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South -Asian Journal of Multidisciplinary Studies (SAJMS) ISSN:2349-7858:SJIF:2.246:Volume 3 Issue 5

Spatial Distribution and Concentration of Slums

Manoj Banerjee1 and Milan Karmakar

2

Abstract- Slums are the settlement with distress socio economic condition. Slums become an

indispensable part of urban morphology in almost all urban centers of developing countries. But

distribution pattern of this type of settlement over urban environment is not always the same.

Sometimes slums are concentrated in city center and sometimes in periphery. A Little attempt

has been made to unearth this spatial variation. This paper is an attempt to find out the nature of

slum concentration in a particular area as well as responsible factors. Bilaspur city (Chhattisgarh,

India) has been chosen as the study area for this purpose.

Key words- Urban morphology, Residential segregation, Slum concentration

Introduction- World population is growing with almost 1 billion in every 13 years

(USCB).After the United Nations conference on Human settlement in 1976 world urban

population takes only two decades to double itself. Rapid urbanization, especially in developing

countries associates with slum formation .33% or urban population of developing countries lived

in slums (UN habitat 2012).In India 17.4% of urban Indian households lived in slums (2011

census of India). Bilaspur is a city of Chhattisgarh where urban growth rate is 20% (2001-2011)

and slums are growing at17% rate per decade

(2001-2011). From 1990 to 2009 total area

covered by urban population was increased

from 8.31 sq km to 40.33 sq km. Most of the

old slums has age in between 70-80 years

where newly formed slums of Bilaspur have

age in between 25-30 year. As per the survey

conducted under Rajiv Awas Yojana there are

total 134 slums in the city among which 56 are

notified. Total area under BMC (Bilaspur

Municipal Corporation) is 27.9 sq km in which

7.11sq km area lies in the northern portion of

river Arpa. Form of human settlements and the

process of their formation and transformation

is known as urban morphology. E.W.Burges

and Alanso mills models are some pioneer

work in regard to spatial land use in urban

morphology. Our special focus of this study was to find out the nature of distribution of slum

1 Guest Lecturer, Department of Geography, Panchakot Mahavidyalya, Neturia (Purulia).West Bengal, India.

Email Id: [email protected]/, Ph No. 7501522757 2 GIS Engineer in WAPCOS Limited, (Govt. of India). Haryana, India.

Email Id: [email protected]. / [email protected]. Ph No. 9775289034

mailto:[email protected]/

mailto:[email protected]

mailto:[email protected]


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settlement in BMC and depict the actual facts which are responsible for such concentration as a

part of urban morphology.

Objective:-

i. To Study the existing spatial pattern of Slums.

ii. To Study the nature of slum concentration.

iii. To Study location of Slums on Urban Morphology.

iv. To Study prime factor, responsible for slum concentration and growth.

Review of Literature: - Slums have emerged due to rapid urbanization. In the first half of the

19th century Engles Fredrick (1844) observed slums in England and mentioned the worst parts of

a town. Rene Villerne (after 1832) cited relation in between slum poverty and poor health in

different administrative parts of Paris. Charles Both (1889) in his book “Life and labour of the

people in London" prepared a poverty map of old Nichole which was a slum in the east end of

London. Racob Riis (1890) in his book “How the other half lives” highlighted poor living

conditions in New York city slums during 1880s.Slums of London were observed and depicted

by many social researches and journalist in the second half of the 19th century. Henny Mayhew's

“London labour and London poor” (1851), "The million people city" (1853) by John

Garwood."Rugged London" (Holling Head 1861). "The seven course of London"(Greenwood

1869), "Street Life in London"(Adolphe Simon ,1877), "How the poor live" (George Sims 1883),

"East London" (Walter Besant 1899) are some great work in this regard. In 20th century B.S

Routree's "Poverty- A study of town life" (1901) was a depiction of slum life. "The people of the

Abyss" was a description of miserable condition of slum life by Jack in 1902."Slum Travelers:

Ladies and London poverty, 1860-1920", by Ellen Ross (2007) depicted the prevailing slum

condition in first half of the 20th century in London."The slum and the Ghetto: immigrants,

Blacks and reformers in Chicago, 1880-1930" by Thomas Lee Philpott (1991) also shown the

bad socio economic condition of slum dwellers in first half of the 20th century. Lots of work was

done after 1960 in regard to slum, some were acute case study like (Anderson's Birmingham

1960). In these studies slums were established as a region of overcrowding (Barrington Kaye

1960) worse dwelling condition (Oscar Lewis, 1961) Concentrated poverty (Charles J Stoves

1962, De Souza 1980) bad health condition (Jatindar 1999, Hatekar and Rude 2003) poor

sanitation ( Geetna and Swaminathan ,1996, Banerjee and Karmakar ,2016) economically

deprived( Patel et all, 2012). Over all socio economic condition of slums in Indian cities are

observed by Ali and Totan 2003, Chandrasekhar 2005, Karan et all 2003.

Slum settlement is a part of urban morphology and urban morphology was especially discussed

by Ecological school. E.W Burges described that desirable place of a city is occupied by

dominant groups and weak sections have a tendency to concentrate in the residual place. In his

concentric zone theory he indicated transition zones are the slum areas. Alansumuth mills model


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highlighted a relation between transport cost or time and living space for shaping urban

morphology. Factorial ecology is comparatively new concept which deals with three factors,

socio economic status, familism and ethnicity. Amenity, employment, exclusionary zoning,

cultural landscape also consider as factors to shape urban space. It is noteworthy that these

researches and models are not well established in the context of developing countries. Factorial

ecology is not an active force in our study area as well as amenity, job opportunity, landscape are

completely negligible to shape urban space. So we applied application of residential segregation.

Residential segregation is the level of dispersion of a particular group in a given geographical

area (Royuela and Vargas 2010).Massey and Denton (1988) cited five dimensions evenness,

exposer, concentration, Centralization and clustering to describe residential segregation as a

multidimensional phenomenon. There are total 17 indexes in regard to these five dimensions (US

department of commerce 2002). In the present study we are used modified dissimilarity index of

culter, Glaeser and Vigdor (1997, 1999) to judge segregation of slum population in respect of

evenness and exposer. “Evenness refers to the differential distribution of two social groups

among areal units in a city "(Massay and Denton 1988, p.287). While exposer "measures the

degree of potential contact or possibility of interaction, between minority and majority group

members "(Massay and Denton 1988, P.287). Use of segregation technique in regard to slum

population is a vital one to judge spatial concentration of slums. Residential segregation shows

most of the slums are situated in government land with illegal tenure (with high segregation

value). So we decided to access the role of government land availability for the development and

concentration of slum.

Hypothesis of study

(i) Availability of government land and the concentration of slums are not correlated.

(ii) Availability of government land is a prime factor for concentration and growth of slum in

a particular area.

Methodology- There are total 55 wards in BMC and 56 notified slums. Modified dissimilarity

index and isolation index by Culteret al (1997, 1999) are taken into consideration to find out

residential segregation in respect of slum population. An Urban morphological map which was

prepared by Z.T Khan in 1980 is used to demonstrate the location of slums. The Correlation

between government land availability and slum population is compared by the regression

equation. Ultimately Z score is used to test hypothesis. All the maps and tables calculation are

prepared with the help of Arc GIS 9.3, ERDS-9.2. Microsoft Excel-2007. The survey data of

Rajiv Awas Yojana 2013 is taken as prime source and field survey has been completed from July

2015 to Feb. 2016.


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Bilaspur City and Spatial Distribution of Slums- Bilaspur is the second largest city after

Raipur in Indian state Chhattisgarh. The city is located precisely at 22°5'21"N and 82°9'17"E it

has an inland location in the Chhattisgarh basin. According to census of India 2011 the city has a

population 331030. BMC has total 55 wards and 128794 slum population. There are total 134

slums in the city among which 56 are notified (RAY 2013).There are total 8 wards in the city

without slum. To judge the nature of spatial distribution of slum population, we used

dissimilarity index and isolation index, which are components of residential segregation

normally use to identify evenness and exposer (Table-01). Especially evenness map has been

prepared in which ward no. 40, 41, 44 in the north of Arpa River and ward no. 12,7,55 in the

south of Arpa River are with high dissimilarity index numbers. In the same manner to judge the

location of slums in urban morphology, we took an urban morphological map of Bilaspur (1980)

prepared by Z.T. khan and Imposed location of slums. It is noteworthy that there are only few

slums located in the central part of the city. Most of the old and large slums are located in the

peripheral area of the city. The mentioned wards with high dissimilarity index bears those slums

.ward no. 40, 41 and 44 are carrying total 10 slums out of 19 in the north portion of city Bilaspur.

In the southern portion this concentration is more dispersed than the north. The Slum population

is highly concentrated in peripheral area with a large slum size like Jhopra Para, Mini mata, Mini

basti slums. It may be pointed out that the slums of south Bilaspur are comparatively smaller in

size than its northern part and most of them are young in respect of age.


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Slum growth and concentration factors- Global report on human settlement (UN-HABITAT,

2003) has mentioned four macro factors for slum growth, which are: 1.Urbanization,

2.Migration, 3.Demographic changes and 4. Poverty. Roy et al (2014) summarized seven main

factors for the growth of slums: 1. Population Dynamics, 2.Economic growth, 3.Housing market

dynamics, 4. Street pattern, 5. Politics of slums, 6. Informal economy, 7. Local topography.

Economic growth leads the process of urbanization and immigration change the spatial form of

demography that is why urban areas face population dynamics. Most of polarized urban land

normally forces lower income group to reside in slums. Most of the real state lobbies occupied

land and polarized Housing condition with high price. Which creates a housing market

dynamics. Street pattern is related to the livelihood of slum dwellers, most of the times


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they are connecting lines for working destination and sometimes working place .Slum politics,

which is actually vote bank of politicians hamper slum development policies. Informal economy

also a boost factor for slum formation. Local negative physical area or topography where urban

people refuse to settle, slum gets its origin due to shortage of urban space. These are the factors

which also influence the location and concentration of slums. It can be cited that all factors

simultaneously not active in a particular region. In Bilaspur particularly the location and

concentration of slums highly influenced by land tenure. Most of the slums are located on

government land or with patta (which is a semi temporal living permit by BMC). In each ward

we computed availability of government land (till available + encroached by slum) and

percentage of slum population, and then formulate a regression equation. In result, it is vivid that

there is a positive correlation between availability of government land and percentage of slum

population. Z score is applied the analyze this hypothesis

i. Null hypothesis (Ho): Availability of government land and concentration of slums are not

correlated

ii. Alternative hypothesis (H1): Availability of government land is a prime factor for

concentration and growth of slum in a particular area.

Test Statics: (Z-test) - (Ref: Table 02, Appendix)

Z -Score Method:-

Z = ∑ 𝑍𝑥 . 𝑍𝑦 [Where ZX = 𝐗−𝐗

𝛔𝐗 and 𝐳𝐲 =

𝐘−𝐘

𝛔𝐘 ]

= 29.8004

Comment: - Since calculation value of Z, which is greater than critical value 1.96 so (Ho) is

rejected at 5% level of significance.

We also prepared a composite thematic map in which availability of government land, slum

population over layed on residential segregation. In this visual representation wards with high

availability of government land (>30%) are highly slums concentrated zone, like ward no. 40, 44

etc. These are the also wards with big slums as well as several in numbers. In the middle part of

the city, wards with no government land are less prone to slum formation.


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Figure No. 04: Residential Segregation Map of Bilaspur Municipal Corporation


186


Conclusion- The Growth of slums is a serious issue in the context of the urban environment.

Such type of settlement is normally created pressure on urban resources if those are not coming

under the city development programme. In our study, we have found out the encroaching

tendency of slums which is a serious issue for future urban development. Most of the slums of

the BMC are on government land. Whenever demolition initiatives were taken BMC had faced

protest by the slum dwellers. But it is a good one in 2013 Rajiv Awas Yojana (a slum eradication

government programme in India) survey was completed and some slums have already been

relocated. Smart city and Housing For All (HFA), Atal Mission for Rejuvenation and Urban

Transformation (AMRUT) are flag ship programme of the government of India for urban

development. The Government of Chhattisgarh has also notified Apra Special Area under the

provesion of C.G Town and Country Planning Act.-1973, for the purpose of developing Arpa

River Front and constituted ASADA. Under this project several river front slums will be

benefited. We hope these initiatives will mitigate the problems of slum in BMC. Our study is

also a lesson for growing city to manage their urban morphology on right time.

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publishing company, 1998.

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Appendix:-

Table 01: Calculation for Residential Segregation, Especially Dissimilarity Index &

Isolation Index

War

d N

o.

Ward Name

War

d P

op

ula

tio

n

(20

11)

Slu

ms

Po

pula

tion

(20

13)

Ind

ex o

f

Dis

sim

ilar

ity

Iso

lati

on

of

Slu

m

Po

pu

lati

on

Iso

lati

on

of

War

d

Po

pu

lati

on

(1)* (2)* (3)*

1 Vikash Nagar 4839 587 0.0079 0.0007 0.0132

2 Vishnu Nagar 8607 2004 0.0029 0.0044 0.0213

3 Nehru Nagar 6736 1458 0.0036 0.0030 0.0169

4 Kasturba Nagar 8216 509 0.0192 0.0003 0.0236

5 Bhakti Kanwar Ram Nagar 4245 150 0.0112 0.0001 0.0125

6 Tilak Nagar 5363 622 0.0091 0.0008 0.0147

7 Guru Ghansidas Nagar 11890 7276 0.0485 0.0322 0.0225

8 Rajendra Nagar 3099 291 0.0061 0.0003 0.0087

9 Ayappa Nagar 7736 93 0.0226 0.0000 0.0234

10 Mother Teresa Nagar 6021 486 0.0127 0.0004 0.0170

11 Dr. Ambedkar Nagar 5023 550 0.0089 0.0006 0.0138

12 Krantikumar Bhartiya Nagar 9544 5775 0.0381 0.0254 0.0182

13 Rani Avantibar Nagar 9062 1889 0.0057 0.0038 0.0229

14 Vinoba Nagar 9110 0 0.0278 0.0000 0.0278

15 Sanjay Gandhi Nagar 7324 1396 0.0061 0.0026 0.0188

16 Priyadarshani Nagar 3541 828 0.0012 0.0018 0.0088

17 Nirala Nagar 4665 0 0.0143 0.0000 0.0143

18 Azad Nagar 4672 0 0.0143 0.0000 0.0143

19 Saheed Asfak ulla nagar 2232 0 0.0068 0.0000 0.0068

20 Ram Nagar 3024 91 0.0082 0.0000 0.0090

21 Subash Nagar 2553 301 0.0043 0.0004 0.0070

22 Munnulal Shukla 3120 562 0.0030 0.0010 0.0081

23 Lala Lajpat Rai Nagar 2391 118 0.0059 0.0001 0.0070

24 Shivaji Nagar 5526 301 0.0134 0.0002 0.0160

25 Sant Ravidas Nagar 5848 979 0.0065 0.0016 0.0153

26 Nagorao Shesh Nagar 2274 0 0.0070 0.0000 0.0070

27 Krishna Nagar 3651 619 0.0039 0.0010 0.0095

28 Vasantbai Patel Nagar 7552 589 0.0162 0.0005 0.0214

29 Sahid R.P Bismal Nagar 4481 591 0.0068 0.0008 0.0121

30 Gandhi Nagar 3967 693 0.0040 0.0012 0.0103

31 Indira Nagar 3542 325 0.0070 0.0003 0.0099


189


War

d N

o.

Ward Name

War

d P

op

ula

tio

n

(20

11)

Slu

ms

Po

pula

tion

(20

13)

Ind

ex o

f

Dis

sim

ilar

ity

Iso

lati

on

of

Slu

m

Po

pu

lati

on

Iso

lati

on

of

War

d

Po

pu

lati

on

(1)* (2)* (3)*

33 Ramdas Nagar 5906 1052 0.0058 0.0019 0.0153

34 Bhagatsingh Nagar 3327 446 0.0050 0.0006 0.0090

35 Maharana Pratap Nagar 3485 833 0.0009 0.0019 0.0086

36 Vivekananda Nagar 8374 181 0.0235 0.0000 0.0251

37 Shankar Nagar 5270 958 0.0049 0.0017 0.0136

38 Shahid Hemu Colony 9587 938 0.0184 0.0010 0.0267

39 Ganesh Nagar 5148 1886 0.0063 0.0059 0.0115

40 Kamal Nehru Nagar 9732 8675 0.0714 0.0477 0.0157

41 Thakur Dev Nagar 10693 9376 0.0766 0.0511 0.0174

42 Dr.S.P Mukherji Nagar 12769 5403 0.0240 0.0187 0.0274

43 Rani Durgavati Nagar 6245 3235 0.0186 0.0129 0.0126

44 Shahid Mangal Pandey Nagar 10038 6635 0.0467 0.0308 0.0185

45 Arvind Nagar 15173 5568 0.0185 0.0174 0.0339

46 Shastri Nagar 9107 1024 0.0159 0.0012 0.0250

47 Devkinandan Dikshit Nagar 5756 0 0.0176 0.0000 0.0176

48 Ramkrishna Paramhans Nagar 6862 395 0.0164 0.0003 0.0198

49 Bilasa Nagar 2336 0 0.0071 0.0000 0.0071

50 Wireless Colony 3949 374 0.0077 0.0004 0.0110

51 Bharat Mata Nagar 2754 1700 0.0114 0.0076 0.0052

52 Jaganath Nagar 3181 0 0.0097 0.0000 0.0097

53 Bapu Nagar 4208 1165 0.0007 0.0029 0.0101

54 Loko Colony 3944 1582 0.0064 0.0053 0.0086

55 Tripura Sundari Nagar 4503 4542 0.0392 0.0266 0.0069

Total 327163 85784 0.8126 0.3205 0.8218

Source: Census of India-2011 & SFCPoA Bilaspur City-2013

Formula:-

(1)* Dissimilarity Index (ID) = ( W/Wt)-(S/St)

(2)* Isolation Index (Slum Pop) = (S/St) X (S/S+Wt )

(3) * Isolation Index (Ward Pop) = (W/Wt) x (Wt/W+S)

S= Slum population of each ward 2013

St= Total Slum Population 2013

W=Ward Population of each ward 2011

Wt= Total Ward Population 201


190


Table-02: Calculation for Z Score S

L N

o.

Ward No.

(%) of

Govt.

Land

(x)

(%) of

Slum

Population

(Y)

(X- )

𝑍𝑥 𝑍𝑦

𝑍𝑥 . 𝑍𝑦 (X-/σ) (Y-𝑌 ) (Y-𝑌 /σ)

1 Ward - 01 0.47 12.13 -7.4275 -0.8225 -13.5694 -0.5353 0.4403

2 Ward - 02 7.87 23.28 -0.0338 -0.0037 -2.4166 -0.0954 0.0004

3 Ward - 03 1.59 21.64 -6.3133 -0.6991 -4.0551 -0.1600 0.1119

4 Ward - 04 0.85 6.20 -7.0463 -0.7803 -19.5048 -0.7697 0.6006

5 Ward - 05 0.76 3.53 -7.1388 -0.7906 -22.1664 -0.8748 0.6916

6 Ward - 06 1.69 11.60 -6.2059 -0.6873 -14.1020 -0.5565 0.3825

7 Ward - 07 12.08 61.19 4.1844 0.4634 35.4943 1.4007 0.6491

8 Ward - 08 5.34 9.39 -2.5604 -0.2835 -16.3099 -0.6436 0.1825

9 Ward - 09 0.17 1.20 -7.7278 -0.8558 -24.4978 -0.9668 0.8274

10 Ward - 11 1.41 10.95 -6.4856 -0.7182 -14.7504 -0.5821 0.4181

11 Ward - 12 29.62 60.51 21.7184 2.4051 34.8092 1.3737 3.3039

12 Ward - 15 10.66 19.06 2.7617 0.3058 -6.6394 -0.2620 -0.0801

13 Ward - 20 0.58 3.01 -7.3249 -0.8112 -22.6907 -0.8955 0.7264

14 Ward - 21 3.10 11.79 -4.7995 -0.5315 -13.9099 -0.5489 0.2918

15 Ward - 22 4.88 18.01 -3.0248 -0.3350 -7.6872 -0.3034 0.1016

16 Ward - 23 2.78 4.94 -5.1231 -0.5673 -20.7648 -0.8194 0.4649

17 Ward - 25 8.24 16.74 0.3386 0.0375 -8.9592 -0.3536 -0.0133

18 Ward - 27 16.47 16.95 8.5726 0.9493 -8.7457 -0.3451 -0.3277

19 Ward - 28 2.33 7.80 -5.5679 -0.6166 -17.9007 -0.7064 0.4356

20 Ward - 29 1.86 13.19 -6.0427 -0.6692 -12.5110 -0.4937 0.3304

21 Ward - 30 2.68 17.47 -5.2216 -0.5783 -8.2309 -0.3248 0.1878

22 Ward - 33 3.61 17.81 -4.2903 -0.4751 -7.8876 -0.3113 0.1479

23 Ward - 35 2.76 23.90 -5.1385 -0.5691 -1.7976 -0.0709 0.0404

24 Ward - 36 1.04 2.16 -6.8613 -0.7598 -23.5385 -0.9289 0.7058

25 Ward - 37 3.59 18.18 -4.3103 -0.4773 -7.5216 -0.2968 0.1417

26 Ward - 38 2.14 9.78 -5.7619 -0.6381 -15.9159 -0.6281 0.4008

27 Ward - 39 10.16 36.64 2.2637 0.2507 10.9356 0.4316 0.1082

28 Ward - 40 31.35 89.14 23.4549 2.5974 63.4389 2.5035 6.5027

29 Ward - 41 9.67 87.68 1.7651 0.1955 61.9835 2.4461 0.4781

30 Ward - 42 5.86 42.31 -2.0419 -0.2261 16.6134 0.6556 -0.1483

31 Ward - 43 12.25 51.80 4.3471 0.4814 26.1014 1.0300 0.4959

32 Ward - 44 31.03 66.10 23.1300 2.5615 40.4000 1.5943 4.0838

33 Ward - 45 14.42 36.70 6.5186 0.7219 10.9968 0.4340 0.3133

34 Ward - 46 3.65 11.24 -4.2540 -0.4711 -14.4559 -0.5705 0.2688


191


SL

No

.

Ward No.

(%) of

Govt.

Land

(x)

(%) of

Slum

Population

(Y)

(X- )

𝑍𝑥

(Y-𝑌 ) 𝑍𝑦

𝑍𝑥 . 𝑍𝑦

(X-/σ) (Y-𝑌 /σ)

35 Ward - 47 4.33 0.00 -3.5668 -0.3950 -25.7000 -1.0142 0.4006

36 Ward - 48 1.18 5.76 -6.7206 -0.7443 -19.9437 -0.7870 0.5858

37 Ward - 50 2.03 9.47 -5.8743 -0.6505 -16.2292 -0.6405 0.4166

38 Ward - 51 6.69 61.73 -1.2072 -0.1337 36.0284 1.4218 -0.1901

39 Ward - 52 7.09 0.00 -0.8129 -0.0900 -25.7000 -1.0142 0.0913

40 Ward - 53 10.09 27.69 2.1873 0.2422 1.9854 0.0783 0.0190

41 Ward - 54 33.16 40.11 25.2639 2.7978 14.4116 0.5687 1.5912

42 Ward -55 20.64 90.76 12.7370 1.4105 65.0617 2.5675 3.6216

Total ( ∑ ) 332.16 1079.56 0.0398 0.0064 29.8004

Mean () 7.90 25.70 0.0009 0.0002

Standard

Deviation (σ) 9.03 25.34 0.9996 1.0002

Source: SFCPoA Bilaspur City-2013

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