge as well.
R. Bhagat, Urban growth by city and town-size in India, Annual meeting of Population
Association of America, Philadelphia, USA, March 31th – April 2, 2005.
P. Bocquier, World urbanization prospects: an alternative to the UN model of projection
compatible with urban transition theory. Paris, DIAL, working paper (2004)
A. Bretagnolle, E. Daudé, D. Pumain, From theory to modeling: urban systems as complex
systems, Cybergeo, European Journal of Geography, 335 (2006).
A. Bretagnolle, D. Pumain, C. Vacchiani-Marcuzzo, The Organization of Urban Systems”,
in : D. Lane, D. Pumain, S. Van der Leeuw, G. West (eds.), Complexity perspectives on
innovation and social change, ISCOM, Berlin: Springer, Methodos Series, (2009) 197-220.
Draft Paper: not to be quoted without authors' permission
29 April 2013
S. Chandrasekhar, Migration and Urbanization: A case-study of India, in B. Deborah, M.
Mark (eds.), Projecting the Urban Future: New Methods and Data for Developing Countries,
Springer (2010)
B. Cohen, Urban Growth in Developing Countries: A Review of Current Trends and a
Caution Regarding Existing Forecasts, World Development. 32, 1, (2004) 23-51.
K. Davis, Urbanization in India: Past and Future, in R. Turner (ed.) India's Urban Future,
University of California Press. (1962) 3-27.
E. Denis, K. Marius-Gnanou, Toward a better appraisal of urbanization in India, Cybergeo,
European Journal of Geography, 569 (2011).
G. Hugo, A. Champion (Eds.) New Forms of Urbanisation. Aldershot: Ashgate, 2003.
F. Moriconi-Ebrard, L'urbanisation du Monde. Paris: Anthropos, 1993.
F. Moriconi-Ebrard, Geopolis - Pour Comparer les Villes du Monde, Paris: Anthropos, 1994.
F. Landy, L’Union Indienne, Paris: Editions du Temps, 2002.
K. C. Pradhan, Unacknowledged Urbanization: The new census towns of India, New Delhi,
Centre for Policy Research, Working paper, 2012.
D. Pumain, La dynamique des villes, Paris : Economica, 1982.
D. Pumain, Pour une théorie évolutive des villes, L’Espace Géographique. 26, 2, (1997) 119-
D. Pumain, Alternative explanations of hierarchical differentiation in urban systems, Chapter
7 in D. Pumain (Ed). Hierarchy in natural and social sciences, Springer. Methodos series 3
(2006) 169-222.
R. Ramachandran , Urbanization and Urban Systems in India, Oxford university Press, 1989.
A. Rogers, Sources of Urban Population Growth and Urbanization, 1950-2000: A
Demographic Accounting, Economic Development and Cultural Change. 30, 3 (1982) 483-
A. Schaffar A., M. Dimou, Rank-size City Dynamics in China and India, 1981–2004,
Regional Studies. 46, 6 (2012) 707-721.
S. Sharma, Persistence and stability in city growth”. Journal of Urban Economics. 53 (2003)
A. Shaw, Emerging Patterns of Urban Growth in India, Economic and Political Weekly. 34,
16/17 (1999) 969-978.
Draft Paper: not to be quoted without authors' permission
29 April 2013
KC. Sivaramakrishnan et al., The future of urbanization, spread and shape in selected states.
Centre for Policy Research, New Delhi, 2001.
KC. Sivaramakrishnan, A. Kundu, BN. Singh, Handbook of Urbanization in India. New
Delhi: Oxford. UniversityPress, 2005.
E. Swerts, Construction de bases de données harmonisées pour comparer l’évolution des
systèmes de villes en Chine et en Inde. PhD Thesis under the supervision of D. Pumain,
Université Paris 1 Panthéon-Sorbonne, 2013.
E. Swerts, D. Pumain, Approche statistique de la cohésion territoriale : le système des villes
en Inde, L’Espace Géographique, 1 (2013) 77-92.
UN, World Urbanization prospect: the 2011 revision. (2012)
World Bank, Global Economic Prospects and the Developing Countries 2004. Washington,
D.C.: World Bank, 2003.
W. Zelinsky, The Impasse in Migration Theory: A Sketch Map for Potential Escapees, in P.
A. Morrison (Ed.), Population Movements : Their Forms and Functions in Urbanization and
Development. Liège: Ordina - IUSSP, (1983) 19-46.
... Sustainability 2019, 11, 485 ...
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This novel study explores the driving forces and dynamics of rapid urbanization, highlighting the main causes and effects of urban explosion, environmental disruption, and city pattern transformation. This study was carried out that how urbanization and urban sprawl have influenced the structure of the city of Sulaymaniah in Kurdistan region of Iraq. This is because over the years many urban areas have experienced dramatic growth and population explosion that has resulted in the exhaustion of social amenities in the concerned communities. For this purpose, a qualitative method is used based on in-depth face-to-face interviews with local authority, including planners, architects, and experts of master planning, as well as professors in the academic institutions. This study also utilizes extensive document analysis to present the evolution of urban growth. The findings reveal that the autonomy, political conflict, non-implementation of master plans, and economic prosperity are the driving forces which are accelerating this urbanization process. It is proposed that the practical policies and strategic urban development plans are urgent requirement to control the unplanned urban growth and stimulate the desired sustainable future urban development.
... The country has more than 31.2% of the total population living in 7935 towns/cities (census 2011). It is estimated by 2050, India will house 14% of the world's urban population in its cities causing a major landscape modification (Swerts et al. 2014). The existing urban landscape is becoming over-stressed and populous causing the spill over in suburban and rural hinterlands bringing about change in the land use and land cover pattern. ...
Solid waste management is a significant aspect of urban services and environmental sustainability. In the past, enormous land masses made trash disposal easy, but today’s growing population, changing lifestyle, technological advancements, and fast urbanization make it harder. Solid waste management is crucial for a healthy and vibrant society. In this paper, attempts have been made to analyze the solid waste management scenario of Raiganj municipality using geospatial technology in terms of solid waste generation, collection, transportation, and disposal. All necessary information was gathered from both primary and secondary sources. These included field research, interviews, and municipal data collection. Data were evaluated statistically and qualitatively using Arc GIS 10.2.1, Microsoft Office Excel, and Microsoft Office Publisher. The cartographic maps were used to analyze the data. The findings of this investigation show that Raiganj’s present waste management system cannot handle the growing number of urban residents. This city has growing challenges with solid waste collection, treatment, and disposal. The unavailability of scientific landfill sites hinders Raiganj’s welfare. Solid waste management in the Raiganj Municipal area needed to be improved. The ramifications of prospective solutions for municipal solid waste (MSW) at the centralized and decentralized level must be emphasized via the conjunct initiative of different scientific treatment procedures. As a result, municipalities, in collaboration with the informal sector and commercial organizations, must concentrate on developing potential prospects to fulfill the long-term aim of municipal solid waste management (MSWM) sustainability for this municipality.
... Population growth around 2050 is likely to result in doubling of population in Africa and an increase of 25% in south Asia (United Nations, 2014). In south Asia, urbanization may increase in 2050, but in Africa the opposite may be true with rural areas becoming more densely populated (Swerts et al., 2014, Racki et al., 2014. More than 90% of the global 500 million MT of rice is produced and consumed in Asia (FAO) which is produced from 30% of the total arable land of this region. ...
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In recent years there is discussion regarding nexus between agricultural trade and environment and shared responsibility in addressing trade related environmental externalities. In the current study, this nexus is examined focusing on rice exports from India in the recent decade. India’s share in quantity of world rice exports was 22.45 per cent on an average in the decade 2010-2019. However, in the same period India’s share in water footprint of world rice exports was 28.29 per cent. Further average economic productivity of water in rice exports was 0.24 and 0.22 USD/ M3 in the case of World and India, respectively. The estimated methane emission associated with Indian rice exports ranged between 2.42 to 11.31 per cent of total methane emission from rice production. Totally, 47 countries were involved as top 5 destinations of different types of rice exports from India. Land scarcity, water scarcity, water availability for agriculture, agricultural trade policies in these countries were the underlying factors of the observed rice export pattern of India. Out of these 47 trade partners, in 27 countries, methane emission intensity in paddy was higher than that of India in 2017, but paddy area was lower compared to India. Several national level and international level policy options are available for handling the environmental externalities associated with rice exports from India.
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Urbanization has become a universal phenomenon in the contemporary world and is characterised as the key determinant of social transformation. It is responsible for both development and apprehensions to the concerned space. Urban places have remained the desired location for millions of people residing in the countryside owing to progression opportunities and superior health, education and livelihood facilities. Apart from assuring qualitative life to residents directly, urban centers also contribute to the economic pool of the nation through skill and capital generation. The nation's prosperity and advancement are substantially designed and geared by the level of its urbanization and vice-versa. The present chapter attempts to explain the level of urbanization and its nature in Haryana state over a period. The evaluation of secondary data and information reveals that liberal industrialization policies of the government have augmented the urban process and modified the towns’ size. The significant share of geographical space with the national capital region also supported the urbanization in the state. The state's current urbanization ratio (34.88%) is higher than the nation’s (31.16%) average. Another finding reveals that compared to western and south-western districts of the state, northern and eastern belts are more urbanised due to some extra advantages. There is a need for a decentralized approach regarding establishing economic activities and developing necessary infrastructure in less urbanised areas to get balanced and sustainable urban growth in the state.KeywordsUrbanizationDeterminantTransformationApprehensionLivelihoodQualitative lifeIndustrialisationTowns
Urban Heat Island, the phenomenon synonymous with urbanization and change in local climate, is a grave threat to the energy balance and resources of a city. This paper presents a study of one of the fastest-growing satellite towns of Delhi, Gurugram, using remote sensing techniques to establish if the fast pace of urban expansion influenced air and surface temperatures. The temperature trends were studied using remote sensing and ArcGIS software. Satellite images for the years 2000 (Landsat 7 ETM+), 2010 (Landsat 5, TM) and 2019 (Landsat 8, OLI/TIRS) were downloaded and analyzed for LST ArcGIS using the mono-window algorithm. The year 2019 revealed a maximum LST of 47.68 °C for June in comparison with an LST of 44.8 °C for June 2010 and 40.4 °C for May 2000. The city’s temporal and spatial changes over the past decades (2000–2019) were studied by the technique of change detection. To study land use and land cover changes, supervised classification using ERDAS was done. The supervised classification (maximum likelihood classifier) has been used to identify the five major categories of LULC for the period years 2000, 2010 and 2019. The study found that since 2000, the city’s most abundant resource of agricultural land 2000 saw a sharp decline of 60% in 2019. This seems to be utilized by the urban built-up because the urban areas also saw an increment of more than 62% for the same time frame. The classification had accuracy of 96.67%, 94% and 86.67% for the years 2000, 2010 and 2019, respectively. Studies involving LULC classification are important because they represent how human activities are modifying ecology. The classification helped establish that the agricultural areas of Gurugram are on a rapid decline, whereas urban built-up areas have significantly doubled in the past two decades. The study helps in understanding the impacts of urbanization patterns for a fast-expanding metropolis and the possible interventions to be made by urban planners and policy managers to prevent further aggravation of UHI and plan mitigation strategies.
Cities are experiencing continuous growth in population and must straddle a delicate balance between nurturing nature and providing livelihood. In that context, the contemporary urban agenda of sustainability must find creative ways of meeting global environmental expectations and resolving issues of displacement and rehabilitation of the poor. First, I use Marx’s concept of species being and estrangement to understand how sustainability discourses commodify and externalize urban nature as “environment,” estranging urban citizens from a deep sensuous connection with nature. Second, I use Marx’s species being to demonstrate how globalization-induced displacement estranges labor from itself and spaces in which labor produces existence. I provide two empirical moments, green city-New Town, Kolkata and the globalizing city-Ahmedabad in India to explore how urban policy fails to fundamentally alter nature–society relationship or eradicate estrangement of labor from itself, labor from nature, and nature from itself. This article argues that cities are caught up in a nature–society paradox that puts society in contradiction with nature.
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Rapid urbanization has the potential to improve wellbeing of societies. Yet it also presents many human development challenges. Hence Urbanization is always not positive specially if it is unplanned. Existing urban cities in the country are facing tremendous pressure on livelihood and infrastructure facilities as a result of rapid urbanization. There is a need to evaluate potential of class II and class III cities as future urban centers. Objectives of particular research focus to understand the impact of urbanization in cities concerning the quality of life of people. To study the social, economic and political impact on the development. To understand the existing policy framework and various stakeholders in cities affecting the factors of livability standards. Aims majorly to understand the gaps between the expected and present status of livability standards. Study will be carried out step wise starting with identification of research area, understanding existing development and sprawl. It will focus on understanding city and area specific issues impacting cities regarding urbanization. Study will be carried out through primary surveys & interviews and secondary data sources. Research will primarily talk about various aspects of inclusive city planning and sustainable development along with a good quality of life.
The IoT services composition is a complex task, where the necessary services choice and the handsets in the proper order as an integrated composite service is the main challenge in a highly constrained environment. The services composition has been the subject of research in several academic works where the authors try to find the best way to combine and compose the services in an optimal way. In this paper we examine the composition mechanism of IoT services, by focusing on QoS-aware approaches, by a comparative study of some proposed approaches in the literature.KeywordsServices compositionIoTInternet of ThingsQuality of serviceQoS
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The unexpected increase in the number of census towns in the last census has thrust them into the spotlight. The new CTs account for almost 30% of the urban growth in the last decade. The estimated contribution of migration is similar to that in previous intercensal periods. Further, the data indicates a dispersed pattern of in situ-urbanisation, with the reluctance of state policy to recognise new statutory towns partly responsible for the growth of new CTs . A growing share of India’s urban population, living in these CTs , is being governed under the rural administrative framework, despite very different demographic and economic characteristics, which may affect their future growth.
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A study of investment in India's metropolitan cities (cities with million-plus population) and their neighbourhoods during the nineties indicates the emergence of urban cores of high investment and the virtual bypassing of the remaining metropolises by liberalisation-fostered growth. As the growth patterns of the 23 metropolises tend to reflect the state of the economies of their respective regions, this bespeaks the widening of interregional economic disparities.
Chapter 1: Rationale, Terminology, Scope.- Chapter 2: Fundamental of Population Analysis.- Chapter 3: Overview of the Cohort-Component Method.- Chapter 4: Mortality.- Chapter 5: fertility.- Chapter 6: Migration.- Chapter 7: Implementing the Cohort-Component Method.- Chapter 8: Extrapolation Methods.- Chapter 9: Structural and Microsimulation Models.- Chapter 10: Special Adjustments.- Chapter 11: Related Projections.- Chapter 12: Evaluating Projections.- Chapter 13 Forecast Accuracy and Bias.- Chapter 14: A Practical Guide to Small-Area Projections.- Epilogues: Some Final Thoughts.- Glossary.- Index.
L’Inde a une histoire riche et ancienne, caracterisee par l’avenement successif de royaumes et de civilisations urbaines et par la succession de decompositions et de recompositions politiques et territoriales au cours du xxe siecle. Du point de vue de la dynamique des systemes de villes, le territoire indien pose ainsi la question du degre d’integration d’un ensemble de villes. Cet article montre que l’on observe a la fois une unite du systeme de villes indien, qui se traduit par un processus de croissance distribuee homogene depuis plus d’un siecle, et une diversite regionale revelee par l’heterogeneite d’une region a l’autre des degres d’inegalite de la taille des villes et de leurs rythmes de croissance.
Statistical approach to territorial cohesion: The system of cities in India. India has a rich and ancient history, characterized by the advent of successive kingdoms and urban civilizations and the succession of political and territorial decomposition and recomposition during the 20th century. From the point of view of the dynamics of the city system, Indian territory raises the question of the degree of integration of a set of cities. This article shows that there is both a unity of the Indian city system, characterized by a homogeneous distributed growth process for more than a century, as well as a regional diversity, revealed by the heterogeneity from one region to another of the degree of inequality with respect to the size of the cities and their growth rates.
Urban theories and especially urban economic theories adopt a static conception of cities (for instance central place theory or agglomeration economies theory). As a result their explanation of the urban phenomena neglect their genesis and urban change. Therefore, possibilities of prediction are reduced. To deal with cities which are complex objects, urban theory has to integrate dynamics and history. We propose here the premisses of an urban evolutionary theory, including self-organization processes. A few elements of this theory can be borrowed from dynamic models inspired by physical or biological theories of self-organization, but they have to be complemented by some specific social and spatial properties of urban systems.
Les theories urbaines, en particulier economiques, reposent pour la plupart sur une conception statique de la ville (par exemple, la theorie des lieux centraux, ou la theorie des economies d'agglomeration), ce qui conduit a des explications du fait urbain qui ne prennent pas en compte la genese ni le changement, et donc reduit la pertinence des previsions. Pour traiter des villes, qui sont des objets complexes, la theorie urbaine doit integrer des aspects temporels, non seulement au sens de la dynamique, mais aussi du devenir, de l'histoire. Nous proposons ici les premisses d'une theorie evolutive des systemes de villes. Quelques elements de cette theorie peuvent etre empruntes aux modeles dynamiques d'auto-organisation inspires des theories des systemes physiques ou vivants, mais il faut y ajouter des proprietes, spatiales et sociales, specifiques des systemes urbains.