Urban growth in developing countries like India is very rapid than the other developed countries in the world. In India, huge increase of population and unplanned urban growth in the fringes of the metropolitan cities are the major reason behind the origin of city externalities. Basically city externality is a part of urban planning and management. Concerning authorities responsible for the planning of those areas has been taken many steps for the proper planning and management of the area, but it is inadequate to solve the problem. Kolkata city is now growing towards the southward direction as it has been seen through the analysis of satellite images. Availability of vacant land with low prices has been accelerated urban growth in the southern part of Kolkata Metropolitan area.
The rate of population growth is very high in case of developing countries rather than the developed countries. In 1950, 30 percent of the world population was urban area but in 2050, 66 percent of the population is projected to be urban area (United Nations, 2014). In the last decade, most of the cities in the world have experienced high growth rate of population among them most of the cities are from the developing countries which is characterized by the rapid transformation of land use/land cover (i.e. from rural or semi urban areas to urban areas). (Yu & Qingyun, 2011). This rural to urban transformation is mainly because of increase in population and huge economic and infrastructural development which leads to change in socio economic environment of the city (Bounoua, 2009). Recently urban area occupies only 3 percent of the Earth’s total land surface, but it have marked effects on environmental conditions at both local, regional and also in global scales (Herold, et al., 2003; Liu and Lathorp, 2002).
The transformation of rural or semi urban areas to urban areas through the process of urbanization is now a day’s occurring at an unprecedented rate which affected on the natural functioning ecosystems of the city (Turner, 1994). Transformation of the agricultural areas to the urban areas may create different problems like land degradation and desertification (Shalaby et al., 2004). This is the causes behind the city externalities.
Urbanization, Urban Growth and City Externalities
Urbanization is an important characteristic in case of every metropolitan region around the world. Urbanization can be defined as the conversion of rural or semi urban areas to urban areas (Antrop, 2000) (Burgi, et al., 2004) (Pickett, et al., 2001). Rapid urbanization especially in the metropolitan cities of the developed countries often causes enormous pressure on physical and socio-economic environments of the area.
Urbanization is also one of the dynamic processes which are mainly induced by the human activities but it is also responsible for the loss of agricultural land (Lopez et al. 2001). It leads to urban growth. But the spatial pattern of urban growth is a consequence of the interaction between the various physical and socio-economic factors (Burgi et al. 2004). Different factors like topography, population, land use land cover types, infrastructural development of an urban area impacted on the morphology, which leads into different types of urban growth. Urban growth is mainly the conversion of semi urban or rural area to commercial area. It is also related with the regional economic sustainability of an area. Its benefits are increasingly balanced against the environmental and ecological impacts, which are also affected on the air quality and water quality with the loss of agricultural tracts of an area. It also affected the socio economic condition of an area which leads into regional disparities, social fragmentation etc. (Squires, 2002).
Due to the huge urbanization process in Kolkata city different problems has originated, but this research work will deal be dealt particularly with one of the related issues of urbanization i.e. city externalities. The research questions will center on few questions which are as follows:
What are the present trend of demographic growth, nature and pattern of land use land cover change in the Kolkata Metropolitan Area.
What are the possibilities of urbanization in the rural areas of Kolkata metropolitan area and in which direction will the mean center of population shifted in recent periods?
What are the differences of growth in the South Eastern and South Western Part of Kolkata Metropolitan Area.
What are the changes in land use, socio economic and transport externalities due to southward expansion of Kolkata city.
The rate of population growth is very high in developing countries rather than the developed countries. Developing countries like India are often characterized by rapid land use and land cover change, land degradation, or the transformation of agricultural areas to built up area which affects on the environment. Among the metro cities in India, Kolkata is one of the cities where rapid urbanization has been taken place from 1980s. In Kolkata urban growth is mainly haphazard or unplanned and it is now growing towards the southward direction along the major road as it has seen by the analysis of satellite images. This huge unplanned growth gives birth to city externalities. The research problem is mainly centered on the shifting of the city externalities due to urban growth towards the city fringe areas.
1.4. Research Objectives
In recent decades the expansion of Kolkata city is towards the southern direction as it has been seen through the analysis of concentration of population, population growth rate and classification of satellite imageries. Because of the availability of vacant land with low prices, extension of metro railway to the New Garia and Joka area are the major causes behind this southward expansion. Expansion towards the fringe areas leads to city externalities. The objectives of the study are as follows
To analyze the trends of demographic growth, nature and patterns of land use and land cover change within Kolkata Metropolitan Area between the years 1980 to 2015.
To find out the possibilities of urbanization in and around Kolkata city with the shift in mean center of population.
To identify the differential growth pattern with the emerging externalities in south eastern and south western part of Kolkata Metropolitan Area.
1.5. Study Area
Kolkata city is now growing towards semi urban areas in the southward direction. These give birth to five municipalities in the southern fringe of Kolkata. Among the five municipalities, two municipalities are located on the south eastern part of Kolkata Metropolitan Area i.e. Rajpur Sonarpur Municipality and Baruipur Municipality. Other three municipalities are located on the south western part of Kolkata Metropolitan Area. Among the five municipalities, four municipalities Rajpur Sonarpur Municipality (south eastern part of KMA), Maheshtala Municipality, Budge Budge Municipality and Pujali Municipality (south western part of KMA) have been considered as the areas of study. Those are as followings
Rajpur Sonarpur Municipality comprises of 37 mouzas namely Ukhila-Paikpara, Kumrakhali, Sonarpur, Ghasiara, Boral, Rania, Paschim- Nishintapur, , Kodalia, Rajpur,Malancha, Nischintapur, Chak-Harinavi, Manikpur, Balia, Gorkhara, Kamrabad,Noapara, Tegharia, Chowhati, Jagannathpur, Harinavi, Mahinagar, Jagaddal, Dhamaitala, Mallikapur, Kusumba, Garagachha, Lashkarpur, Sripur-BagherGhola, Baikunthapur, Bansidharpur, Ellachi, Barhans-Fartabad, Kandarpapur-Boalia, Tentulberia, Dhalua, Panchapota. This municipality is one of the largest municipalities in West Bengal comprising 35 wards with a growth rate of 26.03 percent according to census, 2011. It is bounded to the north by Kolkata Municipal Corporation (i.e. KMC), to the south by Baruipur Community Development Block (C.D.) and to the east as well as to the west by the Sonarpur Community Development Block.
Maheshtala Municipality of the South 24 Parganas district is a newly developed area. The name ‘Maheshtala’ has been named after the name of ‘Mahesh Suri’ who was collecting tax from this area in favour of Sri Ramakanta Banerjee who was originally in charge of collecting tax as appointed by Lord Clive, the then British Ruler. Being transformed from the Panchayat (containing 21 nos. of Gram Panchayats and 40 nos. of partial and total Mouzas ) in 1993, vide Govt. Notification No.- 368/C-4/MM-353/92 dated 30.06.93,Maheshtala Municipality has emerged as the second largest municipalities in West Bengal (Maheshtala Municipality, 2018). At present the municipality is divided into 35 wards and it is thickly populated with 95579 nos. of house holdings and 463 nos. of manufacturing units. The population of this municipality is 4.48 lakhs, 44.18 square kilometer area with the population density of 10,148 persons per sq.km comprising 35 wards. Beside the river Hooghly, along the Sealdah-Budge Budge railway tracks, the major road namely Budge Budge Trunk Road are present in this area since the British period. Because of the adjacency of Budge Budge area both for the trading and manufacturing purposes probability of future expansion of this municipal area is very high. This municipality is surrounded in the northern and eastern side by KMC, in the southern side by Thakurpukur-Maheshtala C.D.block and on the west by river Hooghly.
Budge Budge municipality was established in 1900 in the district of South 24 Parganas. This municipality is the entrance of the rural areas of Bengal and it is also the terminal station of local train services to Kolkata. This municipality is located in an advantageous position because of the accessibility through the rail, road and water transport system. This municipality is surrounded in the northern side by river Hooghly and Maheshtala municipality, in the southern side by Budge Budge I CD Block on the eastern side by Uttar Raipur Gram Panchayat and on the west by Pujali municipality.
Pujali municipality is the smallest municipality located in the southwestern part of KMA. It is situated in the east bank of river Hooghly and at the north-west portion of the South 24 Parganas district. Present area of this municipality is 8.32 square kilometer, with the population density of 4452 persons per sq. km. Total number of wards in this municipality is 15. This municipality is the one of the smallest municipalities in West Bengal. It is bounded to the west by Hooghly river, eastern side by the Budge Budge I C.D. Block, north by Budge Budge municipality and to the south by Bishnupur Community Development (C.D.) block of South 24 Parganas district.
Table 1.1 Overview of Study Area
Name of the Municipality Rajpur- Sonarpur Municipality Maheshtala Municipality Budge Budge Municipality Pujali
Location South Eastern part of KMA South Western part of KMA
Area 49.26 44.18 9.06 8.32
Population in 2011 Census 424368 448317 76837 37047
Number of Wards 35 35 20 15
Population Density(Sq. Km) 8615 10148 8481 4452
Growth Rate from 2001-2011 26.03 16.37 1.73 9.42
Source: Census of India, 2011
Fig 1.1 Study Area
1.6. Logic behind chosen this topic
Kolkata is unplanned city comparatively with the other metro cities in India. After computing various report of Census of India it has been found that the demographic growths in the southern part of the Kolkata Metropolitan Area are increasing with the time. Urban expansion and city growth in the southern part of Kolkata Metropolitan Area (KMA) is more dynamic than the other parts of KMA. More minute observation it has been seen that Kolkata is now expanding towards south east direction and south west direction from the city core area. The process of urban growth is very rapid after the 1980s. Though south eastern portion (for e.g. Rajpur-Sonarpur, Baruipur, Garia) have developed between the last two decades i.e. 1980 to 2000. But in recent decades urban growth towards the south western portion of Kolkata city (i.e. Maheshtala, Pujali, Budge Budge area) is very much intensive than the south eastern portion. So this topic has been selected as an area of research.
1.7. Review of Literature
A critical review of literature is important to find out how much work has been done in the selected area of research, what are the research gaps and to decide in which direction further work can be done.
Urbanization has become a global phenomenon. Over the past 30 years, the populations of urban areas have increased a lot, and urban land has rapidly expanded towards semi urban areas which are mainly driven by spatial expansion of cities. Spatial expansion is a process of changes in urban size, urban morphology, urban form and various other aspects within a certain period of time.
Urbanization is the most important process and the process of urbanization can be clearly seen through the process of land use and land cover change. Conversion of non built up area to built up area is the major land use change categories due to urbanization. Urban growth is related with the socio-economic development of the region by improving quality of life (i.e. positive externality), but it has also often caused various problems like congestion, pollution (i.e.Negative externalities).
Concept of Urbanization and Urban Growth
Global urban pattern is changing in three main ways as a result of urbanization, urban growth and urbanism. Urbanization is when certain settlements grow at the cost of their surrounding countryside and Urbanism is the extension of the social and behavioural characteristics of urban living across society as a whole. (Pacione, 2009).
According to Clarke (1982) urban growth is a spatial and demographic process which refers the increase in the importance of towns and cities as a consequence of huge concentration of population in a particular economy and society.
Urbanization can be measured in a number of different ways. The first is to examine the changes in the level of urbanization, secondly by measuring the ‘urban-rural growth differential’ (URGD) and lastly by measuring growth of urban population itself (Mohan and Pant, 1982).
Concept of City Externalities
In light of the recent trend for decentralized urban development, researchers are contemplating alternatives to decentralized urban growth because of its negative externalities. Although outward urban growth possesses both good and bad effects (Cieslewicz, 2002; Benfield et al., 1999; Lucy and Phillips, 2006; Jargowsky, 2002; Squires, 2002; Kahn, 2006; Wassmer, 2001). Good effects create positive externalities of the city and vice versa.
Causes of Externalities
Interdependence between economic agents- Activity of one person affects the utility or production of other.
Lack of or weak property rights- Because of lack of property rights affected party is unable to demand or ask about the compensation for the damage i.e. the effect of externality.
High transaction costs- The cost of negotiation, implementation and enforcement between the parties may be high (Asafar, 2000), (Titenberg, 2001).
Types of Externalities
Relevant Externalities- An externality is relevant until the affected person is indifferent to it. It will become relevant when the affected person is suffering by the activity and wants the offending person to reduce the level of the activity (Asafar, 2000), (Titenberg, 2001).
Pareto Relevant Externalities- A Pareto relevant externality exists whenever its removal results in a pareto movement. It means that the when the level of an externality is optimal, it becomes pareto irrelevant (Asafar, 2000), (Titenberg, 2001).
Static and Dynamic Externalities- Static externalities explain the formation of cities and degree of specialization with in cities rather than city growth (Henderson, 1997). Traditional local externalities are associated with the extent of localization and urbanization. Positive externalities in relation to both of these characteristics suggest that bigger cities give rise to greater benefits. By contrast the generation of negative externalities, such as congestion and commuting costs, suggest the existence of an optimal city size (Henderson 1974, 1997).
These external impacts can be either detrimental or beneficial to the society at large. Those which impose a cost on the external movement are called a negative externality and those which confer benefits on it are called positive externality (Natarajan, 2007). External effects can be either positive or negative. However external effects often negative. Examples of negative externalities are air, water and noise pollution. A positive externality (external economy or external benefit) occurs when the effect is benefitted to the affected person (Asafar, 2000) (Titenberg, 2001).
Dynamic externalities are related with the impact of the accumulation of prior information on the current productivity to explain the city growth (Chen, 2002). There are three types of theories related with the dynamic externalities namely, the Marshall-Arrow-Romer externalities (MAR), Porter (1990) and Jacobs (1969) theories (Glaeser et al. (1992).
Pecuniary Externalities- A pecuniary externality occurs when the externality is passing through the higher prices or reduced costs (Adjaye, 2000), (Titenberg, 2001).
Cities are a centre of socio-economic interplay, human confrontation, political dialectics, and birth places of civilization, centers of science and art, and a melting pot of cultures (Verhoef and Nijkamp, 2003). According to Jane Jacobs (1969), cities generate economic growth inter aila from the disordered order of human interaction. In the urban economics the concept of agglomeration advantage means that a spatial clustering of economic activities which leads to various types of economics of scale. Sometimes a distinction is made into localization advantages, urbanization advantages, scale advantages, urban externalities and the like (Verhoef and Nijkamp, 2003).
An increase in population increase aggregate demand and enables firms to expand output without efficiency or productivity improvements. In this respect, scale and density are interrelated but not identical. A greater scale of activity may be accommodated by increasing urban sprawl at constant density, while alternatively the current tendency for a return of knowledge workers to the inner city may increase urban core density without changing scale. Scale and density effects may be referred to as urbanization externalities (Henri et al. 2008).
Urban growth could occur in either coordinated or uncoordinated manner. The distinction is usually based on whether the urban growth results in severe negative externalities, such as a shortage of new facilities in locations where growth is taking place (Batty et al. 2002). Batty et al. (2002) proposed several types of generic measures to detect the different spatial, physical and geographical configurations of urban growth: density, configuration, accessibility, construction, negative physical externalities, negative economic externalities and social benefits and costs. These measures make examining and estimating the effects of sprawl on cities possible.
Planners and decision makers prefer to underestimate the power of urbanization economies and overestimate the urban sicknesses resulting from spatial agglomeration. Urban economists believe that urbanization economies generate positive and negative externalities. Whereas positive externalities are the driving force of urban growth, negative externalities cause urban decay. Whether cities grow or decay depends on the competition of these two kinds of externalities. In theory, when the negative externalities are greater than the positive, city sizes will shrink and urban decay will begin (Zhen, 2013).
There must be a point in the future, after cities have undergone long term persistent growth, at which the growth will stop and begin to decrease. This turning point has unfortunately not arrived. Little evidence has emerged to show that urban decay occurs due to the extreme growth driven by agglomeration economies thus far. In contrast, much evidence has shown that urban decay is usually caused by industrial structure adjustments (Zhen, 2013).
From the national and regional perspectives, urban growth estimations must consider both endogenous and exogenous development pressures and demands. In megacities and central cities, growth size has generally been influenced more considerably by exogenous demands. The challenge of spatial planning is how to organize large amounts of urban growth due to regional aggregation, not how to decentralize a so called “crowded” city center. However, whether a city center is too crowded to function healthily depends not on common sense, but competitions between the positive and negative externalities (Zhen, 2013).
Squires (2002) emphasized that “smart growth” should be proposed as an alternative to decentralized urban sprawl in local jurisdictions. Smart growth principles seek to use existing resources efficiently and also to allocate them more equitably. Based on this notion, Squires (2002) outlined eight remedies to offset negative externalities of the decentralized outward urban growth
Reusing existing land and infrastructure resources;
Restricting development in outlying suburban and exurban areas;
Relying less on the automobile by developing a number of transportation alternatives;
Concentrating residential and commercial development centrally and along mass transit
Devoting more money to area-wide revenue sharing and regional investment pools;
Constructing more affordable housing and distributing it throughout metropolitan areas;
Enforcing more vigorously fair housing laws; and
Increasing public and private investments in central cities for more balanced development throughout the region.
Downs (1994) proposed five components of visions to address the negative outcomes of decentralized outward urban growth, which include ownership of detached, single-family homes; ownership of private automotive vehicles; employment in scattered, low-density workplaces, themselves in landscaped settings with free parking; living in small communities with strong local governments; and provision of housing to the urban poor through a “trickle-down” neighborhood change process (Downs, 1994).
Externalities of Land use
Land produces multiple services for society and it is also an input in various production activities, by providing food, housing etc. Using land to provide one service directly affects the availability of land for providing other services; it may also indirectly affect the capacity of land to provide other services via the external effects that each land use may generate. The external effects, referred to as externalities (Karpankar, 2008). Vreeker (2004) proposed the advantages and disadvantages of mixed and compact land uses, where advantages indicates the positive externalities of land use and disadvantages indicate the negative externalities of the land use. Irwin and Bockstael, 2004 proposed different policies to reduce the land use externalities, open space conservation and urban sprawl. It is related with the environmental externalities also.
Externalities on Socio-Economic Perspectives
Socio economic externality means the impact of city externalities on the socio economic condition of the area. In this study the impact of urban growth on the socio economic condition of the people has been considered. Due to the urbanization the change in occupation, change in the employment opportunities, change in educational opportunities etc. termed as positive externalities of urban growth on socio economic perspectives, whereas due to the unplanned urban growth the problem of water logging, sanitation has been termed as negative externalities of urban growth.
Externalities of Transport
The externality of transport means the change in the transport condition due to the impact of urban growth. When due to the urban growth mode of the transport increases it indicates the positive externalities of transport, but when due to the urban growth traffic congestion, pollution etc. increases, it indicates negative externalities of transport. Holocombe and Williams (2003) conducted a study on the costs and benefits of urban sprawl on the transportation services. Borger and Proost (2013) developed different model to reduce the various traffic externalities like congestion, pollution etc.
Similar Studies at International Level
Harvey and Clark (1965) and Ewing (1997) described urban sprawl as a pattern to understand the spatial distribution of the city. It is very much related with the urban growth process. According to The Regionalist (1997), Berry (1990) environmental systems with the measures of urbanization are correlated such as population density and built up area. Razin (1998) suggested that “Urban sprawl is widely acknowledged as an undesirable form of development, due to its economic, social and environmental disadvantages”. According to Davis (2000) “A city is a bounded space that is densely settled and has a relatively large culturally heterogeneous population. Urbanized societies, in which a majority of people live crowded together in towns and cities, represent a new and fundamental step in man’s social evolution”. Nechtya and Walsh (2004) proposed that urban sprawl can be considered as a negative effects of urban growth because of different reasons like traffic congestion, loss of public spaces etc. Later Galster et al. (2001) proposed urban sprawl as a pattern of urban land use and as a process. According to this study, urban sprawl is a pattern or a process to be distinguished from the causes of the pattern or from the consequences of the pattern.
Masek et al. (2000) made an attempt to analyze the growth of Washington DC metropolitan area from 1973-1996. For this study satellite images were used using NDVI indices and change detection techniques. Barnes (2001) uses remote sensing and GIS technologies to identify the patterns of urban sprawl on landscape.
Carruthers (2002) described urban sprawl as a dominant mode of growth in the metropolitan areas. Liu and Sylvia (2002) conducted land use land cover study of Beijing from 1982 to 1997 using remote sensing and GIS techniques. This study revealed that the rate of urban expansion was high from the year 1982 which is mainly because of huge economic development and industrial growth of the area. This study also revealed that the expansion of the city is more rapid on the northern part rather than southern or eastern part.
Jantz et al. (2003) used cellular automata, SLEUTH model for the future prediction of the city for the next thirty years. Jianjun et al (2005) also made an attempt to analyze the land use land cover change of Xi’ an region of China. For this purposes Normalized Difference Built up Area Indices (NDBI) was used.
Hossain (2008) aimed to identify the problems related with the urban growth in Dhaka city, Bangladesh as this city was experienced huge growth of slums and squatter settlement on that time period. According to this study the formation of slums is related with the rural to urban migration of the city. This study also revealed that most of the poor people in slums were migrated from the rural areas and urban poverty in the slums was mainly because most of them were engaged with informal sectors.
Fan et al. (2008) used remote sensing and GIS techniques to identify the land use and land cover of Pearl river delta, China. For the analysis supervised classification, change detection
method were used. This study revealed that most of the farmland, grass land, forest land has been converted into built up area because of this huge urban growth. Luo and Wei (2009) used global logistic regression model to predict the urban growth of Nanjiang city in China.
Alsaaideh et al. (2011) studied land use and land cover change analysis in the central part of Jordan using spatio-temporal satellite images from 1987 to 2005. According to this study huge urban expansion took place in recent decades which is mainly because of high growth rate of population, migration from the neighbouring countries and socio economic development of the region. Nole and Lasaponara (2011) made an attempt for the analysis of urban areas in the Bari town which is one of the biggest cities in southern Italy. Mohammadi et al. (2012) made an attempt to analyze the urban growth of Urmia city, Iran from 1989 and 2007. To quantify and analyze the urban growth holderness and shanon’s entropy method were used.
Salvati et al. (2012) made an attempt on the urban sprawls of the Mediterranean regions. According to the study urban sprawl on that region are mainly because of expansion of low density settlements from the inner city area. Multi dimensional approach was used for identifying and quantifying the spatial distribution of low density settlements.
Al- sharif et al. (2013) studied the urban expansion of Tripoli city of Libya from the year 1984 to 2010 using remote sensing and GIS techniques. Shanon’s entropy method was used for the study. According to them the rate of increase in built up area is greater than the population growth rate in Tripoli city between the year 1984 and 2013 and it is maximum in last decade.
Haregeweyn et al. (2012) conducted a study to analyze the dynamics of urban expansion of Bahir dar city in the north western part of Egypt from the year 1957 to 1984 using aerial photo.
Shi et al. (2012) conducted a similar study to quantify the urban growth processes. For this purpose Landscape Expansion Index (LEI) was used. According to this study urban growth type in this area was edge-expansion and most of the expansion takes place towards the peri- urban areas. This study also revealed that built up area increased like coalescense pattern and declined diffusion pattern over the years from 2004 to 2008.
Villa (2012) proposed Soil and Vegetation index for mapping urban growth of Milan city, Italy between the years 1984 to 2003. Asoka et al. (2013) were aimed to conducted research impacts of population growth on infrastructure and service in Easleigh neighbourhood. In this research work emphasis has been given on the population growth with its impact on infrastructure and services and to explore various strategies for planning of the area. According to this study infrastucture and services in this region was negeatively afftected by the population growth.
Sithole and Goredema (2013) made an attempt to analyze the urban growth of Hazare city. To mitigate of the problem of rapid urbanization many of the areas in this city has been reclaimed from the wetlands. Due to the huge population growth on those reclaimed wetlands people of those areas encounter various problems related to waterborne diseases.
Lawi (2013) analyze the urban growth of the Babati town. In this city huge migration from the rural areas created problem of water supply, sanitation, health services, unemployment etc. This study also suggested that development of rural areas should not be neglected and both the community and Government were responsible for this negative effect of urban growth.
Lu et al. (2013) conducted a study to find out the driving dorces of Guangdonf province of China from the year 2000 to 2010. According to this study there were four factors are responsible for the urban growth those were economic development, living environement,urban size and locational advantage.
Appiah et al. (2014) examined the effects urbanization on the land use change in Peri urban areas of Bosomtwe district of Ghana. This study revealed that urbanization in this area was occurred mainly due to highly demand of residential land, recreational land and commercial land.
Bihamta et al. (2014) analzed the future expansion of Isfahan metropolitan area from the year 2010 to 2015 using cellular automatic modelling and SLEUTH modelling techniques. After applying the SLEUTH model in this area it was found that the mode of future expansion of this area was ‘organic’ in recent period.
Wu et al. (2015) conducted a compertaive study of the spatio temporal pattern among the three major cities (i.e. Beijing, Tianjin and Shijiazhuang) of China. This study revealed that the expansion pattern of Beijing, Tianjin and Shijiazhuang city was double nucleated polygon line expansion pattern in recent period.
Bhalli and Ghaffar (2015) used satellite images to study the urban expansion of Lahore city in Pakistan from 2000 to 2014. Both the supervised classification and change detection techniques has been used for land use change analysis. According to this study due to the urban growth most of the cultivated land has been transformed into built up area and major changes in land use has been taken place in case of built up area and agricultural area. This study also reveaoed that Lahore city was expanding towards the south east, south and south west through the major roads.
Similar Studies at National Level
The first appearance of urban growth and sprawl using remote sensing data in India was first published in 1989 in “Journal of Indian Society of Remote Sensing”. Sokhi et al., (1989) and Uttarwar and Sokhi (1989) first aimed to study the fringes of New Delhi from the areal remote Sensing data. Jothimani (1997) used Landsat MSS and IRS LISS-II images for the analysis and trends of urban sprawl along transportation network of Surat and Ahmedabad cities. In this study only the visual interpretation techniques were used. Later Lata et al., (2001) used remote sensing data for the characterization of urban sprawl for the Hyderabad city in the southern part of India using shanon’s entropy. Sudhira et al. (2003) used shanon’s entropy approach to analyze the urban growth along the Bangalore-Mysore highway using multi-temporal remote sensing data.
Banerjee, (2005) tried to trace the evolution, growth and development of Kolkata city in relation with its regional economy and population growth from the year 1901 to 2001. This paper also highlighted on the effect of rapid urban growth on land use, traffic congestion, environmental quality, urban housing etc.
According to Sudhira and Ramachandra, (2007) urban sprawl is characterized by unplanned and uneven pattern of growth which is driven by multitude of processes and it leads into inefficient resource utilization. According to this study urban sprawl is change in land use and land cover which is mainly increase in built up and paved area.
Later Jat et al. (2007) used shanon’s entropy and landscape metrics method to compute and quantify the spatial distribution of sprawl of Ajmer city. Other than these methods different statistical techniques were used to establish the relationship between the urban growths with the factors of urban growth. According to this study land development in Ajmer city was more than three times than the population growth.
Vipin, (2008) made an attempt to identify the urban expansion and to analyze the factors behind the urban expansion of Bikaner city. According to this study the physical growth of the Bikaner city was faster than population growth rate and the city was expanded along the major roads and railway tracts.
Chaudhary et al. (2008) attempted to identify of land use or land cover pattern in northern part of Gurgaon District using satellite images from 1996 to 2002. Shweta (2009) made an attempt to study the urban sprawl of Jaipur Metropolitan Area. According to this study, rapid growth of population is mainly because of different factors like influx of refugees from Pakistan, rapid growth of industries and growth of secondary and tertiary activities etc. Author also suggested various strategies for future land use planning of the area.
Sivaramakrishnan and Bandopadhyay (2009) considered Dehradun city for the land use or land cover analysis. The images of the year 2000 and 2005 were used and to find out the change in land use and land cover change detection technique was used. This study revealed that the percentage of built up area is high in the southern part of the city and transformation of cultivated land to built up area was maximum.
Bhatta (2009) was used different models using remote sensing data to analyze the urban growth pattern of Kolkata. Various statistical techniques were used to udentify the pattern which shows the development of the city with the declining population growth rate on that time period.
Mohan et al., (2011) makes an attempt to monitor the urban expansion of Delhi using sateliite images. According to the study from the year 1997 to 2008 the city was expanding towards peripheral regions and because of this expansion most of the rural area were transfromed into urban area. For this urban expansion most of the agricultural land, waste land, scrub land, sandy areas and water bodies were transformed into built up area.
Basawaraja et al. (2011) studied the urban sprawl of Raichur city of Karnataka. According to the study this city was experienced rapid urbanization in recent decades which leads into haphazard growth of the area. This study also showed that because of the rapid urbanization most of the agricultural land has been converted into built up area and accourding to thir prediction within the year 2021, 27 percent of the agricultural land has been converted into built up area.
Gupta (2011) discussed about the land use land cover change of Jaipur city more than 30 years time. This study revealed that the growth of population in this area was very high from the year 1971 to 2001 and population growth was the major driving factors of the land use and land cover change of Jaipur city.
Bhardwaj and Kumar (2012) made an attempt to analyze the changes of landscape in Karnal city using remote sensing and GIS techniques. Four major land use categories were identified i.e. built up area, waterbodies, cropland or vegetation land and bare land. According to this study this city was exanding through the railway track or the national highway and conversion of crop land and vegetation land into built up area is maximum which is followed by vacand land and bare land to built up area.
Dubey and Kumar (2013) made an attempt to analyze the urban sprawl of Gorakhpur city using remote sensing and GIS techniques. According to the study, urban development is largely towards the north, north-west and south-west direction along the major transportation route of the city. For this rapid urban development vegetation and agricultural areas has been transformed into urban area nearer the city areas.
Tali and Murthy (2013) focused on the land use land cover changes of Srinagar City over the 30 (1979-2010) years time period using multi temporal satellite images. From the spatio temporal study it was found that expansion took place towards the Budgam in the southward direction, Baramulla in western direction, Pampore in the south eastern direction and Ganderbal in the northern side.
Chawla (2013) gave an idea about the impact of land use change on environment. Gogoi (2013) analyzed the land use pattern of Guwahati city over the three decades using satellite data and according to the study due to the urban growth vegetation area, wetlands, cultivated land were decreased rapidly which impacted upon the city’s life and environment. The growth and development of this city is unplanned and haphazard in nature.
Subramani and Vishnumanoj (2014) made an attempt to analyze the urban sprawl of Panamarathupatti Lake of Salem from the year 1973 to 2009. For the change analysis change detection methods has been used. According to the study built up area increased a lot while agricultural area and barren area was decreased rapidly.
Kumar and Tripathi (2014) applied remote sensing and GIS techniques for mapping and evaluationg urban sprawl in Nagpur City of Maharsahtra. According to them the amount of built up area increased 37.18 square kilometer between the twelve year time period. According to them growth of the city is maximum towards the eastern direction and it is minimum towards the western direction.
Rani (2014) made an attempt to analyze the urban growth of Jalandhar city from the year 1901 to 2011. This study revealed that this area was experienced huge population growth between the time periods and urban expansion took place towards the peripheral areas of the city. For this reason in the peripheral areas built up area increased a lot while agricultural areas were decreased rapidly.
Suribabau and Bhaskar (2014) used multi temporal satellite images to analyze the trends and pattern of urban growth of Thanjavur city between 1970 and 2006. For the analysis unsupervised classification with the maximum likelihood algorithm was used. Mahapatra, Paul, and Sharma (2014) analyzed the impact of urban expansion on the geomorphology of Gwalior city between the years 1972 to 2013 with the help of multi temporal satellite images. According to the study pediplain, residual hills, denudational hills were affected.
Kovitha et al. (2015) attempted to analyze the process of urban growth in Bangalore city and according to this study built up area was increased a lot while agricultural area was decreased rapidly. Kumar et al. (2015) conducted a similar study of Vijayawada city from 1973 to 2013. For the analysis change detection technique was used.
Vijayakumar et al. (2015) tried to analyze the land use land cover change of Thirumanimuttar Sub Basin, Cauvery River between the year 1992 to 2010. This study revealed that because of the rapid economic development and urban expansion of the area built up area increased a lot while evergreen forest decreased rapidly.
Bhat et al, (2017) made an attempt to monitor land use and land cover of Dehradun city between the year 2004 and 2014, using IRS p-6 data and topographic sheets to assess urban sprawl in GIS environment for better decision making and sustainable urban growth.
As a whole, rapid urbanization and urban growth leads into land use change, mainly from the agricultural area, wetland or vegetation area to built up area. These results into change in land use, socio economic and transport externalities of the city. Several studies have been conducted both in the international level and national level on the urban growth, urban expansion, land use land over change etc. This research study differs from the others in the sense that is analyzes the effect of urban growth on the land use, socio economic condition and transport condition of Kolkata Metropolitan Area. Further this study is unique as it analyzes the shift or change in city’s externalities due to the impact of urban growth. This study will throw new light for to find out the externalities of the Kolkata city towards the semi urban areas.
The research work is based on the empirical study of the specific urban unit. The entire work can be represented in the following manner.
At the beginning previous literature study from various books, journals, periodicals, administrative report, Governmental and Non-Governmental publications has been done to specify the research problems, selecting the area and topic of this research work.
The following multi-temporal remote sensing satellite imageries have been used to find out the nature and pattern of urban expansion in the southern part of Kolkata Metropolitan Area (KMA) and also to find out the externalities of land use among the four municipalities (i.e. Rajpur Sonarpur Municipality, Maheshtala Municipality, Budge Budge Municipality and Pujali Municipality). Administrative maps (ward maps, boundary maps, road maps etc.) published from the different municipalities has been collected and digitized from hardcopy topographic maps from the Survey of India, with scale of 1:50,000. This map has been used as a reference image. It has been also used for geometric correction of the satellite images and for some ground truth information. Finally, ground information was collected between 1980 until 2015 to find out the accuracies of those land use and land cover map.
Table 1.2 Detailed Information of Utilized Satellite Imagery
Acquisition Date Sensor Spatial Resolution Projection
08-12-2015 OLI 30m WGS 84 UTM 45 N
05-11-2010 TM 30m WGS 84 UTM 45 N
17-11-2000 ETM+ 30m WGS 84 UTM 45 N
14-11-1990 TM 30m WGS 84 UTM 45 N
16-01-1980 MSS 60m WGS 84 UTM 45 N
Source: US Geological Survey, 2015.
All the landsat imageries (Table 1.2) have been collected from the United States Geological Survey (USGS). Thermal bands of landsat sensors have not been considered for the analysis. For digital processing of satellite imageries Erdas imagine software has been used.
Table 1.3 The Spatial Resolutions of the Used Imageries
Landsat MSS Landsat TM and Landsat ETM+ Landsat OLI 8 LISS IV
79*57m 30*30m 30*30m 5.8*5.8m
Source: US Geological Survey, 2015
A total of 300 ground control points (GCP) surveyed with Global Positioning System (GPS) receiver have been used to make the satellite imageries geographically referenced.
Information and Data Sources
Detailed map of Kolkata Metropolitan Area has been collected from the office of Kolkata Metropolitan Development Authority (KMDA). To find out the growth, development and to analyze the shift in city externalities different maps have been collected from various sources. For e.g. Administrative map of Rajpur Sonarpur Municipality, Transport and Communication map of Maheshtala Municipality, Drainage and Sewerage map of Budge Budge Municipality, Ward map of Pujali Municipality etc.
Secondary data (e.g. socio-economic, demographic) of the year 1981, 1991, 2001, 2011 data has been collected from the Census Office at Saltlake, Kolkata Municipal Corporation office and Kolkata Metropolitan Development Authority (Unnayan Bhawan), Rajpur Sonarpur Municipality, Maheshtala Municipality, Budge Budge Municipality, Pujali Minicipality, Bureau of Applied Economics and Statistics office etc. Primary data collected from the field survey has been used to analyze the shift in city externalities.
Table 1.4 Spectral Details of The Satellite Imageries
Landsat MSS Landsat TM and Landsat ETM+ Landsat OLI 8 LISS IV
Bands Spectral resolution
7 0.8-1.1 Bands Spectral resolution
7 2.08-2.35 Bands Spectral resolution
7 2.10-2.30 Bands Spectral resolution
Spectral resolution in µm.
Source: US Geological Survey, 2015
Scanning Hardcopy Map
The hardcopy map of KMA and four municipalities has been scanned with drum scanner to convert into digital raster image. Then those images have been geo-referenced with the topographical maps and satellite imageries.
To analyze the trends of Demographic growth
To analyze the trends of demographic growth of Kolkata Metropolitan Area, Rajpur Sonarpur Municipality, Maheshtala Municipality, Budge Budge Municipality and Pujali Minicipality following parameters have been used.
Annual growth rates of population in percentage have been estimated using the following equation:
R= (P2-P1)/P1 *100
Where, P1 and P2 are the population of urban area in two census years at 10 years interval and R= Rate of growth.
Population density may be defined as number of population per square kilometer of area.
Concentration of Population
Concentration of population has been computed by
Concentration of population= (Pi /Pt)
Where Pi and Pt are the population of any urban centre and total of the region respectively. It ranges between 0 to 1. (Basak, 2009)
Land use and land cover Change
The images were geometrically corrected and geo-refernced to the Universal Transverse Mercator (UTM) coordinate system by using a reference image which has been geo-referenced previously from the topographical maps provided by Survey of India (SOI). The minimum of 250 randomly distributed ground control points (GCPs) were selected from the topographical sheets for geo-referencing the image. Re-sampling technique was performed using a nearest neighbour technique.
Land cover classes are typically mapped from digital remotely sensed data through the process of a supervised digital image classification (Campbell, 1987; Thomas, et al., 1987). The overall objective of the image classification procedure is to automatically categorize all pixels in an image into land cover classes or themes (Lillesand and Kiefer, 1994). ERDAS IMAGINE 9.2 software has been used for digital image processing and image classification.
To scrutinize the nature of Land use and Land cover change
Urban Land use classification Criteria
Classification is therefore, an activity of subdividing a group of objects in two or more groups. This classification can be based on activity, economic function, physical appearance, or simple land cover. The guidelines could be:
The classification system should be applicable over a large area covering both city core and its surroundings and it should be applicable for using remotely sensed data obtained at multi temporal time periods.
Minimum accuracy and reliability of the classified image should be about 85 percent.
The nomenclature, definition and framework to the extent possible should be compatible with existing terminologies adopted in planning agencies.
Classification should be easier to understand and flexible and the land use classes must be mutually exclusive, i.e. any geographical individual can only fall into one class and wherever possible, it must be based upon quantitative criteria (Rai & Kumra, 2011).
Table 1.5 Land Use and Land Cover system of Classification of United States Geological Survey
Level/ Sl. No. Level-I Level II Level III
I Built up structure Settlement
II Land under vegetation Agricultural field
III Water body River
IV Land without vegetation Fallow land
Source: Anderson, et al., (1976)
Table 1.6 Scheme of Classification
Level Classes Sub classes
I Built up Area 1. Rural 2.Urban 3. Mining
II Agricultural 1.Cropped 2.Plantation 3.Fallow
III Forest land 1. Evergreen 2.Deciduous 3.Forest plantation
4.Scrub forest 5.Scrub Mangrove
IV Grass/Grazing Grass/Grazing
V Barren/ Un culturable/ Waste lands 1. Salt affected land 2. Scrub land 3.Sandy land
4. Barren rocky
Vi Wet lands or water bodies 1. Inland wet land 2. Coastal wet land
3.River/ stream/Canal 4. Reservoir/ Lake/ Pond
Source: National Remote Sensing Centre, India
Table 1.7 Scheme of Classification of land use and land cover used in this study
Level Classes Sub classes
I Built up Area Rural Urban
II Vegetation Dense vegetation Light vegetation
III Cultivated Area Cropland Plantation and Orchards
IV Water bodies Inland wet land Riverine wet land
River/ stream/Canal Pond
V Barren land Uncultivable land Waste lands
Source: Computed after image classification.
Accuracy assessment method is very useful for individual classification when resulting data are used for the change detection analysis (Owojori & Xie, 2005). Accuracy assessment technique was performed based on using a random sample method of more than 150 check points from ground control points obtained during GPS survey, old historical maps, topographic maps etc. have been used as a referenced map.
Detection of LULC changes
Post Classification Comparison (PCC) method and change detection analysis has been applied to compare and analyze the LULC maps resulting from the integration of the results of visual interpretation and supervised classification. PCC was used to detect the differences between each pair of LULC maps (i.e., 1980 to 1990, 1990 to 2000, 2000 to 2010 and 2010 to 2015).
Change detection accuracy assessment
The simplest method of accuracy assessment of change maps is to multiply the individual classification map accuracies to estimate the expected accuracy of the change map (Yuan et al., 1998). A more rigorous approach is to randomly sample areas classified as change and no-change and determine whether they were correctly classified (Fuller et al., 2003).
Overall accuracy was calculated from the error matrix by dividing the sum of the entries that make major diagonal by the total number of examined pixels. Khat statistics of agreement was also calculated by using following equations.
r = number of rows in error matrix
nij = number of observations in row i, column j
ni = total number of observations in row i
nj = total number of observations in column j
M = total number of observations in matrix (Jensen, 1996).
To find out the Shift (Direction and length) of Mean Center of Population 1981 to 2011
Understanding the mean center of population is very essential for urban modeling as well as urban design and planning. The mean center will give the concentration of population for the respective year. When the direction of the shift in mean center is followed it will give us the direction of urban growth.
The length of shifting of mean center is calculated by?(X1~X2+Y1~Y) 2.
In this above equation each of population has been multiplied with coordinates for each Municipal Corporations and Municipalities. The sum of the calculated values is X1 representing the standard distance of previous year and X2 represents standard distance of the second consecutive year which is calculated by X coordinates in the same manner as X1. Y1 represents the standard distance of previous year and Y2 represents standard distance of the second consecutive year which is calculated by Y coordinates of an area. The standard distance is calculated by the difference between X1 and X2. The direction of shiftingtan^(-1)? has been calculated by the ratio of standard distance of?X/?Y. (Sarkar, 2013)
Identification of Probable Rural areas to be Urbanized in Future
To identify the probable areas of urbanization in the rural areas of KMA different variables have been used which are obtained from the Census of India. Weightage has been given over the data on the presence and absence of the facility. To visualize the probable urbanized area in future different cartographical techniques have been used. To find out the main dominant factors responsible for the high possibilities of urbanization CAT PCA (Categorical Principal Component Analysis) has been used. Before applying the CAT PCA, those variables have been categorized into three broad categories. Those are Socio-economic categories, land use categories and infrastructural categories.
Table 1.4 Criteria’s for Identification the Probable Areas for Urbanization
SL No. Name of Variables Criteria Character
Urban Peri Urban Rural
Socio- Economic variables
1. Population (Total) >=2500