new bombay

The Urban Social Pattern of Navi Mumbai, India

Malathi Ananthakrishnan

Thesis submitted to the Faculty of the

Virginia Polytechnic Institute and State University

in partial fulfillment of the requirements for the degree of

Master of Urban and Regional Planning

John Browder, Chair

Wendy Jacobson

Paul Knox

April , 1998

Blacksburg, Virginia

Keywords: urban social pattern, Navi Mumbai, Bombay, urban planning - India

Copyright 1998, Malathi Ananthakrishnan

The Urban Social Pattern of Navi Mumbai, India


(ABSTRACT)

This research thesis examines the emerging trends in urban social patterns in NaviMumbai, India. Unlike the other planned cities of India, Navi Mumbai was specifically built asa planned decentralization of a large metropolitan city. The research focuses on explaining theurban social pattern of this particular case study. An urban social pattern reflects the socialcharacteristics of the urban setting. In the case of Navi Mumbai, the government had a socialagenda of promoting a social pattern based on socioeconomic distribution rather than an ethnicone. Analysis of the data provides an insight to the results of this social agenda, and provides abasis to frame new ones. Thus, the study not only addresses a basic research question, but alsohas policy implications.

The research involves a comprehensive review of secondary source material to establishthe theoretical framework for the research. The review also involves an extensive inspection ofurban social patterns across the world to better contextualize this particular case study. Theresearch puts forth a model that explains the social pattern of Navi Mumbai by social areaanalysis using variables, which are drawn from social aspects of any city and indigenous factorsof Indian settlements. The model depends not only on statistical analysis but also oninterpretation of local conditions. This research situates the emerging social pattern ingeographic literature in developing countries.

This research was supported in part, by a grant from the College of Architecture andUrban Studies, Virginia Tech.

Acknowledgment

I would like to take this opportunity to thank my Advisor and Chair of my committee, Dr. John

Browder. He was supportive of all my efforts to successfully complete this thesis. It would not

have been possible without his help. Thank you also to my committee members, Dr. Jacobson

and Dr. Knox, for the time and effort they contributed.

Thanks also due to everyone in Navi Mumbai who helped me collect the data and all relevant

information. Special thanks to Ms. Adusumilli, Senior planner, CIDCO, Mrs. Raje, Chief

statistician, CIDCO, Dr. Venkatachalam and Dr. Sengupta at IIT-Bombay and Dr. Banerjee-

Guha at the University of Bombay. I would also like to thank Prachi and Avesh Tapde for their

hospitality in Navi Mumbai.

Dr. Dyck and Dr. Bohland clarified many of my conceptual and analytical queries. I would like

to give my appreciation for their support. I would also like to thank Dr. Randolph and Dr.

Schubert for having made a grant available for me to carry out the field research.

I am also grateful to my good friends Inga, Maneesha and Elda for not only helping me out with

proof reading and other mundane things, but also for being there during the ups and downs of the

entire process. I would like to thank my family for always encouraging me to think and my

fiancé for his patience.

Table of Contents

1. Introduction…………………………………………………………………..1.1 Research Problem Statement1.2 Significance of Thesis1.3 Organization of the Thesis

2. The Research Setting………………………………………………………….2.1 Introduction2.2 The Planning History of Bombay and the Greater Bombay region2.3 The Creation of Navi Mumbai2.4 The Draft Development Plan of 19732.5 Development Potential of the Site2.6 Design Principles of Navi Mumbai2.7 Social Agenda in the Planning of Navi Mumbai2.8 Plan Implementation through the Public Administrative Framework2.9 The Reality of Implementing the Plan2.10 Conclusion

3. The Conceptual Framework…………………………………………………..3.1 Introduction3.2 Urban Form and Urban Pattern3.3 Factors influencing Urban Form3.4 The Evolution of the Urban Form of Indian Cities3.5 Sociocultural Factors

3.5.1 Caste3.5.2 Class3.5.3 Religion3.5.4 Language3.5.5 Implications of the Sociocultural factors

3.6 The Built Form3.7 Theories of Urban Social Patterns

3.7.1 Concentric Zone Theory3.7.2 Sector Theory3.7.3 Multiple Nuclei Theory

3.8 Case Study of Urban Social Patterns3.8.1 Western Cities3.8.2 Third World Cities3.8.3 Indian Cities

3.9 Conclusion

4. Research Design………………………………………………………………4.1 Social Area Analysis4.2 Hypothesis4.3 Operationalization4.4 Data Collection4.5 Methodology

4.5.1 Descriptive Analysis4.5.2 Cluster Analysis

1

3

20

38

4.5.3 Principal Component Analysis4.5.4 mapping and Overlays

4.6 Data Analysis

5. Presentation of Data…………………………………………………………..5.1 Introduction5.2 Descriptive Analysis5.3 Regional Scale – nodes

5.3.1 Principal Components Analysis5.3.2 Cluster Analysis5.3.3 Discussion

5.4 Sub-regional Scale – sectors5.4.1 Principal Components Analysis5.4.2 Cluster Analysis5.4.3 Discussion

5.5 Conclusion

6. Interpretation / Discussion……………………………………………………6.1 Regional Scale6.2 Sub-regional Scale

6.2.1 Socioeconomic Status and Sector Theory6.2.2 Family Status and Concentric Zone Theory6.2.3 Ethnic Status and Multiple Nuclei Theory

6.3 Summary6.4 Potential Utility of the Research

7. Conclusion……………………………………………………………………

Bibliography……………………………………………………………………..

Glossary of Terms

Appendix AAppendix BAppendix CAppendix DAppendix EAppendix FAppendix G

43

65

74

77

List of Tables

Tablenumber

Title page

2.12.22.32.42.52.6

4.14.2

5.15.25.35.45.55.65.75.85.95.105.115.125.135.145.155.165.175.185.195.205.21

Population Density of BombayImmigrant population of BombayLand Fragmentation in 1970Household Income and Capacity to PayPopulation Density in Various Sectors of BombayLand Use of Navi Mumbai

Constructs and VariablesSurvey Sampling

Constructs and VariablesWork ForceNumber of EarnersOccupational Classification of WorkforceHousehold IncomeLocation of Education InstitutionsLevel of EducationMale PopulationFemale PopulationFamily SizeType of HousingOwnership of HouseHousing built by CIDCOHousing built by Private EnterpriseYear of OccupationPrevious Place of ResidenceReligionLanguageSpatial Pattern of VariablesAttributes of Principal ComponentsAttributes of Principal Components

45681617

3940

434444454647474849505152525353545556576061

List of Figure

FigureNumber

Title Page

2.12.22.32.42.5

2.6

3.13.23.33.43.53.63.73.83.93.10

5.15.25.3

5.45.55.65.75.85.95.105.115.125.135.145.155.165.175.185.19

6.16.26.36.46.5

Expansion of BombayTwin City Across the HarborDevelopment Potential of the SiteNodes of Navi MumbaiInstitutional Hierarchy in Implementation of Development Plan forNavi MumbaiLand Use of Navi Mumbai

Circle and Swastika Town PlansConcentric Zone TheorySector TheoryMultiple Nuclei TheoryUrban Social PatternsPlan of Delhi and New DelhiAsian PortsLatin American CitiesPattern of Indian CitiesTheories of Urban Social Patterns and Corresponding Case Studies

Distribution of Single-earner FamiliesFrequency of Families with Income range Rs. 2651-4450Frequency of Families with at least one individual with SecondaryEducationFrequency of Male Population in the age group 25-45Frequency of Households with 4 or 5 membersFrequency of Houses built by CIDCOFrequency of Housing built by CIDCOFrequency of Houses built by Private EnterpriseFrequency of TenureFrequency of Bombay as Previous Place of ResidenceFrequency of HindusFrequency of MuslimsFrequency of MarathiFrequency of MalayalamComponents in Rotated SpaceLoadings of Principal ComponentsDendrogram using Average Linkages between groupsLoadings of Principal ComponentsDendrogram using Average Linkages between groups

Cluster of Nodes of Navi MumbaiAverage Linkage between Factor ScoresAverage Linkage between VariablesClustering of Sectors of VashiAverage Linkage between Factor Scores

2571115

18

26282929313232333436

454648

49505152535455565657575959606263

6566666768

6.66.76.86.96.106.116.126.136.146.156.166.176.18

Average Linkage between VariablesHypothetical Sector Pattern for Socioeconomic variablesDistribution of Number of EarnersDistribution of IncomeHypothetical Concentric Pattern for Family Status variablesDistribution of Ownership of ApartmentHypothetical Multiple Nuclei Pattern for Ethnic variablesDistribution of Households speaking MarathiDistribution of Households which follow IslamClustering of SectorsScore 1Score 2Score 3

68696969707071717172727272

Chapter 1: Introduction

1.1 Research Problem Statement

The overall objective of this thesis is to determine what common patterns, if any,exist in the urban social pattern of planned towns in India. The urban social pattern is one ofthe many aspects of the urban form. The urban form of a city is primarily the result of thecharacteristics of its physical and social design as well as socioeconomic and political forces.It is a synthesis of the spatial relationships of various elements. Different characteristics aredrawn from the factors influencing the physical design and cultural aspect of the city.Physical and economic landscapes, land use and ownership, street patterns, planningregulations, and political events may influence the physical design and pattern of a city.Various processes influence the social pattern of the city. These include the ethniccomposition of the city, religion, race, migration, and the housing market.

Navi Mumbai (New Bombay) is one of the first planned new town developmentsbuilt for a diverse, middle class population in India. Traditional Indian cities have evolvedover the centuries, and their social pattern is characterized by residential segregation basedon ethnic, religious and linguistic classes. The purpose of this thesis is to delineate andinterpret the social pattern of Navi Mumbai.

Socioeconomic factors, housing characteristics, land use pattern and ethnicclassifications will be used as key variables to study the urban social pattern of NaviMumbai. Urban patterns occur because of repetition of these elements. The pattern of NaviMumbai will be studied at different hierarchical spatial levels: regional (node / township) andsub-regional (sector / neighborhood).

1.2 Significance of Research

A holistic approach to the study of settlements involves understanding theinterrelationships between their constituent elements at a certain period of time. The studyof the physical form and structure of cities is the study of urban morphology. Why is such astudy significant? The urban form of the city influences behavioral, economic and socialprocesses within it (Vance, 1990). Thus, the study of human settlements has anencompassing view of all the activities it supports.

The basic research here involves the search for an urban social pattern of NaviMumbai. This research determines how the present social pattern relates to varioustheoretical frameworks. This research aspires to contribute to basic research in socialgeography. The literature review shows that a specific study of Navi Mumbai has not beenpreviously documented. Therefore, this paper will augment existing knowledge about socialconfigurations of planned urban development in Asian regions.

A policy emphasizing a uniform distribution of the population is the ideologicalorientation of the government. An interpretation of the emerging social pattern revealssomething of the social character of the city. The pattern suggests not only the outcome of

Malathi Ananthakrishnan Chapter 1: Introduction 2

the policy, but also variables that influence this pattern. The urban social pattern also servesas a framework for further research. Thus, the basic research has many applications in long-range planning in Navi Mumbai.

1.3 Organization of the Thesis

This thesis is divided into seven chapters. This first chapter is the introduction,which provides the problem statement and the broader objectives of the thesis. The secondchapter provides the background to the particular case study used in the research. The thirdchapter is a comprehensive review of the secondary sources to establish a context of theresearch question. The fourth chapter outlines the methodology used for analysis of data andexplains the data source and method of data collection. The presentation of data and itsanalysis is in the fifth chapter. Interpretation and discussion of the analysis and itsrelationship to the theories discussed in the third chapter is done in the sixth chapter.Chapter seven draws to conclusion the thesis with a review of the problem statement, theresearch setting, its contextual framework, methodology, analysis and interpretation and thebroad outcomes of the thesis.

Figure 2.1 Expansion of BombaySource: Dwivedi and Mehrotra, 1995.

Chapter 2: The Research Setting

2.1 IntroductionNavi Mumbai (New Bombay), India, established in 1972, is a new planned city across

the harbor (of Bombay) from Bombay. This planned decentralization was the outcome ofefforts by the government to make Bombay more “sustainable” (Bombay MetropolitanRegional Planning Board, 1973). The geographical area of Bombay is an island. The firstsettlement was established in the southern most tip of the island. Urbanization and

subsequent suburbanization of Bombayhave created a linear city such that thecentral business district (CBD) andresidential areas have become furtherand further apart (Figure 2.1).Bombay’s high concentration of docks,trading posts, textile mills andgovernment offices have made it thepreeminent port of Western India.South Bombay is the center of India’sbanking and service industries. Thisrange of activities led to crowding at anunprecedented scale. In Bombay, forthose who could not afford to make thelong commutes, squatter settlements allover Bombay became the way of life.Navi Mumbai was designed to providea better quality of life, especially to themiddle and lower class of people.

2.2 The Planning History of Bombayand the Greater Bombay region Bombay is not a city built on Indiantraditional planning ideas. The city ofBombay had its beginnings in a series

of fishing villages until it was taken over by the Portuguese in the 16th century. In 1661, theKing of Portugal gifted the Bombay islands to King Charles II of England when KingCharles married Catherine Braganza, a Portuguese princess. In 1668, the Crown rentedBombay to the East India Company. Bombay was then established as a trading post. TheEast India Company encouraged Indian and East India Company merchants to settle inBombay. By the 1780s, the East India Company had taken on the new role of ruler (Dwivediand Mehrotra, 1995).

The East India Company, now as rulers, was interested in developing the town in amethodical manner, and providing efficient infrastructure (Dwivedi and Mehrotra, 1995).The harbor was strengthened, the shipyard modernized and the city fortified. There was a

1965

1950

1957

ArabianSea

BOMBAYNAVI

MUMBAI

1910

Malathi Ananthakrishnan Chapter 2: The Research Setting 4

strong development of mixed land use settlements. Commercial and residential areas weremixed because many merchants carried on business from home (Tindall, 1992).

In 1865, the Bombay Municipal Corporation was established, and, in 1896, theBombay Improvement Trust was created. These formal government bodies were thebeginning of a conscientious effort to regulate the growth of Bombay (Banerjee-Guha, 1995).By the early 1900s, some thought was given to ’Greater Bombay’, which would encompassthe Fort area as well as the suburbs of Bombay. However, Greater Bombay came intoexistence only after the Bombay High Court Act of 1945. This enclosed the Town and Islandof Bombay, the Port of Bombay, the suburbs and 42 villages within the definition of the newcity limit (Dwivedi and Mehrotra, 1995). The Post-War development Committee of 1945and the ’Master Plan in Outline’ prepared by Albert Mayer and N. V. Modak influenced thedevelopment of Greater Bombay for the next two decades (Dwivedi and Mehrotra, 1995).

The development acts of 1954 and 1964 emphasized the need to relocate industrialactivity from the island to the mainland (CIDCO, 1995). In the 1960s, various planningcommittees were formed to develop a regional plan for Bombay. Land use zoning and theconcept of floor space index were incorporated for the first time. In 1966, the GadgilCommittee strongly recommended a multi-nuclear growth using the creation of a new townacross the harbor. This committee appointed the Bombay Municipal Regional PlanningBoard to develop the concept further (Gadgil Committee, 1965). In 1967, the BombayMunicipal Regional Planning Board set up two committees to study the development ofBombay. They recommended:

i the creation of a new town on the mainland across the harbori develop the suburbs of Bombay further

Bombay had reached a level of unmanageable growth by the 1960s. Bombay’sinfrastructure facilities were stretched to the limit. Commuter distances had become largerbecause of increased suburbanization with no change in location of the CBD. The 1967development plan estimated a housing shortage of 131,000 houses, and 24 percent of the oneand two room tenements were over crowded.Table 2.1 Population Density of Bombay

1881 1891 1901 1911 1921 1931 1961 1971Area in acres 14247 14281 14342 14575 15066 15480 16751 16720Persons / Acre 54 56 54 67 78 75 165 184

(Various Census Reports for Bombay in Kosambi, 1986)

The Bombay Metropolitan Regional Planning Board in its report wroteBombay the Beautiful is no more beautiful. Many parts of it are not even tolerablyclean and healthy. Housing deficits are ever widening and slums like a cancerousgrowth can be seen anywhere and everywhere. Adequate water is a serious problem.Transportation is threatening to break down….

(BMRPB, 1973)Population increase, concentration of industries and offices in certain pockets of Bombay,lack of housing and infrastructure and high land values were the major problems identified.The large migrant influx contributed to the overcrowding (Table 2.2).


Figure 2.2 Twin City Across the HarborSource: CIDCO, 1973.

Table 2.2 Immigrant Population of Bombay1881 1891 1901 1911 1921 1931 1961 1971

Population 773196 821764 776006 979445 1175914 1161383 2771933 3070378%Immigrants

72 75 77 80 84 75 72 63

Males per100 Females

151 171 162 189 191 181 160 149

(Various Census Reports of Bombay in Kosambi, 1986) The concentration of industries and offices at the CBD and suburbs like Chembur andAndheri created unequal development, air pollution and mixed land use (UNCHS, 1993).Unhealthy and insanitary conditions for 1 million slum dwellers was the result of inadequatehousing stock. Lack of adequate water supply and sewage facilities worsened conditions.Also, rocketing land prices prevented the acquisition of land for public purposes (BMPRB,1973). In a final attempt, the Bombay Metropolitan Regional Planning Board recommendedconsidering a twin city across the harbor.

2.3 The Creation of Navi MumbaiThe prominent authors of the

’twin city concept’ were CharlesCorrea1, Pravina Mehta2 and ShirishPatel3 who presented to the governmenta proposal in 1964 for constructing newgrowth centers across Bombay harboron the mainland (Figure 2.2). Theimplementation occurred through’correct’ political and bureaucraticchannels in 1969. This was in the formof the Bombay Municipal RegionalPlanning Board’s recommendation thata new city be designed within theBombay Metropolitan region tofacilitate the decongestion of Bombay(Correa, 1997). If the new city was toofar away, then this would not bepossible (BMRPB, 1973).

The site that was finally chosenwas across the harbor from Bombayisland. It is a narrow piece of landbounded by the Western Ghat mountainranges on the north, south and east, and

1 Charles Correa is a prominent architect and urban designer in Bombay.2 Pravina Mehta (late) was a structural engineer.3 Sirish Patel, engineer and planner, was incharge of the planning and design of Navi Mumbai (1970-75).

GrowthCenters

ofBombay

TownCenter

New GrowthCenters

ArabianSea

Harborof

Bombay


the Arabian Sea on the west (CIDCO, 1973). Navi Mumbai covers an area of 344 sq. km. Itis a self-contained city independent of Bombay although there is still a visual connection toBombay.

It was hoped that the nearness to Bombay would facilitate the relocation of peoplefrom Bombay (CIDCO, 1973). Correa, Patel and Mehta designed this regional plan based onthree basic objectives: a planned new development, financing physical and socialinfrastructure through land sales, and improving Bombay by drawing off pressures forgrowth into the new area (Patel, 1997).

The new town, comprising of a number of nodes (townships), was designed toaccommodate new industrial and commercial activity as well as for secure and affordablehousing to workers. The plan hoped to reduce homelessness in Bombay and provide slum dwellers a better life as well as absorb migration from the countryside (Correa, 1985). Theregional plan was approved in 1970. The Bombay Municipal Regional Planning Boardcreated the City and Industrial Development Corporation (CIDCO) in 1970 to implement itsideas.

2.4 The Draft Development Plan of 1973

The task of planning and developing Navi Mumbai was entrusted to the City and IndustrialDevelopment Corporation (CIDCO), a government agency explicitly set up for this purpose.CIDCO is a limited company, wholly owned by the State Government of Maharashtra(CIDCO, 1973). The first task of CIDCO was to prepare a development plan for the newtown. CIDCO used certain development principles in its design. They were (CIDCO, 1973):

i polycentric pattern of developmenti acquisition of all land to have better control of the environment and to use land as

the main resource for development.

The first step was to identify all the land that needed to be acquired for Navi Mumbai.Owners were notified about the government’s proposal. The land notified for acquisition forNavi Mumbai was under private and government ownership (Table 2.3)

Table 2.3 Land Fragmentation in 1970Ownership Area (sq.

km)>500 sq. m.

(number)>1000 sq. m.



Government 10137 - - - AllPrivate 16677 18412 3338 1579 90Marsh(wetlands) 84

(CIDCO, 1995)CIDCO notified all private owners about the compulsory acquisition. The governmentwould acquire land under its power of eminent domain under Section 22, MaharashtraRegional and Town Planning Act (MR&TP Act), 1966. Section 31(6) under the same actgives the government the power to specify land use and proceed with development. Thefinality of the approved Development Plan ensures that the pressure and friction which woulddevelop to obtain land use changes for particular land holdings would be largely eliminated


(CIDCO, 1973). This was not entirely true, and major law and order problems did occur.Nevertheless, CIDCO acquired all the land after settling disputes about compensation(CIDCO, 1995).

Although the main objective of the design of Navi Mumbai was to create a self-sufficient urban environment, it also hoped to improve the quality of life of Bombay. Theobjectives were (CIDCO, 1973: 10):1. Reduce the growth of population in Bombay city by creating a center that would absorb

immigrants, and also attract some of Bombay’s present population.2. To support a statewide Industrial Location Policy which will lead eventually to an

efficient and rational distribution of industries over the State and a balanced developmentof urban centers in the hinterland.

3. To provide physical and social services, raise the living standards and reduce thedisparities in the amenities available to the different sections of the population.

4. To provide an environment which would permit the residents of New Bombay to livefuller and richer lives in so far this is possible, free from the physical and social tensions,which are commonly associated with urban living.

5. To provide a physical infrastructure which prevents ethnic enclaves among thepopulation.

The Draft Development Plan gave only broad guidelines, leaving enough room for flexibility.Although five minor amendments were made to this Draft Plan, no new document was everprepared. The Draft Development Plan remains the guiding document in use even today.

2.5 Development Potential of the Site

The chosen site had variousdevelopment potentials (Figure 2.3).These were (CIDCO, 1995):• the Maharashtra IndustrialDevelopment Corporation (MIDC)Estates at Turbhe and Taloja;• the plan for a modern, containerport at Nhava-Sheva;• the existence of two municipalcorporations at Panvel and Uran;• the newly commissioned bridgeacross the Thane creek, and transportcorridors along Thane-Belapur;• the Thane-Pune National Highway4, Panvel-Uran rail and road links.

The success of Navi Mumbai wasthought to depend on the adequatecreation of jobs (CIDCO, 1995). Thedevelopment plan took into account the

Figure 2.3 Development Potential of the Site

MIDC Industrial

Estates

TalojaArabian

Sea

Turbhe

Panvel

Creekbridge

Nhava-sheva


provision of 750,000 jobs for a population of 2 million (CIDCO, 1995). This was necessaryto (CIDCO, 1995):

i make Navi Mumbai self-contained and not a dormitory;i to decongest Bombay by shifting jobs that are concentrated in the southern part of

Bombay;i to use the job centers with matching infrastructure provision as engines of growth

for the new city.

The employment base of Navi Mumbai was planned to encompass manufacturing(industry), trade and commerce (wholesale and warehousing), as well as service sector(office) jobs. The Industrial Location Policy issued in December 1974 posed variousrestrictions on the start of new industrial units on Bombay island. A series of controls weremade for various regions within Bombay. No new, large or medium industrial units werepermitted on Bombay island. Only small-scale industries were allowed in place of old, largeindustries. Industrial growth was encouraged only in the MIDC industrial estates of NaviMumbai (CIDCO, 1973).

Almost 87% of the office jobs of Greater Bombay are located on Bombay island with62% in South Bombay. The plan called for the shifting of government offices from SouthBombay to Navi Mumbai. The authors of the regional plan cited the case of New Delhi toemphasize their idea (Patel, 1997). A CBD was planned in Navi Mumbai with the aim ofcreating 40,000 office jobs.

Although job opportunities were the driving force behind Navi Mumbai’s success, theavailability of cheaper, better quality houses was the biggest incentive (CIDCO, 1975). Toaccommodate a population of 2 million, assuming a family size of five, 400,000 housesneeded to be built. Table 2.4 shows CIDCO’s estimates on the capacity to pay for housing bydifferent income groups.

Table 2.4 Household Income and Capacity to Pay (Figures estimated in 1971 income where$1~Rs.7)

HouseholdIncome

(Rs. Per month)

% ofPopulation

Monthlycapacity to pay(% of income)

Capacity to payfor housing (in

rupees)

Affordable sizeof housing unit

(in sq. m.)Less than 200 20 10 1200 3201-300 16 11 2580 5301-400 15 12 4140 8401-500 14 13 5940 12501-600 12 14 7800 16601-800 9 15 10800 22801-1000 7 17 15600 31

Threshold of affordability1001-1200 3 19 21000 431201-1500 2 22 30000 601501+ 2 25 37800 75


(CIDCO, 1973)The table shows the ability of each income group to contribute towards ownedaccommodation. The average cost of construction was Rs. 550 per square meter and the costof development of land was Rs. 40 in 1970. Capacity to pay for housing divided by cost ofconstruction shows a very small (or no) house could be owned by most families. Otherwise,each family could own only developed land.

The Government of India’s policy on publicly financed housing has been to build 21sq. m. houses or larger (CIDCO, 1973). The housing has to be heavily subsidized to make itaffordable. This would have a great drain on the financial resources of the government. InNavi Mumbai, it was proposed to use cross subsidies. The higher income groups would paya surcharge for housing, which would subsidize housing for the lower income groups.CIDCO decided to use a maximum surcharge of 15% on housing for highest income group tocompensate for a maximum subsidy of 45% to the lowest income group (CIDCO, 1973).CIDCO decided to build a large part of the housing as public housing. At the same time,land would be leased under a 30-year repayment system to private cooperative housingschemes and private owners.

2.6 Design Principles of Navi Mumbai

The conceptual design of Navi Mumbai was developed at the height of Modernism.Le Corbusier had played an important role in the design of Chandigarh in Punjab in the mid-1950s (Le Corbusier, 1961). Some of the highlights of the design elements of this plan weresector planning, hierarchy of roads and important buildings of a gargantuan scale (Fry, 1977).Le Corbusier explained "the plan is based on the main features of the 7V rule (Appendix B)determining an essential function: the creation of sectors. The sector is the container offamily life" (Le Corbusier, 1961). The sector was based on the Spanish cuadra of 110 to 100meters. Each of these cuadras was a self-contained unit with primary schools, communitycenters and residential areas. The cuadra had a detailed zoning plan with single-use zoningon all lots. No fast traffic was allowed in the sectors. V4 roads were designed for shoppingand commercial activity. Children were able to walk to school on the V7 through green belts(Sarin, 1977). Many of these principles of Modernism were used in the planning of NaviMumbai. These were:

i decentralization by the design of self-sufficient townships(nodes),i residential neighborhoods (sector),i single-use zoning as opposed to the traditional multiple-use zoning

The result was a single-use zoning pattern with distinct areas for industrial, commercial,residential and institutional activity. The total land of Navi Mumbai was divided intothirteen townships. Each township had several sectors. Many of the sectors were residentialin character. The neighborhoods were self-sufficient and had their grocery store and primaryschool. A sector centrally located within each node took on commercial activities.

The sector planning of Modernism is very similar to the grid planning of traditionalIndian cities. In India the square was used as the basic unit in the layout of traditional cities.The square had a significance in Hinduism as this perfect geometric shape was thought to be


the abode of the gods (Henn, 1969). Even in the planning of Mohenjadaro (7th centuryB.C.), main streets formed perfect rectangles dividing the city into separate residential areasbased on caste. All houses in a neighborhood were occupied by a particular caste. In India,the four castes are Brahmin, Kshatriya, Vaishya and Sudra, which corresponds to theprofessions priest, warrior/king, merchant and peasant.

The indigenous plans all started with a central focal point (either of political orreligious symbolism), and progressively moved outward depending on the natural landscape.Many cities still reflect this street pattern. As the residential classification was based on thecaste, people were forced to work within that particular neighborhood. So each sector hadmixed use. Commercial and residential uses were adjacent to each other or one above theother. This is significantly different from the single-use planning of Modernism.

The Bombay Municipal Regional Planning Board put forth the broad conceptualregional plan of Navi Mumbai. The task of designing and detailing the physical design wascarried out by CIDCO. Mr. Parab, a true Gandhian, was the Chief Planner of CIDCO for 20years (1970-90) (Engel, 1991). Under his leadership, the main philosophical designprinciples of Navi Mumbai are based on Gandhian ideology (Parab, 1997). "Arguing to turnany weaknesses into strength, Gandhi would have urged: If nature chooses not toaccommodate us, let us accommodate nature!" (Gandhi in Engel, 1991). This is the visionthat is the traditional Indian design inspiration for Navi Mumbai. Here in Navi Mumbai theidea of a large “urban village” has been nurtured. The goal has been to create a city based onGandhian principles of swavalamban (self-reliance), swadeshi (fullest utilization of localresources, both materials and human) and swatantrya (self-motivation and mutual self-help)(Ganguli, 1973).

The functionality of the city is based on the principle of neighborhood design as seenall over the Western world. Neighborhood planning in the West was a concept put forth byClarence Perry, an American designer of the 1920s. This was a model layout for an areawith specifications for residences, streets, amenities and utilities with segregation ofvehicular and pedestrian traffic (Banerjee, 1984). Each neighborhood unit was within a onesquare mile radius. Neighborhoods could be placed near each other to form a larger urbanframework. This also facilitated the sharing of other, larger amenities by contiguousneighborhoods. The neighborhood unit is used as a building block to build New Townsacross the world (Perry, 1929). This principle of neighborhood planning and its derivativefrom Modernism was used in Navi Mumbai. In the case of Navi Mumbai, eachneighborhood was known as a sector (CIDCO, 1973).

Navi Mumbai consists of thirteen townships (or nodes). Each node is self-containedfor 100,000 to 200,000 people. Each node is divided into neighborhoods (or sectors). Thenodes contain residential, commercial, infrastructure and recreational uses (Figure 2.4). At alarger scale, nodes share some common facilities such as water reservoirs and transportfacilities. Some of the nodes have special features. Vashi is the center of Navi Mumbai'swholesale market. Airoli and Kopar-Khairane have industrial estates, while Nhava-Shevahouses the new container port. Each node was planned to accommodate a range of incomegroups. There would be no rich or poor nodes (CIDCO, 1973). The size of the node depends


Figure 2.4 Nodes of Navi MumbaiSource: CIDCO, 1973.

on walking distances to themass transit stop. The node should belarge enough to provide schools,shopping areas and other facilities.

The Development Plan of NaviMumbai is an example of the newconsciousness for sustainablesettlements (CIDCO, 1995). The planenvisioned an ecologically friendlycity where products of nature would beused, and then unused portions wouldbe recycled. One of the ideas ofputting the environmental city intopractice was the creation of woodlandcorridors (Parab, 1997). TheDevelopment Plan for Navi Mumbaicalled for the planting of one hundredthousand trees every year! (Engel,1991). This would also ensurereduction of soil erosion and thedevelopment of woodlands for bothrecreation and timber. The streamsflowing from the Western Ghats

mountain ranges would irrigate these trees. The plan called for the construction of holdingponds to retain excess monsoon run-off, which would be used in the dry seasons. Holdingponds would be used for pisciculture and recreation. Water treated from industrial andsewage waste would be used to develop green areas (Parab, 1997).

The design concept of Navi Mumbai was very idealistic. This was partly because ofthe scale and complexity of the project. There was also a high degree of uncertainty attachedto some of the policies and physical developments. It depended very heavily on externalfactors, which were closely linked, for its success. For example, unless sufficient industrialgrowth existed, a migration of population would not occur. For industrial growth largefinances were required. Private industries would not invest in this particular region unlessthey were assured of workers and so on. As financial and economic considerations dependedon the government in office, the plan had a very important political component. Politiciansuse the creation of jobs and better living environments as a common strategy for gettingvotes. Hence, only activities, which ensured their re-election, would be strongly supported.Any change in political power would affect the policies and development strategies of thisnew town.

2.7 Social Agenda in the Planning of Navi Mumbai

Considerations of social equity were very important in all aspects of development in acountry, which had been independent for only 20 years. The primary concerns were related

Airoli

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to providing better quality of housing, education and job opportunities, medical care andsocial welfare. The design of a completely new city was a very good opportunity toimplement these national concerns. The Constitution of India also spells out the need for thegovernment machinery to facilitate social, economic and political equity.

The State shall not discriminate against any citizen on grounds of religion,race, caste, sex, place of birth or any of them (Article 15, I).The State shall strive to promote the welfare of the people by securing andprotecting as effectively as it may a social order in which justice - social,economic and political - shall inform all the institutions of the national life(Article 38).

The planners of Navi Mumbai thought this was a fortuitous occasion to provide socialjustice to the millions of migrants and pavement dwellers of Bombay (CIDCO, 1973). In1970, more than 30% of the population of greater Bombay could not afford a pucca (durable)house (CIDCO, 1973). Thus, it was proposed that housing should be constructed so that thisincome group could afford it. Incremental housing was suggested as the solution.

Housing would be built for the various income groups. For the lower income group,cost-effective, ground floor houses would be possible initially. Construction would be madewith locally available, cheap material. More durable material could be used in the course oftime. The remaining two-thirds of the population could afford more expensive housing. Forthem, walk-up apartments of three to four floors would be designed.

The plan took into account the fact that one-third of the housing in New Bombaywould be sites-and-services plots (CIDCO, 1973). The Gandhian principle of self-helpwould be used to implement this agenda. The sites-and-services plots would have servicessuch as roads, water, electricity and sanitation (CIDCO, 1973). Individual families wouldthen have to build their own homes (swavalamban). The residents could design andimplement their construction in any way they chose (swatantrya). It recommendedconstruction using cheaper concrete, using bamboo instead of steel reinforcements andsetting up of local retail shops where residents would be able to buy inexpensive buildingmaterials for building their homes (swadeshi) (CIDCO, 1973). To aid residents further,CIDCO would sell the plot at a highly subsidized rate and with a twenty-year repaymentperiod. Housing for the middle income and high income groups would be in the form ofCIDCO housing, cooperative housing groups or private builders.

Navi Mumbai’s founders saw the construction of large amounts of new housing as anopportunity to break down demographic divisions and to enhance social equity. The DraftDevelopment Plan spelled out

"there is a tendency in India that induces people to live in like groups,enclaves or ghettos of age long tradition of ’birds of the same feather flockingtogether’. In planned towns and cities this should be avoided to a great extentby allocating housing in neighborhoods to members of differentcommunities."

(CIDCO, 1973)


To justify this consideration, planners cited the segregation of Bombay as an example. Whenthe East India Company encouraged merchants to establish residence in Bombay, merchantsfrom neighboring districts migrated into Bombay and constructed homes inside and outsidethe Fort walls. This led to the development of ethnic enclaves. The Governor of Bombayalso encouraged this development because it reinforced the traditional panchayati (self-government) system of administration by which the council of elders settled religious, andlaw and order problems of the community (Dwivedi and Mehrotra, 1995). This furthercontributed to the creation of ethnic enclaves within the settlement. Establishment of ethnicenclaves has led to a number of problems in India. These are discussed further in the nextchapter. "In each node it is proposed that accommodation be made available for the entirerange of income groups expected in the city. It is expected that this accommodation ofresidents from various social and income groups within the same physical area will not onlymake for a healthier environment, but will also ensure a uniform standard of social andphysical infrastructure and see that no one class of residents is better served than another"(CIDCO 1973: 17-18).

Provision of schools and colleges was a priority in the planning of Navi Mumbai. Thenodes (townships) were designed to provide one primary school per 5000 population, onehigh school for 12,500 population and one college for 50,000 population (CIDCO, 1973).These were the education facilities to be provided by the government. Other privateinstitutions would be encouraged also. Minimum standards for building construction weredeveloped by CIDCO.

Health planning was undertaken as public health projects, medical care, water supplyand sanitation, recreation and afforestation projects (CIDCO, 1973). The planning was for acomprehensive coverage by taking the services to households, schools and colleges andmaking health education a part of classroom education. The community health care centerwould primary health care. It would have out-patient department, diagnostic andinvestigation services. Mobile health care units would operate from this community healthcenter. The medical center would provide secondary health service. It would be a smallhospital and polyclinic where specialized health care would be provided to cases referred bythe community health care center and general practitioners. A large hospital for intensivecare and for teaching and research purposes would be set up (CIDCO, 1973).

The Greater Bombay region had some of the best social welfare programs in India.Institutions for juvenile delinquents, handicapped children, exploited women and leprosy-affected persons would be developed in Navi Mumbai to accommodate the growingpopulation (CIDCO, 1973).

The planners of Navi Mumbai did not intend to create an identity for the city relatedto physical objects. The Development Plan says (CIDCO, 1973: 17):

"CIDCO is anxious that the new city develop its own identity as quickly aspossible. It should contain its own jobs, shopping, recreational and othersocial facilities an should not become a dormitory for Greater Bombay."


Thus, there was no aim to create a monumental city. Its identity is only that of aspreading inkblot (Engel, 1991). It appears that the monumental style of Corbusier was notan influence on this design. New, planned cities of India such as Chandigarh, Gandhinagarcan be described by their grid system or monumental scales. However, the identity of NaviMumbai is subtler. It is more of a philosophical identity - an identity based on the Gandhianvalue of social equality.

The city of Navi Mumbai was planned to address the issue of social equality throughits physical design. The physical design would be the instrument to implement this objective.In particular, the allotment of residential apartments would be governed by a policy, whichwould help implement the objective. However, a strong institutional framework wasrequired for its success.

2.8 Plan Implementation through the Public Administrative Framework

The government authorities of Bombay realized that the effectiveness of regionalplanning depended, largely, on the institutions responsible for the plan. In the verybeginning, the Gadgil Committee Report (1965) had recommended the setting up of a NewTown Development Authority (NTDA). CIDCO was appointed as the NTDA.CIDCO undertook the task of (CIDCO, 1995):

i developing land and providing infrastructure such as roads, drainage, watersupply, electricity;

i developing residential plots for different income groups;i promoting commercial and other employment activity;i involving Government agencies for developing public transport and

telecommunications.

Other institutions have also been set up in the Greater Bombay region to facilitate planningefforts in the region. These are (CIDCO, 1992):

i Bombay Metropolitan Regional Development Authority (BMRDA) in 1975i Navi Mumbai Municipal Corporation (NMMC) in 1992.i Specialized services provided by Maharashtra Housing and Area Development

Authority (MHADA),i Bombay Electric and State Transport (BEST).

Before the creation of these different institutions, CIDCO had to coordinate allplanning and development programs. With the creation of these other agencies, CIDCO hasa more narrow and defined role. The role of CIDCO is to implement the plan of NaviMumbai. CIDCO has executed the implementation of the plan in various stages (CIDCO,1992). These stages include:

i Draft Development Plan (programs and policies)- Objectives- Data base- Other agencies- Visualizing the future

i Action Plans


- Land use plans- Residential layout plans- Infrastructure plans- Industrial location plans- Environmental assessment

i Implementation- Acquisition of land- Finance- Construction- Relocation strategies

BMRDA took over such functions as coordination of metropolitan planning, funding,execution of programs, development control and maintenance of the entire Greater Bombayregion including Navi Mumbai (UNCHS, 1993). Financial responsibilities and investmentdecisions are made by a large number of agencies including the Government of India, StateGovernment of Maharashtra, CIDCO and firms in the private sector, but coordinated byBMRDA.

Figure 2.5 Institutional Hierarchy in Implementation of Development Plan for Navi Mumbai

In 1992, an amendment of the Constitution of India affected the functioning ofCIDCO. The 74th Amendment of the Constitution of India (the 1992 Amendment Act onMunicipalities) spells out the devolution of power to the local bodies and democratization ofdevelopment planning. This Act emphasizes that the management must be done by electedrepresentatives of the people who will account for two-thirds of the board. This committee isresponsible for the preparation of the draft development plan. This ensures a bottom-upprocess with direct inputs from the citizens (UNCHS, 1993). These municipal corporationswill be responsible for their economic development and incorporate all ideas within the

Plan Implementation of Navi

Mumbai

City and Industrial Development

Corporation (CIDCO)

Macro-level Regional Planning

Inputs

Bombay Metropolitan Regional

Development Authority (BMRDA)

Micro-level Sub-regional

Planning Inputs

Navi Mumbai Municipal Corporation


Comprehensive Plan. The direct result of this Act is the creation, in 1992, of the NaviMumbai Municipal Corporation. This allowed CIDCO to give up its role as New TownDevelopment Authority (CIDCO, 1995).

A heavy-handed approach was used by the government to implement its social policy.As most of the housing was built by CIDCO, a government agency, the government couldcontrol, if not regulate, the distribution of the population on socioeconomic basis.Households desirous of buying a house built by CIDCO had to submit an application thatstated the dwelling size they preferred. CIDCO allotted these houses, depending on whenconstruction was completed, on a rolling basis. This was intended to ensure a randomdistribution of the various linguistic and religious groups of the population. The patternexpected would now be one based predominantly on income.

2.9 The Reality of Implementing the PlanThe planning of Navi Mumbai began in 1971. The results of each of the planning

objectives can be studied now. The first objective of the Development Plan of Navi Mumbaiwas to reduce congestion of Bombay by absorbing immigrants and attracting some of thepresent population of Bombay.

Table 2.5 Population Density in Various Sectors of Bombay(BMRDA, 1978 in UNCHS,1993)

1971 1981 1991Population(in ’000s)

Density(pop/ha)

Population(in ’000s)

Density(pop/ha)

Population(in ’000s)

Density(pop/ha)

CBD 1120 1659 1031 1527 849 1258Central Bombay 1950 1349 2254 1559 2309 1597Bombay Island 3070 1447 3285 1549 3158 1489Bombay Suburbs 2900 544 4958 930 6751 1266Navi Mumbai1 - - 128 600 328 617

Over the 1981-91 period, there was a considerable decline in the population of the CBD andBombay island. The increase in the population of the suburbs and Navi Mumbai accounts forthe decline in the CBD and Bombay island. Outmigration to other cities and countries isnegligible (BMRDA, 1978). The main reason for the shift was because of (UNCHS, 1993):

i dilapidation of older buildings in Bombayi cheaper and better housing facilities in Navi Mumbaii better employment opportunities in Navi Mumbaii lesser commuter distances involved

The second objective of the development plan was to bring maximum jobs consistentwith the Gandhian principle of self-sufficiency (swavalambhan). CIDCO’s support of theIndustrial Location Policy brought more jobs to Navi Mumbai. The sectors that hadmaximum growth in Navi Mumbai, were trade (39%), finance and services (27%) andmanufacturing (18%) (BMRDA, 1992 in UNCHS, 1993). The wholesale agriculture produce

1 residential area increased from 213 hectares in 1981 to 531 hectares in 1991.


market for vegetables, foodgrains, oil seeds, sugar and spices was moved from SouthBombay to Navi Mumbai (CIDCO, 1973). A separate railway siding and truck terminal wereconstructed to facilitate effective relocation. This involved the relocation of 30,000 jobsfrom Bombay and the reduction of 5000 truck trips per day. A new iron and steel stockyardcomplex has been developed in Navi Mumbai. This means the relocation of 25,000 jobs anda reduction of 1000 truck trips per day to Bombay. However, the economic agenda, whichwas based on agriculture and cottage industries, is no longer effective because of thegovernment’s redoubled commitment to a policy of industrialization. Navi Mumbaicontinues to be exploited as a major industrial zone (Engel, 1991).

CIDCO's third objective was to provide physical and social amenities in NaviMumbai. The land use of Navi Mumbai shows these amenities (Table 2.6 and Figure 2.6).

Table 2.6 Land Use of Navi Mumbai, 1993 (in sq. km.)Land-use Zone 1979 1985 1986 1991 1992 1993Residential 101.15 133.99 127.08 129.87 128.71 127.61Commercial 6.51 6.51 6.51 5.75 5.75 5.75Industrial 43.21 43.14 43.14 43.14 43.14 43.14Port 12.00 22.7 22.7 22.7 22.7 22.70Wholesale market 6.08 4.54 4.54 4.6 5.76 6.86Woodlands / Park 90.26 61.24 68.15 69.35 69.35 69.35Institutional .76 1.09 1.09 1.09 1.09 1.09Fishing and allied 6.14 3.44 3.44 3.44 3.44 3.44Transportation 30.86 30.35 30.35 29.73 29.73 29.73No development 46.73 36.70 36.70 34.03 34.03 34.03Total 343.70 343.70 343.70 343.70 343.70 343.70

(CIDCO, 1997)Primary, secondary and high schools have been provided in all sectors of Navi

Mumbai. All primary schools are within walking distance. This eliminates the need ofexpensive transport for small children. There is at least one college in every node and Vashinode has both medical and engineering colleges (CIDCO, 1995). Medical facilities areprovided by private medical practitioners. Every node has a hospital run by the MahatmaGandhi Medical Trust. Community health car centers are also there (CIDCO, 1995).

In its fourth objective to provide an ecologically friendly environment, CIDCO hasnot been entirely successful. The area of woodlands has been constantly decreasing (CIDCO,1995). Most woodlands are in the form of mango groves which form a part of neighborhoodparks. In the conceptual plan, streams flowing from the hillsides were to irrigate thewoodland corridors. No significant effort has been made to utilize this resource. However,holding ponds have been constructed. Promenades have been built along them and they arebeing used as recreation areas (Parab, 1997).

The fifth objective is the primary focus of this thesis. The objective to prevent ethnicenclaves and to promote a pattern based on socioeconomic characteristics was fairlyambitious. In order for its success, a perfect control of the market is required. The analysisof the data will show the outcome of the objective.


Figure 2.6 Land Use of Navi MumbaiSource: CIDCO, 1995.

Though the Navi Mumbaiproject was begun in 1970, thedevelopment process has been slow.The poor transportation links betweenBombay and Navi Mumbai has beenthe main contributing factor. Growthin other development sectors ofBombay has also had an adverse effecton Navi Mumbai’s growth. Theabsence of a port and railway linksslowed growth. However, since 1990there has been accelerated growth dueto the commissioning of Nhava-Shevaport, the extension of the railway lines,establishment of more industries andconstruction of more houses. CIDCOprovides serviced sites for bothgovernment and private ownership.Houses have been constructed fordifferent sectors of society -economically weaker section, lowerincome group, middle-income groupand high-income groups. Commuterservices have become operational sinceMay 1992, and housing occupancyrates are high. Hence, the city is nolonger a plan on paper, but a living andworking reality.

2.10 ConclusionThe Draft Development Plan of Navi Mumbai described many broad outlines for the

development of a city for the common citizen. The design principles described in the DraftDevelopment Plan were based on the philosophical reasoning of Mahatma Gandhi and thefunctionalistic approach of Modernism. Many attributes of these two design principles arenot necessarily harmonious. While Modernism called for single-use zoning and a patternbased on socioeconomic characteristics, the Gandhian principles supported culturalheterogeneity and mixed use zoning.

Social aspects of city planning were given importance with special attention given toconsiderations of employment opportunities, housing requirements, utilities, recreation andcommercial needs. Designing, development and implementation of ideas were done in anincremental manner. Periodic socioeconomic and household surveys were used to determinethe status of constructed environment. Problems of design and development were identified,and improvements made in the next phase of design.

Residential

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This design also strongly supported the need to use the government’s power andmachinery to promote the uniform distribution of people and prevent ethnic enclaves. Aheavy-handed implementation strategy of this objective was done by taking complete controlof the residential allotment. The success of this strategy depended on maintaining thiscontrol. This also implies that the urban social pattern was predetermined.

The research setting under consideration is the result of the hybridization of Indianand Western ideas. Navi Mumbai is a modern, planned city within the context of a specifichistoric and cultural setting. Very little analysis has been done on the outcome of CIDCO'ssocial agenda to ensure diffusion of ethnic groups and the urban social pattern that emerged.The aim of this research is to examine the present urban social pattern of Navi Mumbai.

Chapter 3: The Conceptual Framework

3.1 Introduction

A human settlement is an establishment created by people for their inhabitation.Human settlements contain people and societies in a physical environment consisting ofnatural and man-made elements (Doxiadis, 1968). Such a human settlement is not just three-dimensional, but four-dimensional, because it changes continuously in a temporal dimension.A holistic approach to the study of settlements involves understanding the interrelationshipsbetween its elements within the temporal context. The study of the physical form andstructure of cities is the study of urban morphology. The final outcome of a morphologicalstudy is the formulation of a theory which connects facts to form hypotheses, principles andexisting theories for improving the design of cities (Doxiadis, 1968).

The aim of the thesis is to examine the urban social pattern of Navi Mumbai, (NewBombay), India. Urban social pattern is the pattern formed by the interaction of varioussocial variables such as household characteristics, ethnicity, religion, language and housingcharacter. This literature review will first trace the human settlements in India. Most citiesin the Third World and India have been indigenous in origin and organic in growth. Many ofthese cities have been under colonial rule, and bear characteristics of western influence. NaviMumbai is one of the first cities in India built for the common citizen. It is a city designedwith the design principles of the time. These design ideas seem to have a strong influence ofModernism (CIDCO, 1973), and those of Mahatma Gandhi.

3.2 Urban Form and Urban Pattern

Every human settlement consists of certain elements. Interaction of these elementsform a pattern - the urban pattern. The urban pattern is a result of the relationships betweenpeople and their social, economic and physical environments. Buildings and spaces arecreated by people and quite often characterize them (Kostof, 1991). If the residents build thebuildings themselves, then they reflect their lifestyles. However, if government agencies orcontractors build them, they are more generic and may not represent the lifestyles of everyhousehold.

Whatever the mode of construction, residents soon influence their urban environment,changing and modifying it to suit their way of life (Lozano, 1990). Simultaneously, peopleadapt to the physical environment around them. The human-environment relationship is atwo-way process termed as the socio-spatial dialectic (Knox, 1995). Thus, urban form is notmerely the architectural form of the city (Lozano, 1990). It is also a cultural manifestation.

Land ownership patterns, technology, transportation, communication and socio-economic relationships influence urban patterns. Intricacies in relationships have increasedthe complexity of the urban form over time. The pattern of spatial distribution is recognizablein most contemporary cities (Alexander, 1987). Where market forces work, income is one ofthe most important determinants. Education, occupation and values of housing influence thespatial character. Socioeconomic factors have a very important contribution to the pattern.

Malathi Ananthakrishnan Chapter 3: The Conceptual Framework 21

Demographics, linguistics and ethnic background also influence urban patterns. Thus urbansocial patterns are complex manifestations of underlying cultural values intermingled withglobal economic forces (McGee, 1971).

Although details may not be identical, every city has certain elements. Doxiadisdefines five elements in the study of human settlements. They are nature, human beings,society, buildings and infrastructure. Urban spatial patterns occur because of the repetitivespatial distribution of these elements. The patterns have similarities, which may be universalor local. “The typical sector represents the formal characteristics found throughout the areaand thus acquires some universality” (Lozano, 1990). Since the characteristics are universal(within the frame of study) they may be studied by a spatial representative sector. Thisrepresentative sector is defined as the smallest area that exhibits the characteristics of theurban settlement. In most studies this unit is the neighborhood which displays both physicaland social aspects of the whole urban development. They are the units of analysis of themorphological study (Knox, 1995). Urban patterns represent a continuity of time and space.Time and place may provide them with different characteristics making each city unique anddynamic. In the study of Navi Mumbai, the node (township) and the sector (neighborhood)will be used as the study areas using aggregated household survey data.

3.3 Factors Influencing Urban Form

Many factors influence the form of cities. Traditional settlements were shaped by (Lozano,1990):

i the way in which nature and man-made features satisfy needs for protection anddefense

i the way in which physical and economic landscape allows for communicationwith other regions

i the way in which the topography of a site suggests the construction of a humansettlement

i the way in which climate leads to building solutionsThese factors influence the cultural and spiritual form of the cities as well. Traditional citieshave used physical forms to interpret cultural and religious beliefs (Lozano, 1990). Forexample, a hill top site was the utilitarian response to any important building - a fort or areligious building. These features contributed to a particular urban and social pattern.

The physical form is a variable of the social and built pattern of the city. The builtform is influenced by factors as (Alexander, 1987):

i land ownershipi existing land usei planning regulations

i street patternsi economic considerationsi political and historical events

The physical expansion of the city is always bound and guided by land ownership, andnatural and manmade obstacles. A city replaces existing land use. Thus, it is necessary todetermine existing land use as a pre-condition to urban growth and form. The change of landuse from rural to urban depends on the existing land use, and the ownership. Some farmersmay sell their land more easily than others may. The rural land may also have been


subdivided. Plots of varying sizes and shapes influence the layout of the streets and ofindividual buildings (Knox, 1995). Planning controls influence development to a greatextent. Master plans and regional plans provide long-range strategies for development.

Various economic, social and political circumstances influence the social pattern(Scargill, 1979). While some processes are culture-specific, others are global in scope.These factors are (Alexander, 1987, Kosambi, 1986):

i ethnic composition of the cityi religioni race

i migrationi economic considerationsi political and historical events

The housing market also influences the social pattern of the city. A household’s choice ofplace to live is determined by its income level, personal preferences and many institutionalconstraints. Owner-occupier, private rental and public sector housing operationalize housingsectors.

A particular social pattern brings about a particular built form. Certain built formsencourage certain social patterns. The social pattern and the built form are interrelated andcontribute to the urban morphology of a city.

3.4 The Evolution of the Urban Form of Indian Cities

The traditional theory of urban origin is generally attributed to Childe (Herbert, andThomas, 1990). Childe put forth a theory that urban centers were a result of agriculturalchange. People as food gatherers advanced to become farmers. Domestication of animalsand cultivation of land created villages. Soon, surplus food production was achieved. Thisallowed some of the people to develop other professions. Priests, craftsmen and merchantswere born. However, other scholars contend that it is doubtful that surplus can be attributedas the single factor which caused the emergence of urban settlements (Jacobs, 1983).Reasons such as trade and defense have also been used to explain the formation of cities.

For thousands of years, cities were very simple although they rarely served singlepurposes. Instead, they supported a range of activities. Housing, commercial buildings,government offices and warehouses formed the built environment of the city. Pedestrianmovement limited the size of the city. Clear differentiation between urban and rural existed,often because of a city wall. However, within, a city contained social distinctions in terms ofclass, race and religion (Vance, 1990). Urbanization took place at different chronologicalperiods. The factors influencing urbanization were also different. The variation ininfluencing factors and historical circumstance gave rise to different urban forms in differentparts of the world. The evolution of the urban pattern of Indian cities is divided into thesocial pattern and the built form.

3.5 The Sociocultural Factors

India is among the most stratified of all known societies in the world (Srinivas,1992a). The caste system of India separates and hierarchies the Hindus. The external


manifestation of the separation and hierarchy through particular attributes of the castes bringsabout social stratification of the urban social pattern (Marriott, 1992). Clothing, language,rituals, marriage and death ceremonies distinguish one caste from another. In India, theforms of social stratification are many. Along with the caste exist occupational stratification,linguistic stratification and religious stratification. The social stratification is very deep andvaried. The Indian theory of social stratification depends on caste, linguistic, religious andethnic diversity of the country (Gupta, 1992).

Stratification implies a differentiation based on a set of criteria. The population maybe stratified based on income, language, religion or occupation (Bougle, 1992). Hierarchyallows elements of the whole to be ranked with relation to each other (example: income andprestige). However, all elements can not be arranged vertically. The differences may also beplaced in a horizontal system (example: language, religion). Thus, theoretically, vertical andhorizontal systems of stratification exist. The real world, unfortunately, differentiates itselfinto only hierarchical status containing inequality (Gupta, 1992b).

The term ethnic group refers broadly to people “with some similar characteristicswhich go beyond their mere place in a societal division of labor” (Brass, 1974:8). Ethniccharacteristics refer to language, culture, territory, diet and dress, and in the case of India,sometimes reinforced by common work roles. The characteristics caste, class, religion andlanguage are discussed below. Berreman (1965) says "Caste systems rank people by birth-ascribed group membership rather than by individual attributes. Class systems by contrastdefine the rank of their members according to their individual attributes and behavior".

3.5.1 Caste

Castes are the hierarchical divisions of people based on professional and familymembership. The spirit of the caste system is determined by the attitudes of each caste to theother. Repulsion between castes forced isolation and the creation of distinct residentialenclaves (Bougle, 1992). The dominant caste legend is the Purushasukta legend whereby theBrahman, Kshatriya, Vaishya and Sudra are said to have come from the mouth, arms, thighsand feet of the Creator. Although no hierarchy is mentioned in the Sukta, a hierarchy fromBrahman to Sudra has been interpreted (Bougle, 1992). However, this popular castehierarchy is not clear throughout the Indian subcontinent (Srinivas, 1992b). Variouscombinations of the hierarchy have come about due to regional differentiation in certainattributes of social living. Vegetarian castes occupy higher positions. Certain occupationssuch as butchery and cobblery lower the rank. Certain customs lower or raise the status ofthe caste. The caste system varies from village to village and is a local phenomenon.

3.5.2 Class

"Class refers to a system of stratification which is economic in character" (Gupta,1992b:14). The criteria for the differentiation can normally be translated into money orwealth. However, these single criterion hierarchies can be misleading as they depend on cut-off points related to individual analysis (Gupta, 1992a). As many individual criteria are


linked to other attributes, it may be better to create a composite index of education,occupation, prestige and income to form a socioeconomic status.

3.5.3 Religion

Religion and language have provided the motive power for nationalism in India(Brass, 1974). There are many religions in India. India is the birthplace of two majorreligions –Hinduism and Buddhism – and two minor religions - Jainism and Sikhism.Buddhism, Jainism and Sikhism stemmed off from Hinduism and are very similar toHinduism. However, Islam was a religion that came to India from outside and is culturallyvery different from Hinduism. From the beginning Islam has been a conquering andproselytizing faith (Hodson, 1985). A certain degree of animosity between Hindus andMuslims has existed since the first Muslim ruler of 1018 AD. “In most folk-memory theMuslims of India had been ruler, not subjects” (Hodson, 1985:11). During the Mughal rule(16th to 18th century), the Muslims were in power over most of India. After the decline of theMughal Empire and the loss of political power to the British, Muslims became apprehensiveof Hindu domination. An overwhelming view of Hindu-Muslim relations in the nineteenthand twentieth centuries is that Hindus advanced due to their enthusiasm to take up westerneducation and government employment (Kaura, 1977).

The Hindu religion has always been a pacifist and tolerant religion, absorbing otherreligious doctrines and never proselytizing. A Hindu revival period in the late nineteenthcentury to arouse enthusiasm for political action made the Muslims more insecure. At thistime they felt the need for a political party of their own. In 1906 they formed the All-IndiaMuslim League. While the Congress party represented the majority of the Indian population,the Muslim League represented only the Muslim population (Brass, 1974). The Leaguedemanded for a separate electorate and for more employment in public service. Hindus andMuslims drifted apart in the issue of independence from British rule, which culminated in thepartition of united India into India and Pakistan. The wake of Independence brought with itviolence and terror in the Indo-Pakistan borders in Punjab and Bengal. Anger and frustrationbroke out as violence as Hindus moved from Pakistan into India and Muslims moved fromIndia to Pakistan (Hodson, 1985).

3.5.4 Language

A systematic inventory of Indian languages began in the mid-eighteenth century. Thecensus of India 1951 (immediately after Independence) recorded a total of 179 languages and544 dialects in India. The major languages of India are Hindi, Bengali, Tamil, Gujarati,Marathi, Malayalam, Kannada, Telugu, Urdu and Punjabi. The linguistic distribution is notonly diverse but also very complex (Das Gupta, 1970). The characteristics of thepopulation regarding bilinguals, degree of control over the language and relationship betweenthe languages affect their social communication.

The framers of the Indian Constitution chose Hindi and English as the officiallanguages of the government (King, 1997). Hindi was chosen because it was the languagespoken by the largest percent of the population while was a result of the British legacy.


However, a demand for a national language also arose. In a multilingual society there maybe a plurality of national languages. The Eighth Schedule of the Constitution of Indiadeclared the fourteen major languages listed as national language (Gumprez, 1971).However, confusion has always existed about the status of Hindi as official or nationallanguage. Writers in Hindi commonly refer to Hindi as Rashtrabasha (state language) whichmay signify language used by the state, a synonym for official language and like statereligion, a state language with an unique status (Das Gupta, 1970). This confusion interminology is the basis for most language-related problems in Independent India. Althougha majority of the rivalry has been for and against Hindi, there also been conflict betweenother regional languages.

3.5.5 Implications of the Sociocultural Factors

The implications of caste and class are closely related to those of power and wealth(Dumont, 1988). Certain castes are dominant in a society. Traditionally these castes hadeither wealth or power. In many places, the Brahman priests had more power because it wasbelieved that they were the representatives of the Creator on earth. In some villages, allcastes looked up to the farmer caste because they were important landowners and werewealthy (Srinivas, 1992a). The inequality and economic differentiation cause conflictbetween the castes and classes. The separatism movements seen all over India are all basedon ethnicity and inter-caste rivalry (Bose, 1989).

The partition of United India into India and Pakistan came with many problems.Pakistan officially declared itself as a Muslim state. Although a minority of Hindu leaders inIndia felt that India should be declared as a Hindu state, a majority of the leaders preferred acomposite nationalism. This rationale of composite nationalism influenced policies related toreligion and language (Das Gupta, 1970). When the ethnic groups occupy distinctneighborhoods, ethnic conflicts are easily targeted towards these select neighborhoods. Thisissue can not only be seen at the time of partition in 1947 but also was seen during the recentcommunal violence in 1993. The Babri Masjid in Ayodhya was broken down by Hindufundamentalists. Repercussions were felt all over the country. Hindu-Muslim riots broke outeven in Bombay which has normally been a very peaceful city. Small Muslim enclaveswithin a majority Hindu neighborhood were targeted, and vice versa. This was not seen inmore heterogeneous neighborhoods, as it was difficult to isolate only one family.

Language conflicts have also occurred in India. In the early 1950s, many politicalleaders advocated for the use of Hindi as a national and official language. The uniongovernment declared that fifteen year deadline after Independence would be given fortransition of official language from English and Hindi to only Hindi. There was strongopposition from non-Hindi areas in general and South India in particular (Hindi is a Indo-Aryan language while the languages of South India belong to the Dravidian group). TheSouth Indian state of Tamil Nadu was most vocal in the Anti-Hindi agitation. The TamilnadStudents’ Anti-Hindi Agitation Council objected to both the removal of English as an officiallanguage and the declaration of Hindi as the sole official language. The better control theTamil people had over English, they believed, had led them to better job opportunities.Agitation and violence broke out in many non-Hindi states over this issue. Compromise was


finally reached in 1963 under the Official Languages Act. Despite the Act, violence sparkedoff by language issues has continued to occur in India.

The ethnic segregation and conflict has existed from the beginning of the IndianCivilization. In the initial stages it was in the form of caste differentiation as prescribed bythe Hindu/ Vedic texts. The caste system over the next ten to fifteen centuries becamedeeply rooted in the Hindu population and became a part of life. The multi-dimensionalsociety was soon complicated by the emergence of other religions, both from within andwithout the country. Hinduism, Buddhism, Jainism, Sikhism were born in India while Islam,Judaism and Christianity found their way into India. Stratification of the society had toaccommodate these religious factors. The Indian society was also stratified horizontally bylanguage. A number of languages coexisted in all parts of the country. Related to castes,class, religion and language is the issue of group identity which is the cause of most ethnicconflicts. While some groups spoke of an all-India nationality other speaks of a regionalnationality (Brass, 1974). This does not imply that social assimilation does not occur. Socialassimilation and mobilization are a part of any evolving civilization. However, thedifferentiation and assimilation in progress in a multi-ethnic society receives a prominentplace in any political conflict.

3.6 The Built Form

The historical evolution of the built form of Indian cities can be divided into threedistinct phases. The earliest is the Hindu phase (3000 B. C to 12th century AD), whichcontributes many elements to the urban form. These characteristics are derived from theneed for defense and administration and the importance of religion (Kopardekara, 1986).The temple as the symbol of religion dominates the urban form. The temple also influencesthe siting of other land uses. Prime commercial and residential land was located near thetemple. The science of architecture and planning, Vastushastra, governed the alignment ofroads, orientation of buildings and arrangement of internal rooms based on astrological andreligious criteria (Volwahsen, 1969). The square was used in the creation of thevastupurusha mandala, which was the terrestrial representation of the cosmic universeinhabited by Brahma, the creator. The mandala could be divided into smaller squares, padas.

In planning the town avastupurusha mandala which wasmost auspicious, and which had asmany padas as there were to beresidential sectors was selected. Thestreets ran from north to south andfrom east to west. The town wallenclosed the mandala, and fourgateways were situated at the cardinalpoints. The final shape of the towndepended on the natural features of thesite. If it could not be a perfect square,

a perfect rectangle was accepted. Certain other shapes were also considered to be auspiciouslike the circle, cyclical and swastika (Figure 3.1).

Figure 3.1 Circle and Swastika


The residential districts were divided among the four castes. Generally, theBrahmans worked and lived in the northern district, Kshatriyas in the eastern andsoutheastern part, Vaishyas in the southern part and Sudras in the western district. There wasfurther subdivisions within each district depending on the sub-caste. The Brahmans andKshatriyas lived in the parts of the town which were climatically more comfortable -sheltered from the hot sun, and the south-west monsoon.

Characteristics from medieval times are Islamic in nature (14th to 17th centuries A.D.). During this time, the Hindu tradition continued, and Hindu elements of this period arenot distinct from earlier ones. The Islamic elements included the mosque and domesticarchitecture which emphasized the purdah through enclosed courtyards, jali (carved screens)and projecting balconies (Kopardekara, 1986). The residential character throughout thisperiod was segregated. The urban segregation was based on function and occupationpremises. Areas for selling of specific goods – cloth, jewelry, pottery, metalware, and woodformed niches in the urban pattern. Residential areas associated with the commercial areawere contiguous or within the commercial area (Hall, 1980). In India where occupation andcaste are synonyms, this has led to segregation and creation of enclaves within the city.

The colonial influence (17th to early 20th century A. D.) was the third phase ofhistorical urban form, especially seen in the port cities associated with the East IndiaCompany (Mills, 1988). The morphological components include buildings used for trade -warehouses, counting houses. This led to the development of commercial centers and zoningbased on Western market principles. On the periphery of these urban centers, militaryestablishments - the cantonment - were developed (Hall, 1980).

At the time of independence in 1947, India inherited a complex urban fabric.Diversification of professions due to industrialization in the post-independence era hasresulted in further complexity (Becker, Williamson and Mills, 1992). Residential segregationis no longer based only on occupation and caste, but also on socioeconomic factors(Ramachandran, 1989). Large migration of people from the rural area, and insufficientinfrastructure in cities has led to the creation of slums and shantytowns (Misra, 1978). Manyresearchers have tried to fit Indian urban growth into a theoretical model. “In the case ofIndia, many researchers have pointed to the lack of penetration of urban values into thecountryside, and the apparent timelessness and permanence of village life” (Hall, 1980). Ithas been shown that rural values have penetrated the urban philosophy due to large-scalemigration.

The characteristics of the social and built form of the city contribute to its pattern. Ageneralization of these patterns has been made. These are the theories which pertain to thebuilt and social form of the city. The three leading theories described below are based on thebuilt form of the city. As the built form depends on the social characteristics portrayed by itsresidents, the same theories are being used to describe the social patterns as well.

3.7 Theories of Urban Social Patterns


CBD

Low income

Middle income

High income

Transition

Figure 3.2 Concentric Zone TheorySource: Burgess, 1929

Various spatial theories of the social pattern of cities have been advanced; somestatic, others dynamic in nature. The same city may express different models at differenttime periods (Scargill, 1979). The three leading Western models are:

i Concentric zone modeli Sector modeli Multiple nuclei model

These models have become frameworks for studying urban social patterns across the world(Hartshorn, 1992).

3.7.1 Concentric Zone TheoryThis theory put forth by Burgess in 1925

related population mobility and societalorganization to the physical expansion of the city(Burgess, 1929). Burgess was interested indetermining a pattern for the social structure ofthe city, and studying how the city grew (Scargill,1979). Thus, it is a descriptive framework toanalyze spatial organization of land use in a cityand its change over time. It was partly based oneconomic factors. The model made manyassumptions such as uniform land surface, freemarket, accessibility to a single-centered city,heterogeneous population and a commercial-industrial base (Herbert and Thomas, 1990).Burgess’ research on the distributional pattern ofvarious groups of society led him to conclude that

the city was made up of concentric zones with the central business district (CBD) at thecenter (Figure 3.2).

The CBD core had all major commercial, political and social activities. This wassurrounded by a transition zone, which had factories and slums. It also had older residentialdistricts, which were being taken over by the expanding CBD. The next zone had lowerincome housing, and successive zones had higher income residences (Burgess, 1929).Families moved out into the next zone when their zone was invaded. The basic premise inthis model was that of succession and invasion whereby population groups gradually movedout as their economic and social status improved. Mobility and migrant influx were thoughof as the main cause of the social pattern (Hartshorn, 1992).

This model was based on Burgess’ experience in the American mid-west cities, andespecially in Chicago. In the early 1920s, most American cities in the mid-west absorbedmany immigrant groups from Europe. These immigrants first found cheap housing in theinner city. With affluence, they moved to better housing districts (Burgess, 1929). Themovement was towards the periphery. Diversification in employment opportunities gave riseto the growth of mixed land use development. This also forced an outward expansion. Thepublic transport system had also improved significantly and allowed the middle-class to


Income group 1

Income group 3

Income group 2

Figure 3.3 Sector TheorySource: Hoyt, 1939

residential

commercial

industrial

ethnic group

Figure 3.4 Multiple Nuclei TheorySource: Hartshorn, 1992

travel from outer zones to the CBD for work. These reasons complemented a concentriczone development model (Scargill, 1979).

The model is very simple and can be used to predict how urban land markets work. Itwas intended to serve as a framework for studying urban growth and change (King andGolledge, 1978). However, Burgess has been criticized for not having consideredtopographical criteria. The original model did not take into account specialized clusters ofindustry. It also did not explain the impact of transport networks on these zones (Scargill,1979). The real world is more complicated than what was represented by Burgess’ verygeneral model. Hence, empirical studies did not confirm his model one hundred percent(Herbert and Thomas, 1990).

3.7.2 Sector TheoryHomer Hoyt put forth a land use theory

after studying over 100 cities in the U. S (Hoyt,1939). Hoyt primarily studied residential landuse. Hoyt studied the city as an economistconcerned with how the housing market worked.Rental value was the main criterion for studyingthe pattern (King. and Golledge, 1978). He saidthat residential sectors of similar rent aresituated in wedges radiating from the center(Figure 3.3). The wedge pattern representsresidential area growth (Scargill, 1979).Neighborhoods for each income group arecommon. The model also accounts for growthalong transport routes. For example, industriesmay cluster around the railway line or low-income housing along a riverbank. This modelalso accommodates growth (Hartshorn, 1992).Hoyt also stressed the need to consider zoninglaws and slum clearance laws in making models.

3.7.3 Multiple Nuclei TheoryThe multiple nuclei theory was put

forth by Harris and Ullman. This modelproposes that patterns in many cities bearranged around several centers (Scargill,1979). This is because concentration of certainactivities may prove to be more beneficial.Concentric zones or sectors may emerge fromthese nuclei. This is not a generalized model.It is more specific to some cities (King andGolledge, 1978). It gives strength to citieswith original nucleus in the center, andsubsequent decentralization (Figure 3.4).


3.8 Case Studies of Urban social Patterns

The study of the urban social pattern of a city primarily focuses on the residentialland use (Herbert and Thomas, 1990). Analysis of individual cities shows that the pattern isnot uniform and is characterized by residential segregation. In Western cities the reasons fornon-uniformity have been identified as socioeconomic status, ethnic status and family status(Timms, 1971). The non-uniform pattern is consistent over many cities because similarhouseholds exert similar housing choices. However, every city has some constraints. Forexample, housing choices may not be made on economic basis, but on cultural ones.

It is assumed that any planned city consists of neighborhood units. The concept ofneighborhood units became popular since the1920s in planned settlements (Perry, 1929). Itserves as the building block to construct the whole town. A neighborhood is the basis forformally organized residential space. Hence, the neighborhood unit is used as the unit ofanalysis in the study of human settlements (Herbert and Thomas, 1990). It is not only aphysical design concept, but also an expression of socioeconomic and cultural values of thepeople. The values are also related to family, neighborliness, community and social andcivic responsibilities such as aesthetics, safety, security and identity.

This concept, however, has been under strong criticism (Hartshorn, 1992). Critics saythat neighborhood unit strongly emphasizes physical environment; it does not address theneeds of a social environment. A neighborhood unit is not the only model or universallyappropriate unit of analysis. It is only the most convenient one. Individualistic frameworks,which analyze the physical environment under consideration, are suitable modifications ofthe concept (Timms, 1971).

3.8.1 Western Cities

Many studies of the social and physical urban pattern have been done. The city wasviewed as a part of society, and social change was expected to be reflected in studies whichwere repeated over a time period (Herbert and Thomas, 1990). The data source was censustracts. In the analysis of urban social patterns, three indices were used. These were socialrank, family status and ethnic status. Social rank used the variables, employment, education,value of home, housing conditions and material possessions; family status used the variablesrelated to demographics and type of house; ethnic status used religion and social groups. Theuse of these three indices for analysis is a social area analysis.

The broad generalization of the social rank produced a sector model. The mainassumption here was that social rank is related to transportation links which influenceresidential location in a sectoral manner (Scargill, 1979). This type of urbanization is alsorelated to the housing market described by Hoyt (1939). Family status in American citiesshows a concentric distribution. As a family’s needs for space increase, they move outwards.The outward mobility is related to different stages of life - marriage, parenthood, social statusand retirement (Scargill, 1979). Ethnicity causes the social phenomena of segregation. Inthe built environment this corresponds to ethnic neighborhoods (Timms, 1971). This is


predominant in cities where migration is high. Ethnicity, however, does not always emergeas an independent component (Scargill, 1979).

A study of Baltimore (Knox, 1995) shows that the four important factors in the socialpattern are underclass, socioeconomic status, youth/migrants and black poverty. Thechanging pattern of family cycle reflects concentric zones while that of social rank is insectors. Studies of Brisbane, Australia (Timms, 1971), Winnipeg, Canada (Herbert andThomas, 1990) showed similar results.

3.8.2 Third World Cities

Cities in the Third World are frequently dual environments; traditional and moderndesign elements juxtaposed in seemingly dichotomous ways, but socially with more complexrelations to one another. Traditional places are typically more dense with narrow streets andhousing spaces around central courtyards. Public open spaces are generally found only

CBD

Low income

Middle income

High income

Transition

Income group 1

Income group 3

Income group 2

residential

commercial

industrial

ethnic group

Ethnic Status

Family Status

Socioeconomic Status

Figure 3.5 Urban Social PatternsSource: Knox, 1995, Hartshorn, 1992.


around religious buildings. The modern place is more spacious. A classic example can beseen in the design of New Delhi, which is adjacent to, and surrounds old Delhi (Figure 3.6)(Herbert and Thomas, 1990).

Processes quite different from those inwestern cities govern the pattern of Third Worldcities. Even single cities, as opposed toconglomerations, are very complex and haveevolved over a very long time. Thus, social andeconomic variables may not be the only factors,which contribute significantly to the urban pattern(Kopardekara, 1986). A large number of modelsof Third World cities have been made (Lowder,1986).

Social morphological models constructedfor the Third World cities show that there is acentral concentration of commercial activity and anumber of residential neighborhoods. The modelshows that the indigenous elite were closelyassociated with the commercial area. The moreeducated and professional classes followed theWestern ideas of suburbanization and formed theirown neighborhoods (Lowder, 1986). The migrantsand poor did not live in the core of the city, but

formed shantytowns in the peri-urban fringes and in unserviced areas (under bridges, alongriverbanks).

But, the morphological pattern of each ThirdWorld city is different mainly because of thepresence of an indigenous city enclosed by acolonial city, and subsequently surrounded by anindustrial city (Lowder, 1986). Themorphological model of Asian port cities shows amultiple nucleus (Figure 3.7). The nuclei areoriginal village, traditional commercial areas andmodern commercial areas. An analysis ofCalcutta showed a pattern based on land use,family ties, ethnicity and literacy. The socialpattern showed concentric zones for land use.Literacy and ethnic patterns emerged in a sectoral

form. A study of Colombo (Herbert and de Silva, 1974) found that social status, land use,substandard living conditions and ethnicity were the broad variables that defined the socialpattern of the city.

The colonial cities in Latin America show a centralized social pattern (Portes, 1975).The center of the city was the plaza. Around the plaza was the important buildings includinga church. The residences of the richer class formed the first concentric zone around theplaza. The second and third concentric zones were occupied progressively by poorer people.

Figure 3.6 Plan of Delhi and NewDelhi, 1980.Source: Drakakis-Smith

Figure 3.7 Asian PortsSource: Lowder, 1986


Here, the residences became smaller and publicamenities were reduced. The outer ringbordered on farmland (Figure 3.8). A consistentrelationship existed between socioeconomicposition of the household and their distance fromthe center of the city; the farther away from thecenter, the poorer the household (Cornelius,1975). In the 18th and 19th centuries, many largecities became crowded. Wealthier familiesbegan to move out of the center and settle inmore isolated locations. The pattern is similar tothe one described by the sector model of NorthAmerica. In Lima, Santiago and Chileresidential colonies moved from the center of thecity to the urban periphery which were selected

for their better geographic, climatic and aesthetic factors. Soon socioeconomic status relatedto nearness to the center became related to distance away from the center. The pattern was acreation of the lifestyle choices of the urban rich (Portes, 1977).

3.8.3 Indian Cities

In cities of India, spatial segregation based on ethnicity, caste, religion and languagerather than demographics and economics can be seen. The social ties are horizontal andvertical. The horizontal relationships are between people of the same cultural backgroundwhile vertical relationships are between caste and class. Many studies have been done tostudy Indian urban areas, and especially to construct a structural model. It has been foundthat Indian cities defy social modeling. But, in general, the Indian urban social sceneessentially reflects two facets of non-western structure (Hall, 1980):

i Residences have not yet come to serve the symbolic function they do in theWestern world.

i Symbolic functionalism is performed by religion and caste and buttressed byregional affiliations, languages and customs. The nature of traditional socialstatus and the interdependence and spatial interpretation of diverse, yetcomplementary, status groups help to produce a very obscure patterning of socialgroups at the micro-level of analysis.

Research findings point out that while caste is important in rural societies for its veryfunctioning, in urban environments the meaning of caste becomes more important in terms ofidentity rather than function. For example, in rural areas, farming is done only by the Sudracaste, and religious duties performed by the Brahmins. In the cities where new professionswere created, new definitions had to be made. Soon, industrial and office workers belongedto all castes. The greater complexity of urban life and the difficulty of maintaining casteidentity through residential segregation alone, has created social organizations for each caste(Kopardekara, 1986). A second indigenous factor suffusing urban society is that of regionalaffiliation. "Particularly in cosmopolitan cities cultural or linguistic diversity and regionalassociations develop to extol their culture and language and to participate in their own

Figure 3.8 Latin American CitiesSource: Lowder, 1986


Bazaar

TempleFort

Centroid

Figure 3.9 Pattern of Indian CitiesSource: Weinstein, 1974

regional festivals if not usually celebrated in the region within which they live now" (Hall,1980:35). Certain areas are known for their residents speaking a particular language only.Although the neighborhoods that result are not corporate groups in the sense in which theyare defined, such neighborhoods are the source for the development of the corporate groups.

Weinstein (1974) made an attempt to produce a conceptual model for the socialsegregation of an Indian city. He postulated three dimensions as being importantcontributors to residential segregation. These three dimensions were

i socioeconomic dimension symbolized by the bazaari political dimension represented by an administrative symboli prestige dimension derived from the religious function of a temple.

These three dimensions would formconcentric zones (Figure 3.9). Theirinfluence and interplay causes residentialsegregation. The centroid of the systemrepresents the optimum location foraccessibility to all three functions.However, real case studies did not provethis theory. Instead, it was found thatmultiple nuclei were present, and that thetemple acted as the most meaningful focusfor the spatial distribution of socialcharacteristics.

Brush (1977) studied 24 cities inIndia and discerned four types of gradientsof population directly related to theirevolutionary pattern. Pune and Varanasi,cities that were well developed even before

the colonial period, had retained their residential core (Mehta, 1968). Bombay, Calcutta andMadras, colonial cities, had western style CBDs. Hyderabad had two nuclei – the old cityand the colonial city. Industrial towns like Jamshedpur were planned around their industrialcore.

Ahmad (1965) did a factor analysis of the socioeconomic characteristics of Indiancities. He had the following conclusions.

i North Indian cities had low female employment rates, low literacy, low migrationand equal male to female ratio.

i South Indian cities had higher female employment rate, higher literacy, highermigration and equal male to female ratio.

i Metropolitan cities (Bombay, Madras, Calcutta) has low-density commercialcenters surrounded by high-density residential neighborhoods.

i The modern planned cities (Jamshedpur, Chandigarh) have low populationdensities with no concentration of industrial, commercial or administrative areas.


Such broad conclusions are results of regional analyses. Analysis at the level of a single citygave patterns that are more complex. A systematic analysis of census data for Bombay wasdone (Kosambi, 1986). Census data from 1881, 1901, 1831 and 1961 was used to determinethe evolution and change of the social pattern. The patterns were attributed to Europeanism,commercialism, religious polarity, transportation and socioeconomic status (Kosambi, 1986).

These examples show that the urban social pattern of Indian cities is very complexdue to the influence of a variety of factors. The presence of many religions, languages,castes and classes produces a more heterogeneous pattern. The social patterns were alsostrongly influenced by the age of the city. The existence of multiple physical urban patternscaused by the presence of indigenous settlements, British cities and industrial towns withinthe boundary of the urban area.


CB D

Low incom e

M iddle income

High income

Transition

Incom e group 1

Incom e group 3

Incom e group 2

Concentric Zone Theory Sector Theory M ultiple Nuclei Theory

Concentric + Sector Theories

Concentric + Sector + M ultiple Nuclei Theories

Delhi Latin Am erica Asian Ports

Chicago Calcutta

residential

commercial

industrial

ethnic group

Figure 2.10 Urban Social Patterns and Relevant Case Studies.Source: Lowder, 1986, Hartshorn, 1992.


3.9 ConclusionThe urban social pattern is the complex manifestation of the underlying cultural

values of the population within a particular built environment. In the case of India, thesociocultural factors are related to caste, class, religion and language. These characteristicsstratify the society into vertical and horizontal systems. Stratification causes socialinequality in terms of wealth, power and status. The historical evolution of cities hassupported this stratification. In the design of Navi Mumbai, an effort was made to preventthis social stratification and use residential allotments to fulfill this objective.

The growth of cities across the world has been studied. The urban social pattern ofthese cities has been generalized. Three leading western theories describing the urban socialpattern of cities dominate the literature on urban social patterns (Hartshorn, 1992). Theseare concentric zone theory, sector theory and multiple nuclei theory. These theories havebeen combined in a social area analysis to describe the social pattern based on a few socialvariables. Social area analysis assumes that a few independent factors can explain the spatialpatterning of a city. In the American cities, the components derived from social areaanalysis were termed as socioeconomic status, family status and ethnic status.

The components of the analysis of American cities are not entirely apparent in theThird World cities. Status in Third World cities is based on family membership orsocioeconomic class. The lifestyle depends on ethnicity and migration. The lifestyle factorin North American cities relates small nuclear families with higher education achievementsand better employment opportunities. In Third World cities, this is not evident due to theexistence of multi-generational families. The households are generally large with a range ofages, skills and professions. Migration may also be restricted to the men of the family. Thereasons for migration are also varied – they may be migrating as a result of naturalcalamities, or in search of opportunities in the city. Male dominance, migration or ethnicgroup represent the ethnic factor.

Traditional Indian cities have grown over a very long period of time. The residentialneighborhoods of such cities are not as well defined as they are in the American cities. Inthe case of Navi Mumbai, the residential neighborhoods have been designed using theneighborhood principle as those designed in America. Land-use is also similar in that it ispredominantly single-use zoning. A market economy strongly influences the lifestyle of thecitizens of Navi Mumbai. In such a case study, it is appropriate to use a social area analysisto delineate the urban social pattern. However, this social area analysis must take intoconsideration the indigenous factors. Here, the researcher’s knowledge of the localenvironment is important to contextualize the pattern more appropriately.

Chapter 4: Research Design

Determining the urban social pattern of Navi Mumbai is the primary researchobjective of this thesis. The issue of spatial distribution of different kinds of people in NaviMumbai is of primary interest. The research investigates the relationship between the spatialpattern of Navi Mumbai and the different theories of urban social patterns discussed in theliterature review. The analysis looks at the variables at once and at their respective locationsin their distribution. The general issue of social areas will be accomplished through socialarea analysis. The theories put forth by Burgess, Hoyt, and Harris and Ullman will be thetheoretical framework for the conceptualization of the social pattern of Navi Mumbai.

4.1 Social Area Analysis

Social area analysis provides a broad framework for analyzing the social patterns of acity. It was first put forth by Shevky and Williams (1949) in a study of Los Angeles. Thisanalysis classifies census tract data into three main constructs - socioeconomic status, familystatus and ethnic status. The basic premise of social area analysis is that a city cannot bestudied in isolation from the overall society (Shevky and Bell, 1955). The increase inindustrialization creates an occupational status system (Timms, 1971). The family as a unitbecomes weaker. Better transportation systems increase mobility and lead to a greatersorting of population (Cadwallader, 1985). Under these conditions, immigration of ruralpopulation leads to segregation based on language, religion and ethnic background. Thesefactors are taken into consideration in social area analysis.

Cities are complex entities that have many different functions performed by manydifferent people. The pattern of the city may be determined by statistical analysis or bydiscerning people’s mental images of the city. A set of variables describing the socialstructure of the city can be used in the statistical analysis. These involve population,economic, and housing characteristics. The aim is to identify key combinations of differentmeasures that provide an adequate basis on which to differentiate the sub-areas from oneanother (King and Golledge, 1978).

Social area analysis shows how family characteristics, economic status and ethnicbackground produce a certain spatial pattern in the city. The study involves thecategorization of a city based on social rank, urbanization and segregation. Earlier, there wasconsiderable criticism about the choice of variables. They were considered to be very narrowand not universally applicable. However, mapping of social area analysis for a large sampleof cities showed that socioeconomic status, urbanization index, and ethnicity confirmed thevalidity of the analysis. These three factors also corresponded to the theoretical modelsproposed by Burgess, Hoyt and Harris and Ullman. Thus, the city was analyzed as acomposite made up of three layers. Generally the economic model showed a sectoredpattern, the urbanization component showed a concentric ring pattern, and ethnic segregationshowed a multiple nuclei arrangement. Although these analyses have been more effective forstudying North American cities, studies in Calcutta, Cairo and Helsinki showed some usefulgeneralization. The social area analysis may be done statistically by a factor analysis. It is a

Malathi Ananathakrishnan Chapter 4: The Research Design 39

device that seeks interrelationships among the set of input variables (Herbert and Thomas,1990).

Social area analysis based on western thinking can not be naively applied to the studyof urban social patterns in India. Social structure in India is a result of cultural, religious andhistoric development with both horizontal (kinship, religion, language) and vertical(occupation, education, caste) dimensions (Hall, 1980). Variables that arise from suchcultural determinants need to be used in the factor analysis.

4.2 Hypotheses

As discussed in the literature review, mapping of social patterns in many cities acrossthe world show that the socioeconomic status, family status and ethnic status correspondrespectively to the sector theory, concentric zone theory and multiple nuclei theory. In thiscase study of Navi Mumbai, my null hypothesis, H0, is: no significant difference in keyvariables is expected and hence no social patterning will occur. This hypothesis is put forthon the assumption that the social agenda put forth in the Development Plan has beensuccessfully implemented. If H0 is false, then the pattern will be explained using the existingtheories.

4.3 Operationalization

Certain variables will be used to operationalize the social area analysis to obtain theurban social pattern. The variables are tabulated below:Table 4.1 Constructs and VariablesConstruct VariableSocioeconomic status Profession

Number of earning membersIncomeEducation

Family status DemographicsWomen at homeFamily sizeDwelling sizeType of houseYear of occupation

Ethnic status ReligionLanguage

4.4 Data Collection

The data required for the analysis can be obtained from census tracts of NaviMumbai. This database provides aggregated information about each node (township), andeach sector (neighborhood) of the nodes. The sectors (neighborhoods) are identical to censusblock tracts. This provides a spatial hierarchical data set. The data available is based on a


socioeconomic survey done by CIDCO in December 1995. In this research, the sector is theunit of analysis. The survey was carried out on a ~22% sample basis for each node.

Table 4.2 Survey SamplingNode Total Number of

DwellingsSurvey Coverage % of total

VashiNerulNew PanvelBelapurKalamboliAiroliKopar-khairaneSanpada

27,28316,0569,3389,1099,00713,37814,1612,357

6656421921252034228225302506544

2426232225191823

The issues of validity and reliability arise in the use of census data for testing thehypothesis. For a social area analysis, data covering a large area is required. The only datasource that provides this information, is census data. The census data is not 100% reliable.An error of 5-8% is expected. All data is standardized. Statistics are weighted for spatial databecause, although variables are related, the units of analysis are not identical.

4.5 Methodology

Four methodologies are used to analyze the data. These are techniques in multivariateanalysis. The first is a descriptive analysis of the data setting out the parameters that need tobe considered to define the meaning of heterogeneity. The second is a principal componentsanalysis. This is a detailed stage of analysis. Although principal components analysis is nolonger considered the most favorable mode of analysis to delineate patterns, for the purposeof this thesis it shall be used. The third is cluster analysis of the cases to see which variablesare closely associated. Finally, cartographic mapping, and GIS overlay techniques are usedto determine the social pattern at the regional and sub-regional levels. The variables areexpected to cluster based on the constructs described above.

The descriptive analysis helps understand the finer dimensions of the data, andcompare it to other cities. The principal components analysis draws out the relationshipbetween the variables. The cluster analysis puts together cases which are similar based onthe relationship between the variables. The GIS and mapping techniques convert all thestatistical information into a graphic representation. These four methods are collectivelyused to analyze the data.

4.5.1 Descriptive Analysis

The first stage of analysis describes the data at both the regional and sub-regionalscale. At the regional scale the data is tabulated, and at the sub-regional scale attached asAppendix C. The single variable from that data set is selected and a histogram of it at the


sub-regional scale is drawn. The data is interpreted in terms of its mean and standarddeviation. Comparative figures at the national scale are also given.

In order to interpret this descriptive statistics for homogeneity, it is necessary toprovide a permissible range of variation. A variation greater than thirty percent of the totalpopulation from the mean (15% on either side of mean) is used here to show unequaldistribution. If the standard deviation at the 95% confidence interval is within 15% of themean, then the pattern shall be interpreted as homogeneous.

4.5.2 Principal Components Analysis

A principal components analysis reduces a large number of variables to a smallernumber of underlying components. Principal components analysis can be thought of as fourmatrices. The first matrix is a simple data matrix. The cases are the rows and the variablesare the columns. The N by M matrix is standardized in terms of standard deviation. The datamatrix is converted into a correlation matrix. This matrix is next converted into a factormatrix. This matrix contains components that represent a group of interrelated variables.Principal components are the eigenvalues of the correlation matrix (Davis, 1986). Theelements of the eigenvectors that are used to compute the scores are called principalcomponent loadings. These loadings indicate the strength of the relationships betweenvariables and underlying components. Finally, the matrix of component scores is computed.Each original observation is converted into a principal component score. Patterns can bedelineated from mapping these components.

The first step of principal components analysis is to obtain an initial solution. Theinitial solution is based on the orthogonal solution. This solution determines whether a smallnumber of the components can be used to explain the covariance between a large number ofvariables. The eigenvalue criterion (eigenvalue greater than or equal to 1) helps eliminatecomponents which are not meaningful. Corresponding communalities are also estimated.Generally variables with communalities less than 0.7 are not significant in the correlationmatrix. "To obtain the initial solution, certain restrictions are imposed. These restrictions are(1) there are k common components (2) underlying components are orthogonal to each other(3) the first component accounts for as much variance as possible, the second componentaccounts for as much of the residual variance left unexplained by the first factor, and so on"(Kim and Mueller, 1978). The second step is to rotate the axis to get a simpler solution. Theaxis has been rotated orthogonally (assuming the factors are uncorrelated). This is varimaxrotation. Rotating the axis more closely intersects the clusters of variables. The rotationnormally removes the negative loadings, and results in a simpler pattern.

4.5.3 Cluster Analysis

Classification of data places objects in one or more homogenous groups.Characteristics of the urban social pattern can be revealed by considering the relationshipwithin groups. Cluster analysis classifies the groups according to the observations into more-or-less homogenous and distinct groups (Davis, 1986). This approach to classification isvery subjective. It has very little theory and depends largely on experience. The


classification procedure used here is hierarchical clustering. This method joins similarobservations, then connects the next most similar observations to these. The levels ofsimilarity are used to construct the dendrogram. A correlation coefficient or distancecoefficient may be used to evaluate similarities. The distance coefficient is not constrainedwithin the range of +1.0 to -1.0, as is the correlation coefficient, and so produces betterdendrograms. Distance coefficients are linked at low values. The criteria for clustering isthat both observations mutually have the highest correlation with each other. A measure ofsimilarity between every pair of objects is computed using Euclidean distance. A lowdistance would indicate that two objects are similar and a large distance would indicate thatthe two objects are dissimilar.

4.5.4 Mapping and Overlays

The final stage is the mapping of the descriptive analysis, principal componentsanalysis and cluster analysis. This mapping helps explain the statistics through a easilyinterpretable graphic representation. This stage of analysis integrates the theoreticalframework, and the statistical analysis to determine an interpretation of the pattern.

4.6 Data Analysis

Descriptive analysis of the data was done using Microsoft Excel and SPSS. TheSPSS program was also used to perform a principal component analysis and a clusteranalysis on this data set. The aim of these two kinds of analysis was to determine if the dataset clustered into the three constructs given above. Both the analyses were done at a regionaland sub-regional scale. The regional scale was comparisons between the eight nodes of NaviMumbai. Analysis was then done of one particular node of Navi Mumbai, namely Vashi.Mapping of the principal components determined if any pattern exists in the socialcharacteristics of Navi Mumbai at the regional and sub-regional scales.

Chapter 5: Presentation of Data

5.1 Introduction

The aim of this research is to study the urban social pattern of the population across ahierarchical scale. This spatial scale is

• regional scale (nodes),• sub-regional scale (sectors of a node)

The study areas at the regional level of analysis are those of the nodes of NaviMumbai including Vashi, Nerul, Belapur, Kalamboli, Panvel, Kopar-khairane, Airoli andSanpada. The methodological reason for selecting these eight nodes out of the total ofthirteen is because data was available for only these eight nodes. Then the data set wasstudied at a sub-regional level by analyzing the neighborhoods of Vashi node. Vashi is theoldest node, and has fully developed residential sectors. As this node had the most completedata, it was selected out of the eight nodes.

Data for the regional and sub-regional scale was collected from the 1995socioeconomic survey conducted by CIDCO. As the 1995 survey data was the most recentdata, it was used for analysis. One or two variables from each set was selected for thisstudy. The criteria used to select the variables were based on the expectations of thehypothesis. The variables needed to explain the constructs as well as possible; only thenwould they bring out the characteristics of the construct. All the variables belonged to closedsets. Hence, only one or two representative variables from each set was selected. Theanalysis is divided into descriptive analysis of variables and detailed analysis at the regionaland sub-regional.

5.2 Descriptive Analysis of Data

The different constructs and variable names described in the methodology section aretabulated below (Table 5.1) with the actual variable from the data set.Table 5.1 Constructs and VariablesConstruct Variable Name Variable from data setSocioeconomicstatus

ProfessionNumber of earning membersIncomeEducation

highly skilled, unskilled1 earning memberRs. 2651-4450high school

Family status DemographicsFamily sizeDwelling sizeType of housingTenureLast place of residence

Male pop. age 25-45, female pop. age 25-454 to 5 members26-35 sq. m.CIDCO1980sBombay

Ethnic status ReligionLanguage

Hindu, MuslimMarathi, Malayalam

Malathi Ananthakrishnan Chapter 5: Presentation of Data 44

All data tables are for the regional scale while the histograms are from the sub-regional scale.Data tables for the sub-regional scale are given in Appendix C.

5.2.1 Socioeconomic Status

The socioeconomic status is an indicator of social class. A profession brings with it acertain prestige and social class. An increase in the number of earning members increasesfamily income and the socioeconomic class. Better education facilitates getting better jobsand higher income. All these variables are closely correlated, and form the socioeconomicindicator.

Number of earning members: Out of the total population of 91787 recorded in the survey,30430 are the working population. 33.15% (a slight increase from 32.8% recorded in the1987 survey) of the population makes up the workforce of Navi Mumbai. The percent ofmales and females is shown in Table 5.2 and the number of earners in Table 5.2.Table 5.2Work Force

Percent of malepopulation in workforce

Percent of femalepopulation in workforce

Vashi 53 10Nerul 55 7Belapur 52 12Kalamboli 54 6Panvel 57 8Kopar-khairane 56 10Airoli 53 7Sanpada 58 9Mean 54.75 8.62Standard Deviation 2.12 1.99

The average number of earners per household is 1.35, while it is 1.67 in Greater Bombay.Seventy-five percent of families had one earning member and twenty percent of families hadtwo earning members (Table 5.3).Table 5.3 Number of Earners

Single 2 3 4+Vashi 68 23 6 2Nerul 78 16 3 1Belapur 68 22 4 2Kalamboli 79 15 4 1Panvel 78 17 3 1Kopar-khairane 76 17 5 1Airoli 74 20 4 1Sanpada 70 19 7 2Mean 74 19 5 1Standard deviation 5 3 1 1


For the analysis, the variable, singleearning member, was selected. Thisis most representative of the entirepopulation, and has a normaldistribution over eight cases. Themean is 74 with a very low standarddeviation of 5.

The distribution of the singleearner families is shown in Figure5.1. The distribution of the single-earner family at the regional levelshows a standard deviation of only 5(mean=74). This means that thedistribution is homogeneous. At thesub-regional scale the standarddeviation is 7.96 (mean=66.3). Boththe values are within 15% of themean. The pattern is homogeneous.

Profession: Good employment opportunities are offered by the manufacturing industries ofNavi Mumbai. 25% of the workforce is employed there. Government offices includingbanks and public sector enterprises employ 21% of the workforce. Small businesses accountfor 15% of the employees, while service professions such as shops and hotels employ 7% ofthe workforce. Professional workers in teaching and medical institutions are 7% of theworkforce. For this analysis classification based on skills is tabulated (Table 5.3). Highlyskilled professionals hold higher level managerial and supervisory jobs or are professionalbusiness persons, contractors and consultants. In Navi Mumbai this economic classconstitutes 38% of the work force. The standard deviation is 11. Skilled workers are factoryworkers, carpenters, construction workers and trainees. They form 17% of the workforce.Unskilled persons are construction laborers and housemaids. On an average, they are 19% ofthe work force and the standard deviation is 11. Kopar-khairane has a low number of highlyskilled workers and a large number of unskilled workers (Table 5.4). The main reason is thatthis node is presently under construction and has a large workforce of construction workers.Table 5.4 Occupational Classification of Workforce

Highlyskilled

skilledworker

unskilledworker

officeassistant

self-employed

teacher other

Vashi 45 12 12 15 9 4 3Nerul 38 23 13 15 4 4 3Belapur 47 12 8 20 3 6 4Kalamboli 24 31 20 12 8 3 2Panvel 43 19 9 16 4 7 2Kopar-khairane 20 9 41 9 9 0 12Airoli 34 18 44 12 5 1 4Sanpada 49 9 20 14 3 3 2Mean 38 17 19 14 6 4 4Standard Deviation 11 8 11 3 3 2 3

80.075.070.065.060.055.050.045.0

Cases weighted by population

Freq

uenc

y

6000

5000

4000

3000

2000

1000

0

Std. Dev = 7.96

Mean = 66.3

N = 19127.00

Figure 5.1 Distribution of Single-earner families


The corresponding data was not available at the sub-regional scale.

Income: The income groups are defined by the Government of India’s household incomeclassification into:

• economically weaker section (EWS) earning less than Rs1250 per month• lower income group (LIG) earning between Rs. 1251 and Rs. 2650• middle income group (MIG) earning between Rs. 4451 and Rs 7500 and• higher income group (HIG) earning more than Rs. 7500 per month.

The proportion of EWS:LIG:MIG:HIG is 2:16:34:48. This shows a proportionately largemiddle and higher income groups. Thus, in Navi Mumbai it appears that the four incomegroups have to be redefined based on the median and/or mean income of this region ratherthan using the national urban averages (Table 5.5). The monthly average household incomeis Rs. 4900 and the monthly average per capita income is Rs. 1230.

Table 5.5 Household Incomeupto1250

1251-2650

2651-4450

4451-7500

7501-10000

10001-15000

15000+

Vashi 2 14 27 30 15 7 3Nerul 3 27 36 21 6 3 1Belapur 2 12 27 35 12 5 2Kalamboli 2 26 46 21 3 1 0Panvel 2 24 31 31 5 3 2Kopar-khairane 2 9 32 36 9 7 0Airoli 1 14 39 34 8 2 0Sanpada 1 5 31 42 12 4 1Mean 1.88 16.38 33.63 31.25 8.75 4 1.13Standard deviation 0.64 8.26 6.46 7.29 4.06 2.2 1.13

The income range of Rs. 2651-4450 wasselected for the principal componentsanalysis because the median income ofRs. 4200 fell within this range. Almost34% of the population falls within thiscategory, and the standard deviation is6.46.

The regional scale shows astandard deviation of 6.46 (mean=33.45)and the sub-regional scale, the standarddeviation is 10.98 (mean=27.9) (Figure5.2). Both cases do not show ahomogeneous distribution of peoplebased on income as the standarddeviation is greater than 15% of themean.

50.0

45.0

40.0

35.0

30.0

25.0

20.0

15.0

10.0

5.0


Fre

quen

cy

7000

6000

5000

4000

3000

2000

1000

0

Std. Dev = 10

Mean = 27.9

N = 19127.00

Figure 5.2 Frequency of Families with incomerange Rs. 2651-4450


Education: The survey shows that 27% of the total population is children going to school,while 4% of the population is going to college. Most students attend school and collegewithin their node (township). Sanpada is the only node without any education facilities.Vashi has all the major colleges. Hence, the column titled Vashi shows that some studentsfrom all other nodes also go there to attend school or college (Table 5.6). 76% of the studentswalk to their school or college, 12% use public transport, 10% use bicycles and only 2% goby school bus.Table 5.6 Location of Education Institutions

Vashi Nerul Belapur Kalamboli Panvel Kopar-khairane

Airoli Sanpada Bombay

Vashi 88 1 1 1 0 0 0 0 9Nerul 9 77 2 1 1 0 0 0 10Belapur 10 12 67 1 1 0 0 0 9Kalamboli 1 0 1 90 4 0 0 0 4Panvel 2 1 2 8 76 0 0 0 11Kopar-khairane 17 0 0 0 0 81 0 0 2Airoli 7 0 0 0 0 0 83 0 10Sanpada 47 8 1 1 0 0 16 0 27

In the Bombay region literacy rates are seventy-five percent for adult population. 51% of thechildren go to schools where the medium of instruction is English, and 35% of the childrengo to schools where the medium of instruction is Marathi (12% did not specify their mediumof instruction). The level of education is categorized into illiterate, children, primary schooleducation, secondary school education, high school education, technical education, Bachelorsand Masters degrees. The value given represents the highest level of education achieved byat least one member of the family (Table 5.7).

Table 5.7 Level of Educationilliterate Children Primary secondary high

schooltechnical BS MS

Vashi 4 9 14 27 22 1 22 4Nerul 3 5 15 27 17 2 24 5Belapur 5 8 18 30 21 1 15 2Kalamboli 7 10 20 34 16 2 9 1Panvel 3 8 14 25 19 4 22 4Kopar-khairane 4 6 13 27 15 1 29 4Airoli 4 7 16 37 18 1 13 3Sanpada 4 8 12 21 25 2 21 4Mean 4.25 7.63 15.25 28.5 19.13 1.75 19.38 3.38Standard deviation 1.28 1.60 2.66 5.07 3.36 1.04 6.52 1.30


The variable ’secondary school’ was selected under level of education. 28.5% of thepopulation falls under this category with a standard deviation of 5.07. Secondary schoolmeans an education of up to Grade 10 and the passing of a government examination(matriculation). This level of education is provided to everyone by the government free ofcost. The national average for this variable is 16.6 (Census of India, 1991)

The standard deviation of this variable at the regional scale is 5.07 (mean=28.5), andat the sub-regional scale is 7.13 (mean=40.6). The variation is not homogeneous at eitherscale (Figure 5.3).

5.2.2 Family StatusDemographics: The nodes ofNavi Mumbai have a female tomale ratio of 848 to 1000(comparative figures for Bombayare 819 to 1000). Children up tothe age of 15 constitute 33% ofthe total population. The agegroup 16 to 24 is 10% of thepopulation. The working agegroup of 25 to 44 is 39% of thepopulation. About 9% of thepopulation are in the age group of45 to 59, and only 3% of thepopulation are in the 60+ range.The present pattern clearly showsa younger population with a highpercentage of children.

The demographicindicators used are male and female population of the age group 25-45. This age group wasselected because it is a subset of the population and it makes most of the decision regardingsocial choices (Table 5.8, Table 5.9).Table 5.8 Male Population

below 3 4-5 6 - 9 10 -15 16 - 21 22 -24 25 -44 45 -59 60+Vashi 4 3 7 15 12 5 34 14 5Nerul 7 5 10 12 8 5 41 8 3Belapur 6 4 8 14 12 5 37 11 4Kalamboli 8 6 11 13 8 5 43 6 1Panvel 8 4 8 11 9 5 44 9 3Kopar-khairane 10 6 10 10 8 5 43 6 1Airoli 7 5 10 14 11 4 39 8 2Sanpada 7 4 6 10 10 5 43 10 4Mean 7 5 9 12 10 5 41 9 3Standard deviation 2 1 2 2 2 0 3 3 1

50.045.040.035.030.025.020.015.0


Fre

quen

cy

6000

5000

4000

3000

2000

1000

0

Std. Dev = 7.13

Mean = 40.6

N = 19127.00

Figure 5.3 Frequency of Families with at least oneindividual with Secondary Education


The standard deviation of thepopulation is 3 (mean=41) at theregional level, and 3.39 (mean=38)at the sub-regional level (Figure5.4). The population age structure isuniformly distributed over the wholeregion.

Figure 5.9 Female Populationbelow 3 4-5 6 -9 10 -15 16 -21 22 -24 25 -44 45 -59 60+

Vashi 5 3 8 14 11 5 39 10 4Nerul 7 5 10 13 9 7 40 6 2Belapur 5 4 8 14 11 6 40 8 3Kalamboli 15 10 16 20 13 12 6 6 2Panvel 8 4 8 11 10 9 40 6 3Kopar-khairane 9 6 10 9 12 10 37 5 1Airoli 6 5 10 15 10 6 39 6 2Sanpada 6 4 8 10 13 9 39 9 3Mean 8 5 10 13 11 8 35 7 3Standard deviation 3 2 3 3 1 2 12 2 1

The female population of the age group 25-45 is also uniformly distributed over thestudy area.

Family size: The average family size is 4.01 for all the nodes (Table 5.10). A descriptiveanalysis of the data over the last 20 years shows that household size has been constantlyincreasing. The reason for this is not only marriage and children, but also the need toaccommodate older parents. In Vashi, average family size has increased from 3.73 in 1987to 4.21 in 1985. The comparative family size for Bombay is 4.76 and the national average is5.52.

52.0

50.0

48.0

46.0

44.0

42.0

40.0

38.0

36.0

34.0

32.0


Fre

quen

cy

7000

6000

5000

4000

3000

2000

1000

0

Std. Dev = 3.39

Mean = 38.0

N = 19127.00

Figure 5.4 Frequency of male population in the agegroup 25-45


Table 5.10 Family SizeSingle 2,3 4,5 6,7 8,9,10 Average

family sizeVashi 1 26 57 14 2 4.21Nerul 2 34 54 10 0 3.87Belapur 1 31 53 13 1 4.03Kalamboli 3 31 52 14 0 3.99Panvel 5 41 45 8 1 3.67Kopar-khairane 3 41 45 10 1 3.81Airoli 1 27 56 15 1 4.22Sanpada 3 39 45 12 1 3.85Mean 2.4 33.8 50.9 12 0.9Standard deviation 1.4 6.0 5.1 2.4 0.6

The families with a size of 4 or 5members was chosen as 50% of thepopulation belongs to thiscategory. The variable has astandard deviation of 5.1.

The variation of the data isminimal. At the regional scale thestandard deviation is 5.1(mean=50.9), and 5.85 (mean=56)at the sub-regional scale (Figure5.5).

Type of Housing: Initially CIDCO built ninety percent of the housing stock. CIDCO beganall construction in Navi Mumbai. Later, private builders and cooperative housing begandeveloping residential sectors. Since Vashi is the oldest node, the data shows morediversification of the housing stock. All other nodes show a dominance of CIDCO housing(Table 5.11).

67.5

65.0

62.5

60.0

57.5

55.0

52.5

50.0

47.5

45.0

42.5


Freq

uenc

y

6000

5000

4000

3000

2000

1000

0

Std. Dev = 5.85

Mean = 56.0

N = 19127.00

Figure 5.5 Frequency of households with 4 or 5members


Table 5.11 Type of HousingCIDCO Pvt. House Pvt. Co-op Commercial Other

Vashi 64 2 29 2 1Nerul 95 0 5 0 0Belapur 91 0 9 0 0Kalamboli 99 0 0 1 0Panvel 80 5 15 0 0Kopar-khairane 98 0 2 0 0Airoli 100 0 0 0 0Sanpada 88 1 11 0 0Mean 89.38 1.00 8.88 0.38 0.13Standard Deviation 12.24 1.77 9.76 0.74 0.35

For this variable, only housesbuilt by CIDCO was selected. Housesbuilt by CIDCO are 90% of thehouses available. The standarddeviation is 12.24.

The standard deviation at theregional scale is 12.24 (mean=89.38)while at the sub-regional scale it is35.62 (mean=66.4) (Figure 5.6). Thisis a very significant result. CIDCO’saim to promote heterogeneity was tobe implemented by having a stronghold over the housing market. AtVashi, the oldest node, the strongcontrol is no longer evident. Thelarge deviation shows that privateconstruction has taken place. Thismay be one of the main reasons forthe greater variability in the pattern at

the sub-regional scale rather than at the regional scale.Table 5.12 shows present ownership of the house. CIDCO is still the major owner.

Most government offices that provide housing for their employees obtain long term leasefrom CIDCO. Some houses are mortgage through CIDCO. The categories, privateownership, resale and rental fall under private ownership.

100.0

90.0

80.0

70.0

60.0

50.0

40.0

30.0

20.0

10.0

0.0

Cases weighted by POP

Fre

quen

cy

7000

6000

5000

4000

3000

2000

1000

0

Std. Dev = 35.62

Mean = 66.4

N = 19127.00

Figure 5.6 Frequency of Houses built by CIDCO


Table 5.12 Ownership of HouseMortgage CIDCO Private Resale Rental

Vashi 11 23 17 21 23Nerul 21 36 3 16 36Belapur 8 40 4 0 37Kalamboli 25 25 1 0 43Panvel 7 33 9 0 36Kopar-khairane 0 34 1 14 49Airoli 0 51 0 0 42Sanpada 15 32 7 18 26Mean 10.88 34.25 5.25 8.63 36.5Standard Deviation 9.09 8.75 5.68 9.43 8.64

Dwelling size: The average size of dwelling units constructed by CIDCO is less than thatbuilt by private builders (Table 5.13, Table 5.14). While CIDCO is building houses for theEWS/LIG/MIG, the private builders are predominantly building for the HIG.Table 5.13 Housing built by CIDCO

<15 16-25 26-35 36-50 51-75 76-100 101-150 150+Vashi 11 30 22 14 15 3 2 0Nerul 7 57 18 8 7 2 1 0Belapur 0 26 10 33 20 11 0 0Kalamboli 24 37 24 5 7 2 0 0Panvel 10 33 16 18 22 1 0 0Kopar-khairane 0 20 10 42 18 9 1 0Airoli 0 30 28 17 18 6 0 0Sanpada 0 61 18 12 9 0 0 0Mean 6.50 36.75 18.25 18.63 14.5 4.25 0.50 0Standard deviation 8.52 14.64 6.36 12.65 6.02 3.99 0.76 0

The standard deviation of the data was21.25 while the mean was 14.2 (Figure5.7).

90.0

80.0

70.0

60.0

50.0

40.0

30.0

20.0

10.0

0.0


Fre

quen

cy

10000

8000

6000

4000

2000

0

Std. Dev = 21.85

Mean = 14.2

N = 19127.00

Figure 5.7 Frequency of Housing Built by CIDCO


Table 5.14 Housing built by Private Enterprise<15 16-25 26-35 36-50 51-75 76-100 101-150 150+

Vashi 4 2 2 14 14 24 8 2Nerul 0 6 6 6 8 23 5 0Belapur 0 1 2 2 33 9 5 1Kalamboli 0 8 0 0 5 0 0 0Panvel 0 0 1 1 18 24 8 2Kopar-khairane 0 91 5 5 42 1 0 0Airoli 0 0 0 0 17 0 0 0Sanpada 13 60 2 2 12 5 2 1Mean 37.50 16.63 18.50 14.38 5.50 3.75 3.75 14.0Standard Deviation 10.76 7.69 10.86 3.16 2.67 2.12 3.41 6.0

The frequency distribution of housesbuilt by private enterprise shows astandard deviation of 18.67 and mean16.2 (Figure 5.8).

Dwelling size was selectedbased on type of house. For bothCIDCO-built houses and privatelybuilt houses, the dwelling sizesselected was 26-35 sq. m.corresponding to middle incomegroups.Tenure: The growth of Navi Mumbaican be divided into three stages: early,slow phase in the 1970s, middle phasein 1980s and accelerated phase in the1990s. There is a great variation in thenumber of houses occupied betweennodes (Table 5.15). Only Vashi and

Belapur had a household population in the 1980s. Families began to reside in Nerul,Kalamboli, Panvel and Airoli in the latter 1980s and in Kopar-khairane and Sanpada only inthe 1990s.Table 5.15 Year of Occupation

before 1980 1981-85 1986-90 1991-92 1993 1994 1995Vashi 11 28 24 8 9 14 5Nerul 0 6 29 10 6 35 14Belapur 4 23 24 11 13 18 7Kalamboli 0 5 31 10 11 37 6Panvel 0 11 14 15 14 34 12Kopar-khairane 0 0 0 20 18 34 28Airoli 0 0 47 14 12 16 11Sanpada 0 0 0 0 8 48 44Mean 1.88 9.13 21.13 11.00 11.38 29.50 15.88Standard Deviation 3.94 10.88 15.99 5.83 3.78 12.09 13.50

60.050.040.030.020.010.00.0

Cases weighted bypopulation

Frequency

12000

10000

8000

6000

4000

2000

0

Std. Dev = 18.67

Mean = 16.2

N = 19127.00

Figure 5.8 Frequency of Houses built by PrivateEnterprise


The three time periods of 1970s, 1980s and 1990s account for the entire span ofgrowth of the city. Only the middle phase was selected as a representative variable.However, this table only indicates the year of occupation of the present accommodation. It isthus, not entirely accurate as families may have shifted after their first place of residence.

The standard deviation at theregional scale is 20.25 (mean=30.25)and 18.25 (mean=52.8) (Figure 5.9).There is a very large variability,which can be attributed to the pace ofconstruction.

Previous Place of Residence: Thetwo variables describing previousplace of residence are Bombay andNavi Mumbai (Table 5.16). Thesedescribe migration from Bombay andmovement within Navi Mumbai.Migration from Bombay is usuallythe first stage of relocation where the

choice of house is not very important. This is because any house in Navi Mumbai would bebetter than the existing living conditions in Bombay. Movement within Navi Mumbai showsdesire to move to a house of the homeowner’s choice.

Table 5.16 Previous Place of ResidenceIsland City Western

suburbsEasternsuburbs

Thane Navi Mumbai

Withinstate

Outsidestate

OutsideIndia

Vashi 18.06 6.19 26.94 3.5 35.89 3.44 4.45 0.53Nerul 13.58 5.55 23.56 2.58 47.53 2.58 2.94 0.07Belapur 10.83 5.65 10.23 4.82 32.34 13.32 19.42 0.2Kalamboli 5.79 2.94 11.39 3.46 66.3 5.26 2.54 0.04Panvel 3.62 2.26 5.27 3.11 68.28 6.82 6.4 0.05Kopar 14.2 2.63 17.16 2.63 55.23 4.51 1.36 0.04Airoli 8.05 4.51 20.43 9.29 49.78 3.75 2.85 0Sanpada 17.1 5.15 24.63 4.23 39.34 2.57 6.25 0.18Mean 11.4 4.36 17.45 4.20 49.34 5.28 5.78 0.14Standarddeviation

5.25 1.54 7.79 2.19 13.39 3.54 5.8 0.17

80.070.060.050.040.030.020.010.00.0


Freq

uenc

y

7000

6000

5000

4000

3000

2000

1000

0

Std. Dev = 18.25

Mean = 52.8

N = 19127.00

Figure 5.9 Frequency of Tenure


The variables, island city, westernsuburbs, eastern suburbs and Thanehave been summed up to obtain thevariable, Bombay. This variable showsthe families whose most immediateplace of origin is Bombay.

The standard deviation of thefamilies whose previous place ofresidence was Bombay is 9.42(mean=26.01) at the regional scale and9.54 (mean=53) at the sub-regionalscale. There is a large variationbecause there has been migration fromthe rural areas, from Bombay andwithin Navi Mumbai.

5.2.3 Ethnic StatusThis construct is very important because it is the construct that creates segregation in India.Ethnic enclaves are formed mainly by religious and linguistic groups.

Religion: This variable is very important for this analysis because India has a number ofwell-defined religions. The means of the religion variable correspond with the nationalaverages. This variable shows diversification of the population based on a cultural variable(Table 5.17).

Table 5.17 ReligionHindu Christian Islam Jain Sikh Buddhist Others

Vashi 84 6 6 1 2 1 0Nerul 88 3 5 0 3 0 1Belapur 79 6 4 0 7 2 0Kalamboli 84 4 5 0 6 1 0Panvel 94 2 2 0 1 0 1Kopar-khairane 89 2 6 0 1 2 0Airoli 88 3 3 0 1 5 0Sanpada 80 9 7 0 3 1 0Mean 85.75 4.38 4.75 0.13 3.00 1.50 0.25Standard deviation 4.98 2.45 1.67 0.35 2.33 1.60 0.46

The variables Hindu and Muslim were selected for analysis. The Hindu population is themajority and is homogenous. The mean is 85.75% and the standard deviation is only 4.98.However, it is more important to analyze the minority religions to see if they are formingethnic enclaves. The Muslim population is 4.75% of the total and has a standard deviation of1.67. An analysis of the other minority populations also show very large standard deviations.

75.070.065.060.055.050.045.040.035.0


Fre

quen

cy

6000

5000

4000

3000

2000

1000

0

Std. Dev = 9.56

Mean = 53.0

N = 19127.00

Figure 5.10 Frequency of Bombay as PreviousPlace of Residence


Figure 5.11 Frequency of Hindus Figure 5.12 Frequency of MuslimsThe Hindu population is spread uniformly over the study are with standard deviation

4.98 (mean=85.75). The Muslim population and other minority religions show a non-uniform distribution over the study area.

Language:The variable language is very important in the Indian context because civil violence

due to language has taken place across India. Hindi is the dominant language of the country.Marathi is the local language, Gujarati is the language of the adjoining state, Punjabi is anorthern language, Bengali an eastern one and Tamil, Malayalam and Kannada southern ones

Table 5.18 LanguageMarathi Hindi Gujarati Malayalam Punjabi Tamil Kannada Bengali Other

Vashi 42.41 13.81 7.23 7.41 4.48 5.14 2.82 3.17 13.53Nerul 45.75 16.50 2.99 10.19 5.50 3.34 3.56 3.01 9.16Belapur 40.76 16.47 3.98 8.31 9.64 2.90 2.36 4.08 11.5Kalamboli 55.87 14.29 2.19 8.11 6.66 2.32 3.20 0.83 6.53Panvel 66.78 9.65 2.92 5.04 1.74 2.35 3.29 2.96 5.27Kopar 67.93 16.72 1.44 2.99 1.12 1.68 1.72 0.80 5.6Airoli 42.46 12.50 3.13 13.60 5.33 5.33 2.57 3.49 11.59Sanpada 63.79 12.37 2.69 5.77 1.34 3.08 3.72 1.11 6.13Mean 53.22 14.04 3.32 7.68 4.48 3.27 2.91 2.43 8.66Std. dev 11.73 2.50 1.74 3.26 2.97 1.32 0.67 1.31 3.22

The two languages selected are Marathi and Malayalam. Marathi is the local language.54% of the population speaks this language. Malayalam is the language of the state 1000miles away, and there is a large population of Malayalam-speaking people in the greaterBombay region. This forms a major minority language. This has been used to study if thereare any ethnic neighborhoods formed due to linguistic considerations.

Freq

uenc

y

5000

4000

3000

2000

1000

0

Std. Dev = 4.

Mean = 82.4

N = 19127.00 Freq

uenc

y

10000

8000

6000

4000

2000

0

Std. Dev = 3.91

Mean = 6.9

N = 19127.00


Figure 5.13 Frequency of Marathi Figure 5.14 Frequency of Malayalam

The standard deviation of Marathi is 11.73 (mean=53.22) at the regional scale and15.73 (mean=46.6). The distribution of families with Marathi as their native language is notvery uniform (Figure 5.13). This is probably the result of the many other linguistic groups,which have formed their own enclaves. The standard deviation of Malayalam is 3.26(mean=7.68) at the regional scale and 3.77 (mean=7.6) at the sub-regional scale (Figure5.14). The standard deviation is very large showing some areas have more Malayalam-speaking persons than others leading to the conclusion that ethnic enclaves do exist.

The descriptive analysis suggests that the urban social pattern is not defined byhomogeneous socioeconomic classes. There is a non-uniform pattern in socioeconomicvariables as well as in the ethnic variables. This pattern is more apparent at the sub-regionalscale rather than at the regional scale (Table 5.19).

Table 5.19 Spatial Pattern of VariablesVariable Regional scaleNumber of earning membersIncomeEducation

UniformNon-uniformNon-uniform

DemographicsFamily sizeType of housingTenureLast place of residence

UniformUniformNon-uniformNon-uniformNon-uniform

HinduMuslimMarathiMalayalam

UniformNon-uniformNon-uniformNon-uniform

80.070.060.050.040.030.020.010.0


Fre

quen

cy

6000

5000

4000

3000

2000

1000

0

Std. Dev = 15.73

Mean = 46.6

N = 19127.00

25.0

22.5

20.0

17.5

15.0

12.5

10.0

7.5

5.0

2.5


Fre

quen

cy

6000

5000

4000

3000

2000

1000

0

Std. Dev = 3.77

Mean = 6.9

N = 19127.00


5.3 Regional Scale - Nodes5.3.1 Principal Components Analysis (PCA)

The analysis at the regional scale uses the eight nodes (townships) as the cases for thestudy. The use of PCA as a method of analysis was limited by the small number of cases.The number of variables used in the analysis could not be more than the number of cases.The constructs described on page 1 suggest the need for 12 variables. However, as PCAlimited the number of variables to 8, the variables selected were number of earning members,income, secondary school education, family size, tenure, migration, religion and language.The variables were weighted by the total population of each node. A PCA was run, and threecomponents were obtained. The rotated component matrix is used here for interpretation anddiscussion (Appendix D).

The communalities of all the variables are very high, and in a range of 0.824 and0.985. The total of the communality is 7.18, explaining 90% of the variance. Hence, theassumption can be made that all the variables are significant and are useful for the study. Theoutputs obtained from the SPSS program are used to determine which variables, or principlecomponents, are needed for the complete explanation of the difference in the data. Theprincipal components obtained from the rotated component matrix are used as they are moresimple to interpret. The components with eigenvalues greater than 1 will be used to explainthe variance. Component 1 with an eigenvalue of 3.468 explains 43.347% of the variation.Component 2 with an eigenvalue of 1.902 explains 23.771% variation and Component 3 withan eigenvalue of 1.818 explains a variation of 22.728%. Cumulatively these threecomponents explain 89.845% of the variation. Thus, nearly 90% of the variance of the 8nodes lies within a 3-dimensional space.


Figure 5.16 Loadings of Principal Components The eight original variables are combined linearly to define principal components. Theloadings produced by the principal components analysis for the variables is used to create barcharts to better visualize the magnitude of the loading. These loadings help explain thecontributions of the variables to each principal component. It does not directly expresswhich, if any, components contribute more or less to the overall data association

C o m p o n e n ts

-1

-0 . 5

0

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Analysis weighted by population of each node

migration

religionfamily size

Component 2

1.0 1.0

tenure

-.5

earner

0.0

.5 .5

income

.5

education1.0

language

Component 3Component 1

0.00.0-.5-.5

Figure 5.15 Components in Rotated Space


The three components are (Table 5.20):Table 5.20 Attributes of Principal ComponentsPrincipal Components Variables NameComponent 1 Family size

Previous place of residenceTenure

Family status

Component 2 EducationIncome

Socioeconomic status

Component 3 Number of earnersLanguageReligion

Ethnic status with highnumber of earners.

5.3.2 Cluster AnalysisA cluster analysis was done using the scores obtained from the principal components

analysis. Analysis of the raw data was not carried out because the SPSS program did notweight the raw data while running a cluster analysis. Cluster analysis of the scores fromPCA ensured that the data was standardized in the same manner for both types of analysis.As the number of cases was only 8, only two clusters were formed. The first cluster (Cluster1) had the nodes Belapur and Kalamboli while the second cluster (Cluster 2) had the rest ofthe nodes, Nerul, Vashi, Sanpada, Panvel, Kopar-khairane, Airoli (Appendix E).

5.3.3 DiscussionThe principal components analysis produced three components with eigenvalues

above 1. The three components correspond to family status, socioeconomic status andethnic status. This analysis does not show any differentiation based on variables of ethnicity.As the analysis was constrained by the reduced number of variables, this PCA does notdirectly correspond to the descriptive analysis. The cluster analysis shows that the two of the

Rescaled Distance Cluster Combine

0 5 10 15 20 25 +---------+---------+---------+---------+---------+ Node Panvel -+-----------------+ Kopar -+ +-------------------------+ Sanpada -------------------+ +---+ Nerul -------------+-------+ I I Airoli -------------+ +-----------------------+ I Vashi ---------------------+ I Belapur ---------------------------------------+---------+ Kalamboli ---------------------------------------+

Figure 5.17 Dendrogram using Average Linkage (Between Groups)

Cluster 2

Cluster 1


nodes are different from the other six. The main reason for this is the high variability in thelanguage data set for Belapur, and the high percentage of families in the selected incomerange for Kalamboli.

5.4 Sub-regional Scale - Sectors of Vashi5.4.1 Principal Components Analysis (PCA)

The analysis at the sub-regional scale uses the 23 sectors (neighborhoods) of Vashi asthe cases for the study. From the data, 13 variables were selected for the analysis. Thesewere: families with one earning member, household income range of Rs. 2651-4450, highschool education, male and female population of the age group 25-45, families with 4 or 5members, houses built by CIDCO, tenure of house in the 1980s, migration from Bombay,Hindus and Muslims, linguistic groups speaking Marathi and Malayalam. The variables wereweighted by the total population of each node. A PCA was run, and three components wereobtained. The rotated component matrix is used here for interpretation and discussion(Appendix F).

The PCA shows the communality of the 11 variables to be 8.01, explaining 73% ofthe variance. The extracted sums of squared loadings of the first three components iscumulatively 72.917%. Component 1 with an eigenvalue of 2.75 explains 25.001% of thevariation. Component 2 with an eigenvalue of 2.690 explains 24.453% variation andComponent 3 with an eigenvalue of 2.581 explains a variation of 23.463%. Morecomponents could have been used, but interpretation would have been more difficult. Theattributes of the principal components are (Table 5.21)

Table 5.21 Attributes of Principal ComponentsPrincipal Components Variables NameComponent 1 Education

IncomeOwnership of housePrevious place of residenceMuslim

Socioeconomic status andMuslim enclave

Component 2 Marathi Ethnic statusComponent 3 Number of earners

MalayalamDemographicsHindu

Ethnic status with highnumber of earners.


Figure 5.18 Loadings of Principal Components

The bar chart explains the loadings of each variable on the component. Theseloadings help explain the contributions of the variables to each principal component. Thesedefine which values contribute more or less significance to that particular component.

5.4.2 Cluster AnalysisA cluster analysis of the scores obtained from PCA was done. Three clusters were

formed using the 23 cases. The first cluster (Cluster 1) had had only sector 5. The secondcluster (Cluster 2) had sectors 12, 14, 16A, 17, 28 and 29, and the third cluster (Cluster 3)had all the rest of the 16 sectors (Appendix G).

C o m po ne nts

-1-0 .8-0 .6-0 .4-0 .2

00 .20 .40 .60 .8

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5.4.3 DiscussionThe principal components analysis produced three equally important components

with eigenvalues in the range of 2.75 to 2.58. Each of the three components have an ethnicvariable in them. The first component is one which has a high socioeconomic componentdominated by a Muslim population. The second component has only the population speakingMarathi. As the Marathi population is 53% of the total population, it represents a majorityof the population. This can be translated into a middle-class population. The thirdcomponent is the economically active age group dominated by the Hindu population. Again,as Hindus are 83% of the population, this component also describes the general population.All the components are equally important and separated only by ethnic variables. It appearsthat there is a segregation based on the ethnic component.

The cluster analysis shows a segregation in Cluster 1 caused by high number ofearners with a high percentage of households speaking Marathi and a low percentage of

Cluster 1

Cluster 2

Cluster 3

Figure 5.19 Dendrogram using Average Linkage (Between Groups)

Rescaled Distance Cluster Combine

0 5 10 15 20 +---------+---------+---------+---------+-----Sector 2 -+ 6 -+---+ 1 -+ +-+ 4 -----+ +-----+ 16 ---+---+ I 20 ---+ +---+ 9 -+-+ I I 10 -+ +---+ I +-----------+ 15 ---+ +-----+ I I 26 -------+ I I 21 -----------------+ +---------+ 3 ---+---+ I I 7 ---+ +---------+ I I 9A -------+ +-----------+ I 8 ---------+-------+ +---------+ 10A ---------+ I I 14 -------+---------------+ I I 29 -------+ I I I 12 -+---+ +---------------+ I 17 -+ +-------------+ I I 16A -----+ +---+ I 28 -------------------+ I 5 -------------------------------------------------+


households speaking Malayalam. Cluster 2 shows a dominance of households speakingMarathi.

5.6 ConclusionThe analysis of the data shows that the urban social pattern appears to be non-uniform

at the regional scale, and distinctly driven by an ethnic component at the sub-regional scale.The descriptive analysis of individual variables also shows this non-uniform pattern. PCAand cluster analysis brings forth the variability of the data and shows which variables andwhich cases cluster together. At the sub-regional scale as there is a smaller percentage ofCIDCO-built houses, individual households have exercised their choice, and a strong ethniccomponent is seen. In summary, although the government policy was to prevent theformation of ethnic enclaves, the outcome of the implementation strategy shows otherwise.

Chapter 6: Interpretation and Discussion

A preliminary interpretation of the data analysis in the previous chapter shows the

details of the social urban pattern are best seen in the sub-regional scale. However, a brief

interpretation of the regional scale is described here before proceeding to the detailed

interpretation at the sub-regional scale.

6.1 Regional Scale

Figure 6.1 shows the spatial

distribution of the clusters. Cluster 1

has two nodes close to each other and

possibly influenced by one another. All

the other nodes are in the second cluster.

Airoli

Kopar-Khairane

Vashi

Sanpada

Nerul

Belapur

Kalamboli

Panvel

ArabianSea

BOMBAY

Figure 6.1 Cluster of Nodes of Navi Mumbai

Cluster 1

Cluster 2

Malathi Ananthakrishnan Chapter 6: Interpretation and Discussion 66

Figure 6.2 shows that different

factor scores influence the two

clusters. Cluster 1 is linked to

score 1 and cluster 2 to score 2

while score 3 exerts almost equal

influence on both cluster.

Further, Figure 6.3 shows the strength of variables, which are contributing to the clustering.

Cluster 1 is influenced by family size, previous place of residence and tenure while cluster 2

is affected by income, education and language. The variables, number of earners and

religion, have an equal influence on the two clusters.

Analysis weighted by population

21

100

80

60

40

20

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-20

EARNER

EDUCATN

FAM.SIZE

INCOME

LANGUAGE

MIGRATN

RELIGION

TENURE

Kopar-khairaSanpada

Panvel

Kopar-khaira

Figure 6.3 Average Linkage between Variables

1454367116 1454367116 1454367116N =


Figure 6.2 Average Linkage between Factor Scores

21

3

2

1

0

-1

-2

-3

Factor score 1

Factor score 2

Factor score 3

Airoli


6.2 Sub-regional Scale

At the sub-regional scale, there were twenty-three sectors. More variables could also

be used to study these cases. The grouping of the sectors into three clusters is shown in

Figure 6.4.

Figure 6.4 Clustering of the Sectors of Vashi

Cluster 3 (red) has sectors 1, 6, 9, 10, 15, 16, 20, 21, Cluster 2 (green) has sectors 2,

3, 4, 8, 9A, 10A, 12, 14, 16A, 17, 28 and 29, and 26, and Cluster 1 (yellow) has only sector

5.

17

9A

10A

10

4 3 2

167

5

9

8

12

16

15

14

29

2826

21

2016A


Figure 6.5 shows that the

three clusters are influenced by

different factor scores. Cluster 1 is

influenced by all three scores,

cluster 2 more strongly by score 2

and cluster 3 by score 3.

Figure 6.6 Average Linkage between Variables

Figure 6.6 shows the average linkage between the variables. Cluster 2 is the most

significant. Ownership, income and the language Marathi dominate it. This is a

socioeconomic construct, but dominated by an ethnic variable. Cluster 1 is also

differentiated by Malayalam, another ethnic variable. Cluster 3 is an outlier.

321

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EARNER

EDUCATION

INCOME

MARATHI

MALAYALAM

MEN

MIGRATION

OWNRSHIP

HINDU

MUSLIM

WOMEN

738189216497 738189216497 738189216497N =


Figure 6.5 Average Linkage between Groups

321

4

2

0

-2

-4

-6

Factor Score 1

Factor Score 2

Factor Score 3

8


6.2.1 Socioeconomic Status and Sector Theory

As discussed in the literature review, the study of many cities across the world shows

that the socioeconomic construct displays a sector pattern. Figure 6.7 shows a scenario that

could be expected from the mapping of any of the socioeconomic variables. The two

variables selected were income and number

of earners. In both maps the median range is

represented by the color purple. The colors

red and orange are immediately above, and

immediately below the median value while

yellow and green represent the outliers or

extremes.

Figure 6.7 Hypothetical Sector Patternfor Socioeconomic Variables

Figure 6.8 Distribution of Number of Earners Figure 6.9 Distribution of Income

The pattern that emerges on mapping of the number of earners and income variables

does not show any particular pattern (Figure 6.8, Figure 6.9).


6.2.2 Family Status and Concentric Zone Theory

The study of many cities across the world shows that the family status construct

displays a concentric pattern. Figure 6.10 shows a possible scenario in Vashi for a variable

representing the family status. The variable selected to describe the family status is

ownership of apartment. In the descriptive analysis, this variable showed a great degree of

variability. The purple color represents the

range within which the mean falls. The colors

red and orange are immediately above, and

immediately below the median value while

yellow and green represent the outliers or

extremes.

Figure 6.10 Hypothetical Concentric ZonePattern for Family Status Variables

The number of sectors which falls within the mean range is very small. Sectors which have

slightly more or slightly less percentage of

apartments built by CIDCO are represented by

red and orange. It is important to note that five

sectors are colored green while one sector is

yellow (Figure 6.11). This shows a high

degree of variability in the data.

Figure 6.11 Distribution of Ownership of Apartment


6.2.3 Ethnic Status and Multiple Nuclei Theory

Multiple Nuclei theory supports the spatial pattern of the ethnic factor. A possible solution is

mapped for any ethnic variable in Figure 6.12. A language variable and a religion variable

were selected from the data set for mapping. The mapping of language and religion variables

shows a segregation of both of them. Yellow

and green colors, which represent the

extremes in the data set, are present in both

the variables (Figure 6.13, Figure 6.14). This

is especially true of the variable Muslim,

which shows a largely non-uniform

distribution.

Figure 6.12 Hypothetical Multiple Nuclei Pattern forEthnic Variables

Figure 6.13 Distribution of Households Figure 6.14 Distribution of Householdsspeaking Marathi which follow Islam


6.3 Summary

The set of figures below shows the mapping of the cluster analysis as well as the individual

factor scores.

Figure 6.15 Clustering of Sectors Figure 6.16 Score 1

Figure 6.17 Score 2 Figure 6.18 Score 3

Although the four maps above (Figure 6.15, Figure 6.16, Figure 6.17, Figure 6.18)

show that there is a different colored sector within a group of one color, the multiple nuclei

pattern is not very obvious. However, looking at the descriptive analysis, principal

components analysis, cluster analysis and the mapping collectively, the multiple nuclei

pattern can be inferred. The descriptive analysis brought out the fact that the spatial pattern is


not uniform or heterogeneous. The principal components analysis shows that the cause of

this spatial pattern is ethnicity. The clustering indicates that

some sectors are dissimilar from others. The mapping of individual variables and factor

scores verifies that within a fairly homogeneous group of sectors there exists a dissimilar

sector.

In conclusion, as the pattern is not uniform, the policy has not been successful.

However, a pattern did emerge at this present stage. This is the multiple nuclei pattern of an

ethnically driven spatial organization. The aggregation of household data at the sector scale

has limited this research from drawing out the finer details of the spatial pattern.

6.4 Potential Utility of the Research

This research is a starting point for further studies in spatial patterns in Navi Mumbai.

As Navi Mumbai has been constructed over the last 25 years, the pattern is strongly

influenced by factors as year of occupation of the house and reasons for moving. The policy

of the government to promote social heterogeneity influenced the type of residential

construction in Navi Mumbai.

Future research could involve:

• Delineating the pattern at intervals of time to study the change in pattern,

• scaling down the study to stories of individual households to reach a more

detailed level of interpretation,

• putting forth a new theory to generalize social pattern in planned cities in India,

• examining the policy instruments and policy goals.

Chapter 7: Conclusion

The purpose of this thesis is to delineate the urban social pattern of Navi Mumbai,India. This particular case study was chosen for two reasons: Navi Mumbai is the firstplanned city that is not a capital city or industrial township, and the government had aspecific social and political agenda. One of the social objectives in the planning of NaviMumbai was to use the government machinery to diversify the spatial distribution of thepopulation based on socioeconomic criteria. Ethnic enclaves have always characterizedtraditional settlements in India. The government had a very practical interest in avoidingethnic confrontation. It was also influenced by the concept of the city as a melting pot(Engel, 1991), and formulated a policy to support it. The thesis addresses this socialobjective.

Bombay is the financial and economic capital of India. Navi Mumbai is separatedfrom the metropolis of Bombay only by the Thane Creek. Every effort was taken by thegovernment to make Navi Mumbai an independent city and not a suburb or satellite city toBombay. However, Navi Mumbai is still dependent on Bombay for much of its activity.The important objectives of Navi Mumbai were: attract some of the immigrant population,support an aggressive industrialization policy, raise the standard of living and reduce socialinequalities, and provide an infrastructure which would promote ethnic heterogeneity.

The draft development plan of Navi Mumbai had very strong functional and socialobjectives. Planning policies in Navi Mumbai were strongly influenced by the teachings ofMahatma Gandhi. It was hoped that a majority of the residential construction could beachieved though a policy of swavalambhan (self-reliance) and swatantrya (mutual self-help). The government also decided to take up most of the initial building construction.Housing would be allotted according to the preference of size of dwelling provided byapplicants. Households would normally place this preference based on how much they canpay. The government hoped that this would distribute people based on socioeconomics andbreak barriers based on religion and language.

Traditional Indian cities have always had a strong ethnic component in their urbansocial pattern. The segregation is attributed to the ethnic variables, caste, religion andlanguage. The Hindu laws and treatises specified residential locations for different castes.This was the first cause of separation in residential neighborhoods. Religious tensions havealways existed in India. The Muslims came to India as invaders. The culture of this raceof people is very different from the Hindus. Areas dominated by Muslims are common inmost cities in India. The religious divide was used in the partition of united India into Indiaand Pakistan. The other feature that is unique to India is the existence of many languages.Political and administrative boundaries in independent India were decided on linguisticlines. Partition and the first years of independence were, thus, strongly influenced by ethnicvariables.

The review of secondary source material shows that urban social patterns have beenstudied across the world. Three leading theories put forth were concentric zone theory,sector theory and multiple nuclei theory. These theories explain the urban social pattern

Malathi Ananthakrishnan Chapter 7: Conclusion 75

and its change over time. The concentric zone theory relates the pattern of cities topopulation mobility. Succession and invasion based on social and economic status is thebasic assumption of this theory. Mobility and immigration are the key variables of thistheory. The second theory, sector theory, is an analysis primarily of economic variables.Wedge patterns representing income groups are the outcome of the theory. The multiplenuclei theory proposes that patterns could be arranged around several centers.

Analysis was done to map the urban social pattern of many cities across the world.The methodology used was that of social area analysis. Social area analysis broadlyclassifies variables into three constructs. These are socioeconomic construct, family statusand ethnic status. Heterogeneity of the population is detected if these three constructsemerge from the analysis. That would indicate that enclaves have not been caused byindividual variables. In the case of Navi Mumbai this is important because of the policy toprevent segregation based on ethnic variables.

The constructs of the social area analysis have been found to correspond to the threetheories. Generally the socioeconomic model showed a sectored pattern, the familycomponent showed a concentric ring pattern, and ethnic segregation showed a multiplenuclei arrangement. The variables selected under each construct were drawn out ofexperience of the researchers. In Navi Mumbai, special emphasis has to be given to theethnic components. Two religion variables and two language variables have been selectedrepresenting the ethnic construct. The other variables selected were number of earningmembers, income and education under the socioeconomic construct, and demographics,family size and type of house under family status.

The hypothesis put forth in this study is: no significant difference in key variables isexpected and hence no social segregation will occur. This hypothesis is put forth on theassumption that the social agenda put forth in the Development Plan has been successfullyimplemented. If H0 is false, then the pattern will be explained using the existing theories.Analysis of data was done at two scales. These scales were the regional scale of the nodes(townships), and the sub-regional scale of the sectors (neighborhoods) of Vashi node. Atthe regional scale the analysis was done between the eight nodes to study their similarity.Twenty-three sectors of Vashi were then analyzed. Since, the scale was smaller, theanalysis allowed a more detailed interpretation.

The software package SPSS was used to do the analysis. Four methods were used toanalyze the data. The methodologies were techniques of multivariate analysis. The firstmethodology is a descriptive analysis. The data at both scales is tabulated, and histogramdrawn of the variable selected from each data set. A variation in the data greater than 15%on each side of the mean is considered as unequal distribution. The second methodology isprincipal components analysis (PCA). The PCA reduces the dimensionality of the data intoa more interpretable form. The variables selected are reduced into a smaller number ofconstructs. Using the secondary source material as reference, grouping of variables isexpected to be under the three constructs, socioeconomic, family status and ethnic status.Next, a cluster analysis was done of the cases of the data set. The similarity between the

Malathi Ananthakrishnan Chapter 7: Conclusion 76

nodes and sectors is determined from this. The final stage was mapping of the clusters,thereby, graphically representing the analysis.

The interpretation of the descriptive analysis shows that the distribution of most ofthe variables is not uniform. This is especially true of the ethnic variables. Thedistribution of these variables shows segregation. However, the socioeconomic variablesalso show separation. The principal components analysis shows that the variables are notgrouping under the three constructs. All three new constructs are dominated by an ethnicvariable. This indicates that the urban social pattern is strongly influenced by ethnicity.

The interpretation of the analysis also involves comparing the descriptive analysis,and clustering to the urban social patterns detailed in the secondary source material. As thesocioeconomic variables are expected to take a sectored pattern, family status variablesconcentric zones and the ethnicity variables a multiple nuclei arrangement, they weremapped under expected and observed conditions. None of the variables selected display auniform distribution. The extreme value range in the mapping is important because itrepresents the dissimilarity in the distribution. The overall pattern of Navi Mumbai is oneof multiple nuclei. The center is an ethnic enclave surrounded by socioeconomic variables.

The hypothesis was proved false. The pattern could, however, be explained usingthe theories of urban social patterns. The urban social pattern is best explained as one ofmultiple nuclei. The policy has not facilitated the distribution of the population based onsocioeconomic criteria. This can be attributed to two reasons:

1. Distribution was originally controlled through allotment of government-builthouses based only on purchasing power (and indirectly socioeconomic status).Control is maximum when the government owns all the houses. In Vashi only64% of the houses were built and allotted by the government.

2. Even in the houses built by the government resale has taken place.Redistribution shows that people have aligned themselves based on ethnicvariables.

The research brings to the fore many questions than answers.• Was this an experiment in enhancing quality of life or is it a method for the

government to exert social control?• The concept of the melting pot has to be re-examined. A moral analysis of

segregation has to be done in the context of the Indian culture. How important isit to promote integration when self-sorting has been the natural process?

• Can the Modernist synthesis seeking homogeneity in heterogeneity be used as atemplate for the Indian culture?

• This leads to the question: is the objective valid? Does it have to be redefined oris the implementation strategy to be modified?

At this stage it appears that a detailed analysis of the policy instrument and policy goals mustbe undertaken. The objective, allotment procedure, physical design and the institutionalframework need to be examined closely to realize their full impact and to understand theresults in their context. In conclusion, although the policy is noble in its aims and aspiration,it has not succeeded at this stage. The spatial distribution of households is still characterizedby traditional Indian values of ethnic segregation.

77

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Glossary of Terms

Term MeaningCuadra Spanish measurementJali Carved screensMasjid MosquePadas Subdivisions of the cosmic universePanchayati Self-governmentPucca DurablePurdahs EnclosurePurushasukta Hindu treatiseRashtrabasha Language of the StateSwadeshi Fullest utilization of local resourcesSwatantrya Self-motivation and self-helpSwavalambhan Self-relianceVastupurusha mandala Terrestrial representation of the cosmic universeVastushastra Science of architecture and planning

Appendix A

March 1958 Study group on Greater Bombay set up under the chairmanship ofMr. S. G. Barve.

July 1958 Bombay Municipal Corporation decided to prepare a developmentplan for Greater Bombay.

February 1959 The study group on Greater Bombay recommended a rail-cum-roadbridge across the Thane creek.

July 1964 Development plan for greater Bombay was submitted to the StateGovernment.

March 1965 A Committee under Dr. D. R. Gadgil was appointed to formulatebroad principles of regional planning for Bombay and Poona.

March 1966 The Gadgil Committee recommended regional planning legislationand regional planning boards.

January 1967 Maharashtra Regional and Town Planning Act 1966 was passed.July 1967 Bombay Metropolitan and Regional Planning Board was constituted.January 1970 The Board published the Draft Plan with recommendations to set up a

twin city.February 1970 State government notified privately owned land in Navi Mumbai for

acquisition.March 1970 CIDCO was formed.March 1971 CIDCO was designated as New Town Development Authority for

Navi Mumbai.August 1973 The Bombay Metropolitan regional Plan was approved by the State

government.October 1973 CIDCO published its Draft Development Plan.

Appendix B

The 7Vs (les sept voies)

The 7V Rule was studied in 1950 at the UNESCO’s request (Le Corbusier, 1961). One

discovered that with 7 types of roads, the man of the mechanical civilization could:

cross continents: V1arrive in town: V1go to essential public services: V2cross at full speed, without interruption, the territory of the town: V3dispose of immediate accesses to daily needs: V4reach the door of his dwelling: V5 and V6send youths to the green areas of each sector, where schools and sports grounds arelocated: V7.

Appendix CNumber of earningmembers

Sectorno.

1 2 3 4

1 64.04 26.81 7.26 1.892 57.67 28.57 8.99 4.763 68.60 24.42 5.81 1.164 70.26 23.08 5.64 1.035 46.79 40.37 11.01 1.836 65.59 27.13 6.48 0.817 62.16 30.41 6.08 1.358 52.07 30.58 9.92 7.449 73.58 20.64 3.77 2.00

10 74.19 19.89 5.16 0.7610A 50.00 35.71 11.43 2.86

12 65.22 26.09 8.70 0.0014 77.52 18.28 3.57 0.6315 72.31 20.06 5.09 2.5416 65.69 29.29 4.60 0.42

16A 71.29 22.49 3.83 2.3917 61.96 27.17 8.23 2.6420 69.23 21.15 5.77 3.8521 63.57 23.43 9.51 3.4826 77.68 16.31 3.86 2.1528 52.38 38.10 0.00 9.5229 82.25 11.26 4.76 1.739A 74.28 21.38 3.62 0.72

mean 66.01 25.33 6.22 2.43std dev 9.40 6.89 2.79 2.25

HouseholdIncome

Sectorno.

uptoRs.1250

1251-2650

2651-4450

4451-7500

7500-10000

10001-15000

15000+

1 3.16 24.68 34.49 22.15 9.49 4.11 1.902 1.62 7.57 25.41 37.84 18.38 7.57 1.623 1.18 6.47 28.82 36.47 15.29 8.82 2.944 0.53 1.07 18.72 44.39 20.86 10.70 3.745 2.75 26.61 16.51 24.77 22.02 4.59 2.756 2.52 11.76 23.11 24.79 18.07 13.45 6.307 11.56 7.48 39.46 21.77 14.97 0.00 4.768 0.00 2.59 9.48 27.59 18.10 23.28 18.979 2.46 17.36 36.39 31.02 7.28 4.26 1.23

10 1.36 26.74 28.10 27.33 11.63 4.07 0.7810A 0.00 0.00 16.92 30.77 26.15 15.38 10.77

12 13.04 4.35 8.70 17.39 34.78 17.39 4.3514 0.64 6.14 25.00 35.17 22.67 7.20 3.1815 0.90 11.73 47.97 28.27 7.22 3.76 0.1516 1.26 12.55 30.96 33.47 12.97 7.53 1.26

16A 0.49 3.90 14.63 40.49 23.41 12.20 4.8817 0.48 0.80 5.94 37.08 32.10 15.41 8.1920 6.45 38.71 34.19 16.13 3.87 0.65 0.0021 2.09 39.07 35.81 16.51 5.58 0.47 0.4726 0.86 21.89 45.92 21.46 8.15 1.72 0.0028 0.00 0.00 10.00 35.00 25.00 20.00 10.0029 0.00 0.00 24.89 37.99 23.14 10.92 3.069A 1.09 2.18 10.55 42.18 25.09 13.45 5.45

mean 2.37 11.90 24.87 30.00 17.66 9.00 4.21stddev 3.45 12.16 12.15 8.40 8.48 6.52 4.42

Highest Level ofEducation

Sectorno.

illiterate

children

primary

secondary

highschool

vo-tech BS MS PhD

1 3.79 3.50 11.81 42.27 10.71 3.43 22.16 2.19 0.152 3.67 4.01 11.01 45.07 9.06 2.18 21.44 2.64 0.923 2.59 3.27 12.38 37.28 10.61 2.18 27.21 3.81 0.684 1.23 3.08 13.44 37.98 7.64 2.47 28.24 4.44 1.485 3.81 5.01 15.03 44.89 6.81 5.41 14.43 4.01 0.606 2.54 2.88 9.85 34.51 7.96 3.54 33.63 4.65 0.447 1.73 2.35 10.52 31.71 7.06 4.71 34.85 5.65 1.418 4.38 4.03 9.98 29.60 9.11 2.98 31.87 5.25 2.809 3.03 4.91 17.24 44.38 8.12 1.80 17.55 2.64 0.31

10 3.46 5.34 16.94 43.06 8.80 2.49 16.32 3.24 0.3510A 1.81 4.71 9.42 23.55 9.06 2.90 32.97 9.78 5.80

12 0.00 5.75 4.60 17.24 8.05 2.30 59.77 2.30 0.0014 2.19 4.81 14.11 34.61 9.68 1.75 27.94 4.05 0.8715 4.23 3.82 15.26 48.95 9.37 2.50 14.07 1.45 0.3416 3.38 3.28 11.09 46.58 9.35 2.89 20.83 2.12 0.48

16A 2.02 4.15 13.69 31.87 9.43 2.69 26.94 7.30 1.9117 1.65 4.24 10.59 29.47 8.97 1.39 35.32 5.74 2.6320 19.07 8.90 22.74 40.68 5.08 0.42 2.97 0.14 0.0021 13.91 5.81 19.03 50.09 5.40 0.64 4.48 0.64 0.0026 3.28 7.95 13.13 51.14 7.58 2.90 12.63 1.14 0.2528 0.00 5.68 12.50 20.45 7.95 2.27 47.73 3.41 0.0029 1.15 3.45 11.03 34.25 11.15 1.72 30.92 5.06 1.269A 1.64 4.09 11.82 30.18 7.73 2.91 32.45 6.18 3.00

mean 3.68 4.57 12.92 36.95 8.47 2.54 25.94 3.82 1.12stddev 4.29 1.55 3.72 9.40 1.52 1.11 12.92 2.26 1.37

MalePopulation

Sectorno.

below3

4,5 6 to 9 10 to15

16 to21

22 to24

25 to44

45 to59

60+

1 4.10 2.54 4.38 11.44 15.25 6.36 32.49 19.63 3.812 4.12 2.39 5.42 14.75 12.15 7.16 31.02 17.14 5.863 4.56 3.29 6.58 16.20 12.91 5.82 29.11 16.96 4.564 3.29 2.59 7.76 12.47 13.65 5.18 30.82 16.00 8.245 2.05 2.87 9.84 19.67 12.70 3.28 31.56 14.34 3.696 2.80 1.40 4.60 12.60 13.60 6.00 27.60 23.00 8.407 2.23 2.87 3.82 10.51 15.61 4.78 29.94 21.66 8.608 3.46 2.42 6.57 10.38 12.11 6.57 27.34 20.42 10.739 5.46 4.12 8.48 17.01 10.12 3.97 37.25 10.91 2.68

10 5.80 3.73 9.45 14.84 12.02 3.40 34.83 12.02 3.9010A 2.22 4.44 2.96 8.89 12.59 5.93 28.89 21.48 12.59

12 6.12 2.04 4.08 12.24 12.24 6.12 36.73 14.29 6.1214 5.39 4.56 8.20 11.93 10.27 3.32 37.76 13.80 4.7715 3.29 3.04 7.88 17.32 13.78 3.97 35.69 11.67 3.3516 3.26 3.07 6.91 14.20 14.59 4.80 30.71 18.04 4.41

16A 3.25 3.68 7.36 16.67 12.34 3.03 31.82 16.02 5.8417 3.93 2.97 5.86 10.99 11.14 4.83 34.74 17.37 8.1720 8.77 5.26 9.52 15.04 10.78 6.77 34.84 8.02 1.0021 4.54 3.45 8.40 20.42 11.60 4.79 33.19 11.26 2.3526 6.87 4.66 6.87 8.65 7.98 8.65 46.12 7.32 2.8828 5.66 1.89 11.32 9.43 9.43 7.55 35.85 16.98 1.8929 4.51 2.87 7.38 17.62 8.81 2.46 42.21 9.43 4.719A 4.35 3.30 5.74 16.52 9.74 4.35 29.57 20.87 5.57

mean 4.35 3.19 6.93 13.90 11.97 5.18 33.48 15.59 5.40stddev 1.62 0.95 2.13 3.41 1.99 1.60 4.59 4.52 2.90

FemalePopulation

Sectorno.

below3

4,5 6 to 9 10 to15

16 to21

22 to24

25 to44

45 to59

60+

1 3.57 1.86 7.61 10.87 17.55 7.30 33.39 13.98 3.882 4.93 3.20 5.42 12.32 12.07 6.16 37.68 12.07 6.163 4.57 3.14 6.29 12.86 12.29 6.86 40.29 9.43 4.294 3.17 4.22 7.39 13.72 10.29 4.22 40.11 11.08 5.805 4.35 1.98 9.88 16.21 14.23 4.74 36.76 9.09 2.776 3.50 1.64 6.31 12.85 9.35 5.84 34.58 19.86 6.077 2.82 2.19 5.96 11.60 11.60 7.21 32.29 17.87 8.468 4.32 1.80 5.40 11.15 13.31 5.76 33.45 17.27 7.559 5.84 3.82 9.49 16.01 9.66 4.27 41.52 6.40 2.98

10 5.31 3.36 9.97 14.91 10.44 5.13 38.96 7.92 4.0110A 6.43 4.29 5.71 6.43 12.14 7.14 32.14 20.00 5.71

12 6.06 0.00 3.03 6.06 15.15 6.06 45.45 15.15 3.0314 4.35 3.88 6.93 11.63 9.64 6.58 42.07 10.34 4.5815 4.35 2.90 9.32 15.51 10.77 3.74 41.94 8.33 3.1316 4.09 1.56 5.46 18.13 14.62 3.90 38.01 10.14 4.09

16A 4.72 2.59 8.25 16.04 10.38 3.54 39.39 11.32 3.7717 4.35 3.13 5.72 10.07 12.28 5.72 38.22 14.49 6.0320 8.44 4.55 12.66 17.86 7.79 6.17 37.99 3.57 0.9721 5.80 2.95 10.18 22.81 11.41 4.79 34.83 5.09 2.1426 7.06 3.82 5.00 13.82 10.29 12.35 38.53 7.06 2.0628 2.78 2.78 11.11 11.11 2.78 5.56 47.22 13.89 2.7829 2.39 3.71 5.57 13.00 5.57 3.18 52.25 9.55 4.779A 3.87 2.71 8.32 12.96 10.83 5.22 39.65 12.96 3.48

mean 4.66 2.87 7.43 13.39 11.06 5.71 38.99 11.60 4.28stddev 1.46 1.08 2.35 3.68 3.09 1.89 4.83 4.48 1.83

Family SizeSectorno.

single 2 to 3 4 to 5 6 to 7 8 to 10

1 2.18 26.17 54.83 14.95 1.872 1.57 19.37 54.97 19.90 4.193 1.71 24.57 57.71 14.86 1.144 0.51 30.46 54.82 12.18 2.035 0.00 15.45 62.73 20.00 1.826 3.23 36.29 50.40 9.68 0.407 0.66 22.52 62.91 11.92 1.998 0.00 26.23 46.72 15.57 11.489 1.55 23.51 59.38 14.68 0.88

10 0.19 20.49 64.14 14.23 0.9510A 1.43 34.29 54.29 7.14 2.86

12 0.00 58.33 41.67 0.00 0.0014 1.88 36.82 51.26 8.58 1.4615 1.04 20.30 61.63 15.11 1.9316 0.83 22.41 63.07 12.45 1.24

16A 0.47 20.85 66.82 9.95 1.9017 1.23 28.92 55.23 12.46 2.1520 0.64 19.87 52.56 25.64 1.2821 0.92 12.67 47.93 32.49 5.9926 2.56 50.43 44.02 2.99 0.0028 0.00 19.05 66.67 14.29 0.0029 1.30 44.16 44.16 9.09 1.309A 1.79 33.21 54.64 10.36 0.00

mean 1.07 28.19 55.35 13.34 2.05stddev 0.86 11.50 7.53 6.98 2.53

Type ofHousing

Sectorno.

CIDCO Pvt.House

Pvt co-opsociety

Pvtcommercial

Other

1 100.00 0.00 0.00 0.00 0.002 48.40 1.60 19.68 2.13 28.193 61.90 0.00 38.10 0.00 0.004 45.18 0.00 53.81 0.00 1.025 22.73 0.91 76.36 0.00 0.006 92.21 6.97 0.82 0.00 0.007 89.12 3.40 6.80 0.68 0.008 35.25 62.30 0.00 0.00 2.469 98.77 0.00 0.56 0.67 0.00

10 83.01 1.74 13.13 2.12 0.0010A 2.86 0.00 97.14 0.00 0.00

12 17.39 4.35 39.13 39.13 0.0014 53.07 0.21 46.72 0.00 0.0015 82.52 0.15 17.33 0.00 0.0016 83.82 0.00 16.18 0.00 0.00

16A 7.62 0.00 92.38 0.00 0.0017 0.62 0.15 85.96 12.96 0.3120 100.00 0.00 0.00 0.00 0.0021 99.77 0.00 0.00 0.00 0.2326 100.00 0.00 0.00 0.00 0.0028 0.00 23.81 76.19 0.00 0.0029 42.86 0.87 20.78 12.12 23.389A 2.51 0.00 92.47 0.00 5.02

mean 53.16 4.84 36.07 3.17 2.75stddev 37.61 13.83 35.58 8.82 7.58

TenureSectorno.

before1980

81-85 86-90 91-92 93 94 95

1 43.99 12.34 13.92 11.71 3.16 13.61 1.272 39.57 12.83 26.74 6.95 5.35 6.95 1.603 11.49 32.18 31.61 12.07 5.17 5.75 1.724 5.10 40.82 24.49 12.76 6.63 7.14 3.065 49.53 20.56 16.82 5.61 3.74 1.87 1.876 51.82 12.15 18.62 4.86 4.45 6.88 1.217 42.38 15.23 22.52 7.95 6.62 4.64 0.668 24.59 38.52 12.30 6.56 6.56 10.66 0.829 0.22 52.11 15.19 8.87 6.54 14.19 2.88

10 0.38 37.09 29.06 13.38 6.50 9.94 3.6310A 0.00 48.57 18.57 14.29 12.86 4.29 1.43

12 0.00 0.00 0.00 4.17 33.33 41.67 20.8314 0.42 0.64 27.60 7.64 18.05 36.73 8.9215 8.46 36.35 28.93 10.09 6.82 6.82 2.5216 27.80 39.42 12.86 4.56 5.81 8.30 1.24

16A 0.00 20.38 56.87 7.11 6.16 6.16 3.3217 0.31 16.82 48.13 11.68 7.94 9.03 6.0720 0.00 35.26 28.85 4.49 12.82 10.26 8.3321 13.02 44.65 17.91 6.28 4.65 7.44 6.0526 0.00 0.00 0.00 0.00 31.88 48.03 20.0928 0.00 0.00 0.00 0.00 0.00 75.00 25.0029 0.87 0.87 1.73 4.33 47.19 31.17 13.859A 0.00 31.43 32.50 12.86 5.71 12.50 5.00

mean 12.54 24.36 21.42 7.57 11.13 16.61 6.37stddev 18.02 17.39 14.56 4.08 11.60 18.40 7.15

Previous Place ofResidence

Sectorno.

Islandcity

Wnsuburbs

Ensuburbs

Thane Vashi NaviMumbai

Insidestate

Out ofstate

Intl.

1 21.45 4.42 17.03 8.83 24.29 8.83 8.20 6.62 0.322 21.05 8.42 24.74 2.63 27.37 10.53 2.63 2.63 0.003 19.30 3.51 36.26 5.26 23.39 2.92 4.09 5.26 0.004 14.58 7.81 23.96 2.60 38.54 5.73 4.69 2.08 0.005 14.95 0.00 18.69 2.80 26.17 25.23 12.15 0.00 0.006 12.35 6.58 35.80 4.94 20.99 7.00 4.12 7.00 1.237 21.19 9.93 37.09 5.30 18.54 3.31 0.00 4.64 0.008 27.05 8.20 27.05 0.82 19.67 2.46 1.64 7.38 5.749 18.48 8.51 30.57 3.25 28.44 5.38 2.91 2.46 0.00

10 15.71 6.90 28.74 4.79 30.84 2.68 3.26 7.09 0.0010A 20.29 7.25 31.88 0.00 24.64 2.90 2.90 10.14 0.00

12 20.83 12.50 12.50 0.00 33.33 8.33 4.17 8.33 0.0014 18.03 6.71 27.25 2.52 31.24 5.45 2.31 5.03 1.4715 15.35 5.37 31.30 2.83 36.07 5.07 3.58 0.45 0.0016 15.48 1.67 34.73 3.77 28.03 6.69 4.60 4.60 0.42

16A 17.62 7.14 25.24 6.67 26.67 8.10 4.76 3.33 0.4817 29.61 6.98 23.10 3.88 20.93 3.57 1.40 8.53 2.0220 12.26 3.87 16.13 1.29 47.10 16.77 2.58 0.00 0.0021 19.63 3.23 26.10 0.69 21.02 22.17 5.54 1.62 0.0026 15.81 3.85 17.95 5.98 39.32 8.55 3.42 4.27 0.8528 4.76 33.33 9.52 0.00 47.62 4.76 0.00 0.00 0.0029 11.26 4.33 22.94 1.30 45.02 9.52 1.30 4.33 0.009A 12.19 8.24 28.67 2.15 32.26 3.58 2.51 10.39 0.00

mean 17.17 7.47 25.92 2.88 30.33 7.76 3.39 4.53 0.55stddev 5.36 6.43 7.54 2.01 8.82 6.15 2.45 3.24 1.29

LanguageSectorno.

Marathi

Hindi Gujarathi

Malayalam

Punjabi Tamil Kannada

Bengali Other

1 51.09 8.72 5.30 9.97 3.43 4.36 4.05 2.18 10.902 44.50 10.47 2.62 7.33 6.81 4.71 1.57 1.57 20.423 32.57 17.14 1.71 8.00 12.00 6.29 2.29 3.43 16.574 46.70 8.12 2.03 9.64 3.55 8.63 2.03 2.03 17.265 77.27 0.91 2.73 2.73 0.00 0.00 1.82 3.64 10.916 33.87 17.34 4.44 5.24 7.66 8.47 2.82 4.03 16.137 37.09 15.23 9.27 5.96 5.96 6.62 1.32 1.99 16.568 22.13 20.49 9.84 4.92 14.75 4.10 4.10 2.46 17.219 50.66 10.26 3.53 9.60 2.10 5.19 3.53 2.76 12.36

10 44.21 21.44 2.09 6.45 2.85 5.31 3.98 4.17 9.4910A 24.29 15.71 1.43 24.29 2.86 4.29 2.86 8.57 15.71

12 8.33 29.17 16.67 4.17 16.67 0.00 0.00 4.17 20.8314 19.87 12.55 32.43 7.95 4.81 5.23 2.51 3.97 10.6715 57.33 13.19 2.37 4.89 4.89 3.85 1.93 1.93 9.6316 54.36 11.20 4.98 6.22 3.73 2.90 3.32 2.49 10.79

16A 51.66 10.90 3.32 7.58 2.37 4.74 4.27 2.84 12.3217 21.38 14.15 16.77 8.00 7.54 7.54 1.54 4.15 18.9220 60.26 13.46 5.77 3.85 0.00 1.92 3.21 0.00 11.5421 61.75 14.98 3.92 1.61 1.15 2.30 1.38 0.00 12.9026 48.72 12.39 4.70 10.26 2.99 3.85 5.13 4.27 7.6928 28.57 14.29 0.00 9.52 19.05 9.52 0.00 4.76 14.2929 25.54 27.27 7.36 6.49 4.76 5.63 1.73 3.90 17.329A 20.34 12.76 3.79 12.76 4.83 7.93 4.83 8.28 24.48

mean 39.61 14.70 6.44 7.61 5.97 4.96 2.55 3.43 14.73stddev 17.36 6.08 7.30 4.56 5.22 2.59 1.40 2.08 4.29

ReligionSectorno.

Hindu Christian

Islam Jain Sikh Buddhist

Other

1 79.18 11.04 5.68 0.32 2.52 0.95 0.322 80.42 5.82 7.41 0.53 3.70 0.53 1.593 75.29 9.20 8.62 0.57 4.60 1.15 0.574 84.26 6.09 6.60 0.51 0.51 2.03 0.005 81.65 9.17 2.75 0.00 0.00 6.42 0.006 83.81 9.72 4.05 0.00 2.02 0.40 0.007 76.82 10.60 8.61 1.32 1.99 0.00 0.668 72.13 8.20 10.66 3.28 4.10 0.00 1.649 84.85 7.19 5.20 0.22 0.55 1.88 0.11

10 80.76 8.76 5.33 0.00 1.52 3.62 0.0010A 72.86 22.86 1.43 1.43 1.43 0.00 0.00

12 79.17 12.50 4.17 0.00 4.17 0.00 0.0014 88.26 5.45 2.73 1.68 1.68 0.21 0.0015 83.53 4.01 6.82 0.45 2.82 2.37 0.0016 88.80 3.32 6.64 0.00 1.24 0.00 0.00

16A 91.47 4.74 1.42 1.42 0.47 0.47 0.0017 85.03 5.56 3.70 2.78 1.85 0.46 0.6220 86.54 0.64 5.13 0.00 0.00 7.69 0.0021 81.67 1.16 15.31 0.23 0.46 1.16 0.0026 86.75 5.13 5.98 0.43 1.71 0.00 0.0028 100.00 0.00 0.00 0.00 0.00 0.00 0.0029 86.34 6.61 4.85 0.88 0.88 0.44 0.009A 73.93 8.21 15.00 0.36 1.79 0.36 0.36

mean 82.92 7.04 6.02 0.73 1.70 1.33 0.25stddev 6.55 4.78 3.91 0.92 1.40 2.09 0.49

Appendix D

Factor Analysis

Descriptive StatisticsMean Std. Deviation Analysis N

EARNER 73.2091 4.6076 81659EDUCATN 8.7800 3.8538 81659FAM.SIZE 53.0814 4.4115 81659INCOME 32.6705 5.9974 81659LANGUAGE 49.1087 9.8863 81659MIGRATN 28.8271 8.6486 81659RELIGION 86.0403 3.7870 81659TENURE 37.9885 16.2670 81659

CommunalitiesInitial Extraction

EARNER 1.000 .926EDUCATN 1.000 .875FAM.SIZE 1.000 .985INCOME 1.000 .928LANGUAGE 1.000 .939MIGRATN 1.000 .824RELIGION 1.000 .879TENURE 1.000 .832Extraction Method: Principal Component Analysis.

Total Variance ExplainedInitial Eigenvalues

Total % of Variance Cumulative %1 4.446 55.571 55.5712 1.946 24.320 79.8903 .796 .955 89.8454 .429 5.356 95.2025 .293 3.660 98.8626 8.039E-02 1.005 99.8677 1.064E-02 .133 100.0008 5.851E-17 .314E-16 100.000Extraction Method: Principal Component Analysis.

Rotation Sums of Squared LoadingsTotal % of Variance Cumulative %

1 3.468 43.347 43.3472 1.902 23.771 67.1183 1.818 22.728 89.845

Component MatrixComponent1 2 3

EARNER .804 .470 .244EDUCATN -.136 .882 -.278FAM.SIZE -.926 .293 .202INCOME .430 .862 -1.317E-02LANGUAGE .937 -.230 -8.383E-02MIGRATN -.785 -7.468E-03 .455RELIGION .685 8.925E-02 .634TENURE -.880 .236 4.454E-02Extraction Method: Principal Component Analysis.

Rotated Component MatrixComponent1 2 3

EARNER -.446 .484 .702EDUCATN .201 .900 -.155FAM.SIZE .951 .107 -.264INCOME -.156 .881 .358LANGUAGE -.888 -7.766E-02 .379MIGRATN .878 -.230 -2.898E-02RELIGION -.255 4.796E-04 .902TENURE .822 .101 -.381Extraction Method: Principal Component Analysis.

Appendix E

Cluster

Case Processing SummaryCasesValid Missing TotalN Percent N Percent N Percent8 100.0 0 .0 8 100.0a Squared Euclidean Distance usedb Average Linkage (Between Groups)

Average Linkage (Between Groups)

Agglomeration Schedule

Stage Cluster 1 Cluster 2 Coefficients1 5 6 .5812 2 7 2.9463 5 8 4.1744 1 2 4.6175 3 4 7.9196 1 5 9.2997 1 3 10.108

Cluster Membership

1:Vashi 12:Nerul 13:Belapur 24:Kalamboli 25:Panvel 16:Kopar-khaira 17:Airoli 18:Sanpada 1

Appendix F

Factor Analysis

Descriptive StatisticsMean Std. Deviation Analysis N

EARNER 66.3183 7.9628 19127EDUCATN 40.5760 7.1339 19127INCOME 27.9421 10.9768 19127LANGUAG1 46.5535 15.7324 19127LANGUAG2 6.9114 3.7719 19127MEN 38.0484 3.3934 19127MIGRATN 52.9759 9.5580 19127OWNRSHIP 66.4424 35.6247 19127RELGION1 82.3839 4.7307 19127RELGION2 6.8628 3.9142 19127WOMEN 33.0375 3.5835 19127

CommunalitiesInitial Extraction

EARNER 1.000 .856EDUCATN 1.000 .836INCOME 1.000 .855LANGUAG1 1.000 .889LANGUAG2 1.000 .527MEN 1.000 .675MIGRATN 1.000 .571OWNRSHIP 1.000 .801RELGION1 1.000 .722RELGION2 1.000 .568WOMEN 1.000 .721Extraction Method: Principal Component Analysis.

Total Variance ExplainedInitial Eigenvalues Rotation Sums of Squared Loadings

Component Total % of Variance Cumulative % Total % of Variance Cumulative %1 3.843 34.937 34.937 2.750 25.001 25.0012 2.438 22.161 57.098 2.690 24.453 49.4553 1.740 15.819 72.917 2.581 23.463 72.9174 .938 8.523 81.4415 .688 6.257 87.6986 .466 4.238 91.9357 .359 3.265 95.2008 .290 2.638 97.8389 9.854E-02 .896 98.73410 9.136E-02 .831 99.56411 4.794E-02 .436 100.000Extraction Method: Principal Component Analysis.

Component MatrixComponent1 2 3

EARNER .246 .748 .487EDUCATN .880 -.234 8.427E-02INCOME .803 8.915E-04 .458LANGUAG1 .773 -.373 -.391LANGUAG2 -.612 .310 .239MEN 0.096 .816 -5.093E-03MIGRATN -.500 4.042E-02 .565OWNRSHIP .777 -.131 .424RELGION1 .473 .522 -.475RELGION2 .127 -.448 .592WOMEN .538 .657 -2.071E-02Extraction Method: Principal Component Analysis.

Rotated Component MatrixComponent1 2 3

EARNER .351 -.366 .774EDUCATN .709 .575 5.704E-02INCOME .869 .201 .246LANGUAG1 .333 .877 -9.610E-02LANGUAG2 -.316 -.647 9.141E-02MEN -.110 -.130 .804MIGRATN 0.046 -.742 -.136OWNRSHIP .855 .240 .113RELGION1 -.120 .524 .658RELGION2 .596 -.231 -.399WOMEN .214 .210 .795Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.a Rotation converged in 6 iterations.

Appendix G

Cluster

Agglomeration ScheduleCluster Combined Stage Cluster First Appears

Stage Cluster 1 Cluster 2 Coefficients Cluster 1 Cluster 2 Next Stage

1 2 6 .114 0 0 32 9 10 .574 0 0 53 1 2 .584 0 1 94 12 17 .653 0 0 85 9 14 .751 2 0 116 15 18 .837 0 0 137 3 7 1.032 0 0 128 12 16 1.411 4 0 189 1 4 1.515 3 0 1310 13 22 1.840 0 0 1911 9 20 1.904 5 0 1512 3 23 2.108 7 0 1713 1 15 2.151 9 6 1514 8 11 2.487 0 0 1715 1 9 3.726 13 11 1616 1 19 4.558 15 0 2017 3 8 4.799 12 14 2018 12 21 5.309 8 0 1919 12 13 6.449 18 10 2120 1 3 8.052 16 17 2121 1 12 11.142 20 19 2222 1 5 13.918 21 0 0

Cluster MembershipCase 3 Clusters1:1 12:2 13:3 14:4 15:5 26:6 17:7 18:8 19:9 110:10 111:10A 112:12 313:14 314:15 115:16 116:16A 317:17 318:20 119:21 120:26 121:28 322:29 323:9A 1


Date of Birth: 30 June 1973

Education: Master of Urban and Regional Planning May 1998 Virginia Polytechnic Institute and State University, Blacksburg, VA

Bachelor of Architecture May 1996University of Pune, Pune, India

Experience Graduate Research Assistant to Dr. J. O. Browder, Professor, Department of Urban Affairs and Planning, Aug. 1997 – May 1998

Graduate Research Assistant to Dr. P. L. Knox, Associate Dean for Academic Affairs,College of Architecture and Urban Studies, Virginia Tech. Aug. 1996 - May 1997

Worked as an Architect with Suyojan Architects, Pune, India May - July 1996.

Worked as an intern with Narendra Dengle Architects, Pune, India. Dec. 1994 - Mar. 1995

Worked with the Indian National Trust for Art and Cultural Heritage May 1993 - May 1994

Worked as an intern at Historic Boulder, Boulder, CO, USA. April - July 1992

Honors and Affiliations• Invited to Phi Kappa Phi National Honor Society, October 1997.• Awarded Virginia Citizens Planning Associate Fellowship - Outstanding First Year Graduate

Student, May 1997.• Student member American Planning Association.• Registered Architect under Council of Architecture, New Delhi, India.• Rank holder of the University of Pune.• Won first prize (three member team) for Formica Interior design competition, 1995.• Won first prize (three member team) in a design competition - Reclaiming a derelict river, 1994.