A GEOSTATISTICAL ANALYSIS OF UTILITY SERVICES IN MADURAI REGION USING GIS

Dr.R.S.Suja Rose, Ms.M. Lakshmi, Ms.M. Shabira Begum,

and Dr.N.Krishnan,

Department of Environmental Remote Sensing and Cartography

Madurai Kamaraj University,

Madurai – 625 021.

Tamil Nadu, India.

INTRODUCTION• The major challenges faced by a developing country is to provide

the sufficient infrastructure facilities to the growing population

• complicated problems can be easily solved by GeographicInformation System

• It is efficient in

– managing a large spatial and non spatial database,

– integrate information,

– visualize the nature,

– present the powerful ideas and

– to develop effective solution.

• to examine the distribution of the existing utilityservice facilities such as Education, Health andTransport.

• to determine the existing relationship among theutility service variables and

• to analyse the spatial pattern of service variablesusing GIS in order to bring out the spatialdisparity.

AIMS AND OBJECTIVES

STUDY AREA

The total geographic area is 12,644 sqkm.

Graticules of 77º 07' E to 78º 30' E longitudes and 9º 30' N to 10º 52' N latitudes.

1053 villages and 82 towns in 35 blocks of 19 taluks.

The total population : 55,95,165 persons

Males : 28,24,486 persons

Females : 27,70,679 persons

METHODOLOGY & DATABASE• Census of India Maps digitized using ArcGIS version 9.2 software

• Population, Education, Health and Transport facilities located at block level hasbeen collected from the Census of India Publications, 2001 and are attributed tothe block polygons

• education related service variables

– Primary school, Middle school, Secondary school,

– Higher Secondary and Colleges

• health facility service variables including

– Allopathy, Homeopathy, Ayurvedic, Unani and Nursing Home

– Maternity and Child Health, Primary Health Centre and Medical Practioners

• transport facilities

– the length of National Highways, State highways, Metalled roads and Railwaysthe network indices like the number of nodes, edges and road density

• Correlation, Factor analysis and Regression Model

RESULTS AND DISCUSSION

Relation between the Population and Utility Service VariablesPopulation Characteristics/

Utility Services

Total population SC Population ST Population Population

0-6 age group

Literates

Primary School 0.10 .376(*) 0.16 0.06 0.03

Middle 0.10 .412(*) 0.16 0.19 0.17

Secondary 0.15 .342(*) 0.16 0.20 0.19

Higher Secondary 0.17 0.24 0.29 0.20 0.20

College .511(**) .395(*) 0.26 .570(**) .547(**)

Allopathic 0.12 0.04 0.02 0.27 0.27

Ayurvedic 0.08 0.22 0.19 0.05 0.04

Unani 0.28 -0.03 0.04 0.26 0.25

Homeopathic -0.01 0.01 -0.04 0.10 0.11

Maternity & Child Welfare-0.05 .386(*) 0.10 -0.18 -0.17

Health Centre 0.09 .568(**) 0.19 0.04 0.03

Primary Health 0.04 0.32 0.21 0.01 0.01

Primary Health Subcenter0.15 0.15 -0.29 0.08 0.08

Nursing Home 0.27 .538(**) 0.13 0.24 0.23

Registered Private Medical

Practitioner 0.00 .497(**) 0.27 0.07 0.03

Subsidised Medical Practitioner0.05 .557(**) .429(*) 0.03 0.00

National Highway .948(**) 0.00 -0.08 .947(**) .964(**)

State Highway .919(**) 0.05 -0.03 .900(**) .912(**)

Major Roads .911(**) -0.03 -0.01 .908(**) .927(**)

Railway line .949(**) 0.05 -0.05 .932(**) .952(**)

Road Density .935(**) -0.01 -0.07 .931(**) .949(**)

Nodes .397(*) 0.20 0.27 .501(**) .471(**)

Edges .404(*) 0.30 0.28 .498(**) .473(**)

• the higher level education is significantly related to the population variables.

• The SC population has significant positive coefficient to the educational utilityservices at 0.05 level, since these rural folks are served by the governmentinstitutions.

• Likewise those populations are also served by the rural health care services.

• The Maternity and child welfare variable shows negative relation with Total,0-6 age group and literate population in contrast to the SC/ST population.

• All the 7 variables of transport utility service shows high relation because theblocks are well connected by road and railway facilities.

• The SC/ST population shows insignificant relation due to the fact that they aredominated over the hilly and foot hill zones where the transport facility ismeager.

Correlation - Inferences

Population and Utility Service Variables – An Eight Factor Solution

Table 2 Population and Utility Services - Component Matrix of the eight factor solution

Population/Utility

Services

Component

1 2 3 4 5 6 7 8

AREA -0.131 0.23 0.23 - 0.082 -0.622 0.14 0.468 0.222

Total Population0.947 -0.201 0.135 -0.138 0.034 -0.102 0.005 0.0004

SC Population 0.245 0.612 0.331 -0.04 0.167 -0.459 -0.125 0.137

ST Population 0.09 0.449 0.17 -0.166 -0.553 0.186 -0.06 0.31

0-6 Population 0.974 -0.163 -0.01 -0.05 -0.02 -0.02 -0.02 0.009

Literate 0.973 -0.198 -0.02 -0.05 -0.01 -0.03 -0.009 -0.01

Primary School 0.166 0.546 0.383 -0.218 0.463 0.364 0.178 0.03

Middle 0.32 0.735 -0.434 0.07 0.247 -0.04 0.168 0.152

Secondary 0.282 0.594 -0.434 -0.295 0.213 -0.03 0.06 -0.02

Higher Secondary 0.297 0.607 -0.393 -0.344 -0.006 0.08 0.103 -0.28

College 0.648 0.497 -0.188 -0.003 -0.136 -0.168 -0.003 -0.05

Allopathic 0.353 0.36 -0.466 0.452 -0.04 0.188 -0.134 -0.367

Ayurvedic 0.06 0.127 0.259 -0.06 0.24 0.321 -0.457 0.425

Unani 0.276 0.02 0.313 -0.266 0.276 0.669 0.04 -0.297

Homeopathic 0.165 0.121 -0.483 0.603 0.07 0.106 0.13 -0.06

Maternity & Child

Welfare -0.06 0.336 0.657 0.175 0.1 -0.193 0.387 -0.144

Health Centre 0.149 0.599 0.562 0.114 0.02 -0.121 -0.211 -0.272

Primary Health 0.114 0.476 0.395 0.309 -0.129 0.06 0.446 -0.141

Primary Health

Subcenter 0.05 -0.254 0.219 0.316 0.591 -0.224 0.253 0.293

Nursing Home 0.278 0.45 -0.204 -0.557 0.03 -0.457 0.09 -0.01

Registered Private

Medical Practitioner0.171 0.648 0.121 0.431 -0.111 -0.131 -0.317 0.154

Subsidised Medical

Practitioner0.136 0.584 0.458 0.05 -0.165 -0.01 -0.407 -0.27

National Highway 0.915 -0.375 0.06 0.03 -0.02 -0.02 -0.003 -0.03

State Highway 0.871 -0.386 0.209 0.003 -0.04 0.02 0.01 0.005

Major Roads 0.875 -0.419 0.09 0.05 -0.121 0.02 0.05 -0.02

Railway line 0.904 -0.367 0.116 0.01 -0.03 -0.09 0.005 -0.01

Road Density 0.895 -0.421 0.08 -0.02 -0.04 -0.02 -0.003 -0.03

Nodes 0.605 0.425 -0.158 0.134 0.01 0.273 0.03 0.355

Edges 0.617 0.483 -0.17 0.116 -0.05 0.171 0.05 0.257

Extraction Method: Principal Component Analysis.

8 components extracted.

Population and Utility Service Variables – An Eight Factor Solution

Component Description Initial Eigen Value Percentage of

Variance

I Total Population and Transport 8.7 30.08

II SC/ST Population Educational and Rural Health 5.6 19.39

III Maternity, Child Welfare and Health Centre 2.9 9.95

IV Homeopathy Health Centre 1.7 5.9

V Primary Health Sub-Centre 1.6 5.7

VI Unani Health centre 1.5 5.1

VII Block Area 1.3 4.5

VIII Ayurvedic Health Centre 1.2 4

Population and Utility Service Variables – The Spatial PatternTable 4 . Location Based Service Dimensions - Factor Loading Matrix of the eight factor Solution and

Regression Residuals

BLOCKComponents

I II III IV V VI VII VIII

Alanganallur -0.21 -0.37 -0.69 -0.68 -0.25 -0.80 0.14 0.28

Chellampatti -0.28 -0.51 -0.23 -0.51 -0.98 0.01 0.62 -1.11

Kallikudi -0.29 -0.59 -0.41 -0.90 -1.15 -0.45 -0.92 0.03

Kottampatti -0.19 -0.65 -0.47 -0.50 0.10 -0.06 0.20 -0.53

Madurai East -0.05 -0.14 -0.56 -0.87 -1.10 0.53 -0.16 1.72

Madurai West 5.68 -0.45 -0.29 0.21 -0.20 0.04 0.03 -0.01

Melur -0.18 0.23 0.47 -0.31 0.43 4.41 -0.72 1.40

Sedapatti -0.25 -0.41 -0.40 -0.48 0.71 -0.26 0.03 -0.20

T.Kallupatti -0.24 0.00 -0.66 -0.60 -0.87 -0.60 -0.07 -0.53

Thirumangalam 0.00 -0.12 -0.29 0.09 -0.90 2.14 -0.71 -1.05

Thiruparangundram 0.04 2.28 -0.09 0.56 -0.04 0.61 0.51 1.22

Usilampatti -0.10 -0.41 -0.75 -0.21 -0.69 -0.46 -0.58 -0.68

Vadipatti -0.16 0.38 -0.61 -0.89 -0.88 -0.61 -0.31 -0.83

Andipatti -0.31 0.45 0.62 -0.72 -0.80 -0.45 3.14 1.30

Bodinayakanur -0.24 -0.18 -1.14 1.49 1.06 -0.38 -0.03 1.91

Chinnamanur -0.42 0.58 -0.52 0.74 -0.22 0.38 0.62 0.55

Cumbam -0.41 0.45 -0.88 0.93 -0.70 0.44 -2.01 -0.82

Myaladumparai -0.16 -1.07 -0.39 -0.61 0.55 -0.93 -1.07 0.44

Periakulam -0.11 0.54 0.40 3.07 0.67 -1.06 0.20 0.57

Theni -0.24 0.50 -0.47 3.10 -1.00 -0.04 1.17 -1.47

Uthamapalayam -0.33 -0.10 -0.69 0.86 -0.80 -0.41 -1.32 -0.06

Attur -0.25 0.27 -0.09 -0.17 -0.65 0.04 0.26 0.15

Dindigul 0.34 4.47 -0.17 -1.69 0.32 -0.69 -0.03 -0.85

Guziliamparai -0.22 -0.89 0.32 -0.48 0.39 0.08 0.33 -1.34

Kodaikanal -0.15 0.41 -1.06 -0.45 4.12 -0.22 -1.08 -0.83

Natham 0.02 -0.63 0.02 -0.20 1.30 -0.08 1.32 -0.16

Nilakkottai 0.08 -0.39 1.22 -0.52 0.67 -0.88 -0.19 2.13

Oddanchatram -0.12 -0.47 1.07 0.42 1.07 1.30 1.15 -1.64

Palani 0.05 0.48 4.57 0.28 -0.33 -0.89 -2.00 -0.17

Reddiyyarchatram -0.15 -0.88 0.95 0.17 0.88 0.19 1.03 -0.98

Shanarpatti -0.16 -0.46 0.51 -0.52 -0.02 -0.39 0.83 -0.23

Thoppampatti -0.27 -0.57 0.01 -0.61 0.13 0.18 0.86 0.73

Vadamadurai -0.10 -0.76 -0.10 -0.46 0.00 -0.51 -0.38 0.39

Vattalakundu -0.34 -0.55 -0.26 0.69 -0.30 -0.49 -1.13 1.33

Vedasandur -0.26 -0.43 1.05 -0.23 -0.52 0.33 0.23 -0.66

Population and Utility Service Variables – The Spatial Pattern of four Primary Factors

Population and Utility Service Variables – The Spatial Pattern

• The first factor namely the Total population and transport dimension has its higher factorloading at Madurai West and Dindigul Blocks, since these are the district headquarters.Very low scores are seen in the blocks of Theni and Dindigul District

• The second factor namely the SC/ST population, Educational and Rural Health dimensionhas its higher scores in Periakulam and Chinnamanur blocks of Theni district and its lowerscores at the blocks dominated by reserve forest area of the present study area

• The Maternity, Child welfare and Health centre dimension has its higher scores at Palaniblock whereas its lower scores are loaded at the blocks in the hilly reserve forested area

• It is quite interesting to note that the fourth factor namely the Homeopathy Health caredimension has higher scores in the three blocks of Theni District namely Periakulam, Theniand Bodinayakanur

Factor Analysis - Inferences

• At the same time the fifth factor namely the Primary Health Sub-centre dimension has itshigher scores at all the rural blocks throughout the study area.

• The sixth factor namely Unani health centre dimension has its higher scores inThirumangalam, Thirupparangundram, Madurai East and West blocks of Madurai Districtand Oddanchatram block of Dindigul district .

• The seventh factor has its higher scores in the two blocks of Madurai District, 3 blocks inTheni District and 5 Blocks in Dindigul District. Lower Scores are mostly confined to theblocks dominated with reserve forests.

• Similarly the eighth factor namely Ayurvedic Health Centre has its higher scores in thesame blocks of Madurai District and few other foot hill blocks like Chinnamanur,Periakulam, Bodinayakanur, Andipatti, Vattalakudu and Nilakottai.

Factor Analysis - Inferences

The correlation coefficient (R) between the dependent and independent variable is 0.99 and the coefficient of determination (R2) is 0.972 which means the independent variables explains 98% of the dependent variable.

• The resultant regression equation is

Population= 151443.77 + 169975.31 x Population and Transport dimension + 33995.24 x SC/ST population, Educational and Rural Health dimension + 13394.52 x Maternity, Child Welfare and Health care dimension ± 5267.83

Population and Utility Service Variables - Regression Models and the

Spatial Pattern

SL.NoBLOCK TOTAL POPULATION REGRESSION RESIDUALS

1 Alanganallur 101,637 8251.21

2 Chellampatti 86,680 3356.23

3 Kallikudi 68,263 -7985.53

4 Kottampatti 98,022 7782.51

5 Madurai East 193,613 63527.09

6 Madurai West 1,093,103 -4769.86

7 Melur 153,897 19407.79

8 Sedapatti 110,624 21146.92

9 T.Kallupatti 89,374 -12311.17

10 Thirumangalam 206,554 63563.14

11 Thiruparangundram 303,125 67886.86

12 Usilampatti 123,786 13444.25

13 Vadipatti 115,545 -12762.35

14 Andipatti 161,224 39462.56

15 Bodinayakanur 67,424 -22826.91

16 Chinnamanur 74,266 -17896.93

17 Cumbam 22,229 -64046.07

18 Myaladumparai 67,863 -13901.9

19 Periakulam 87,634 -68539.86

20 Theni 96,417 -25483.64

21 Uthamapalayam 50,688 -32181.06

22 Attur 131,876 15407.18

23 Dindigul 348,136 -10890.56

24 Guziliamparai 86,149 -1859.1

25 Kodaikanal 100,645 -24470.98

26 Natham 125,198 -9234.49

27 Nilakkottai 149,174 -19433.96

28 Oddanchatram 127,772 -1976.76

29 Palani 222,062 -15516.18

30 Reddiyyarchatram 113,887 5617.87

31 Shanarpatti 121,297 5412.57

32 Thoppampatti 113,747 27728.33

33 Vadamadurai 98,559 -8089.44

34 Vattalakundu 86,592 15227.6

35 Vedasandur 103,470 -3045.35

Population and Utility Service Variables – Regression Analysis

Population and Utility Service Variables - Regression Model and

the Spatial Pattern

• Under-served Blocks - 4 Blocks of Madurai District , 7 Blocks of Theni district and 9 blocks of Dindigul District

• Moderately served Blocks - 6 Blocks of Madurai District, 1 block of Theni District and 5 blocks of Dindigul district

• Well served blocks – Madurai East, Thirumangalam and Thirupparangundram of Madurai District

Inference

CONCLUSION• The relation between selected services to the population has been revealed

scientifically and systematically using the geo-statistical techniques.

• study has clearly brought out the spatial disparities in the distribution of utility service facilities in Madurai region.

• the educational and health facilities are not adequate with respect to the existing population.

• The transport facilities are sufficient for the population.

• Using the recent geomatics techniques, reliable and accurate data can be acquired and systematic analysis can be made in future.

• facilitates in the integration of these results with many other variables so that a planner can execute their decisions in a proper way.

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