Urban Sprawl and its Transformation Over Land Use / Land Cover ...

Bonfring International Journal of Industrial Engineering and Management Science, Vol. 2, Special Issue 1, July 2012

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Urban Sprawl and its Transformation Over Land Use / Land Cover Using Geo Informatics: A Case Study on Madurai Fringe Area P. Saravanan, S. Padmasri and K. Lakshmi Abstract--- The cities are growing in all directions resulting in urban sprawl and it is governed by geographic and socio-economic factors such as population growth, policy and economic development. Uncontrolled momentum of urban sprawl and land use change raises many issues which might have both positive and negative impacts. This sprawl can be effectively monitored using remotely sensed data from different dates by digital analysis of the imagery using change detection techniques. The present attempt aims to examine the change in demography, landuse /landcover (LU/LC) over a time point and assesses the pattern of sprawl through Geoinformatic technique in the fringe area of Madurai city. The geographical a real extend of Madurai fringe is 120.95 sq.km. It consist of 24 villages out of it 15 villages with 6 urban centers falls in the northern part and 9 including 3 urban centers falls in the southern part and it holds the total population of about 3,02,270 persons (Census, 2001). The spatio-temporal study of LU/LC is carried out for two time points 1997 and 2007. The data source used for analysis is IRS LISS pan merged (NRSC) and Geoeye imageries (Google Earth). The analysis mainly focused the demographic changes along with landuse/ landcover changes. The degree of impact on fringe areas is inferred from the analysis. The trend of sprawl is notably high in the urban centers than in the revenue villages in both the sides of the fringe of Madurai city. While comparatively examining the changes, the northern part shows a slighter increase in percentage of urban sprawl than the southern part. Keywords--- Change Detection, Landuse / Landcover, Urban Fringe, Urban Sprawl, Madurai

I.

by the gradual filling-in of the intervening spaces with similar uses [20]. The cities are expanding in all directions resulting in large-scale urban sprawl and it is governed by geographic and socio-economic factors such as population growth, socioeconomic characters and regulatory systems. They not only produce an inefficient and unpleasant environment on the urban fringe, but adversely affect the inner city and the rural areas as well [1],[6]. The spatial pattern of such sprawl is clearly noticed on the urban fringes, than in the city centre [21]. As cities expand physically, the boundary between urban, suburban and rural activities merge, thereby, presenting opportunities for beneficial linkages [9]. Monitoring urban development is mainly to find the type, amount and the location of land conversion for future planning [16]. Horizontal growth or Urban Sprawl converts vast rural areas into urban land leads to misuse of land with a spate of environmental problems. Urban Fringe area studies and suburban development have been widely carried out by urban geographers to understand various dimensions in the development process. In similar direction the impact of urban sprawl has been studied by taking the ancient city Madurai, one of the million cities and the Third largest city in Tamilnadu. The main focus of the present attempt is to examine the change in demography, landuse /landcover (LU/LC) over a time point and assesses the pattern of sprawl through Geoinformatic technique in the fringe area of Madurai city. The major objectives are: 1.

2.

INTRODUCTION

L

AND use patterns have received renewed attention recently as the popular press and public policy debates focuses on the issue of urban and sub-urban sprawl. The term urban sprawl is referred as the growth of metropolitan area through the process of scattered development of miscellaneous types of land use in isolated locations on the fringe, followed

3.

To assess the status of Landuse / Landcover between two time points 1997 and 2007 for the fringe villages of Madurai. Identify the spatial variation in demography and to study the intensity of land use changes in the fringe villages into settlement and decline in area under agricultural and water bodies. Delimiting the degree of urban influence on fringe villages and to explore the direction and pattern of development. II.

P. Saravanan, Research Scholar, School of Earth and Sciences, Madurai Kamaraj University, Madurai, mail:[email protected] S. Padmasri, Junior Research Fellow, School of Earth and Sciences, Madurai Kamaraj University, Madurai, mail:[email protected] Dr.K. Lakshmi, Professor (Retd), School of Earth and Sciences, Madurai Kamaraj University, Madurai, mail:lakshmigeog@rediffmail.

Atmospheric India. EAtmospheric India, EAtmospheric India, E-

OVERVIEW OF THE STUDY AREA

Madurai is one of the million cities and the third largest city in Tamilnadu. During the last four decades, its population has grown from 0.36 million to 1.02. It is strategically located in Southern Tamilnadu at a distance of approximately 500 Kms from Chennai and is well connected by means of road, rail and air ways with the major cities of the country. The geographical area of the fringe is 120.95 Sq.Kms. The city and

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its adjacent areas are diagonally bisected into two halves as north and south by river Vaigai. Madurai fringe area consist of 24 villages, out of it 15 villages with 6 urban centers falls in the northern part and 9 including 3 urban centers falls in the southern part and it holds the total population of about 3,02,270 persons [22]. Generally, the development of Madurai is mainly due to transportation facility and the city and its fringe are well served by road transport which is one of the key factors for the development of the region. Here, there are three national highways and two important state highways runs through the study area namely NH 7 (Varanasi - Kanniyakumari), NH 45B (Trichy – Tuticorin), NH 49 (Bodi – Rameshwaram) and SH 33 (Madurai - Thondi), SH 72 (Madurai - Natham).

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found that the pattern of expansion is linear along major roads in all direction and it can be explained with the help of definition that the urbanization takes place either in radial direction around a well-established city or linearly along the highways [12],[18]. This dispersed development along highways, or surrounding the city and in rural countryside is often referred as sprawl. As discussed earlier the development of Madurai fringe area is mainly due to road transportation and it can be witnessed from Figure: 2 that the settlement of the Madurai fringe area is typically placed close to the national highway and state highway and exhibits a linear pattern of growth. Subsequently, the well fertile agricultural lands which are located along the road side were transformed into builtup landuse. Here, urban expansion is studied between 1997 and 2007 with the help of remote sensing data and the Figure: 2 clearly depict the expanded area. The yellow color represents urban area in 1997 and green in 2007. In 1997 the percentage of urban area to the total is 15.28% and in 2007 the urban area gets increased to 24.91% with a hike of about 9.63%. While considering the urban population, it is found that in 1991 it was 1,82,063 persons and in 2001 it has been increased to 2,79,357 with the growth of 4.58%.

Figure 1: Geographical Location of Madurai Fringe Area For the present investigation, the data source used to study the demography characteristics is obtained from Primary Census Abstract [22] and the spatio-temporal study of LU/LC is carried out using IRS LISS + Pan merged (NRSC) and Geoeye imageries (GoogleEarth). III.

RESULT AND DISCUSSION

Uncontrolled momentum of urban sprawl and land use change raises many issues which might have both positive and negative impacts. The measurement and monitoring of these changes are crucial and it is difficult to understand its dynamics over different time scales. This sprawl can be effectively monitored using remotely sensed data (in combination with ground survey) from different dates by digital analysis of the imagery using change detection techniques[4],[5],[14]. A. Urban Expansion There are various factors that induce the process of urban expansion, out of which the rural to urban migration has been found as a key source of urban growth since the origin of cities. Varied factors such as perceived economic opportunity, resettlement, insecurity in the countryside, and excitement of city life drive rural-to-urban migration [3],[15]. The migration rate varies over time and space and, in the developed world, may be balanced by reverse migration. Considering the urban expansion of Madurai environ, it is

Figure 2: Urban Expansion in Madurai Fringe Area

Table 1: Change in Urban Area and Urban Population Years 1997

Urban Area 5480.32

Urban Areain % 15.28

2007 Change

8933.54 3453.22

Years

Urban population

1991

182063

24.91 9.63 Urban population in % 57.28494

2001 Change

279357 97294

61.86144 4.576502

B. Spatial Variation in Demographic Parameters Spatial variations in demographic parameters are effectively analyzed with the help of census of India report 1991 and 2001. The total administrative units considered to

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perform this analysis include 15 revenue villages, 5 town panchayats and 4 census towns. The demographic parameters considered for present analysis are total population, households, population density, total urban population and total workers which includes primary, secondary and tertiary respectively. To clearly emphasis the pattern and trend of urban growth the study area has been divided into north and south. Among 24 administrative units, the northern fringe has 15 which include 6 urban centers and southern fringe contains 9 with 3 urban centers. The demographic change is studied for two time points for two sides of the fringe area viz north and south. Table: 2 shows the actual values in 1991, 2001 and change between them.

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parameters is because the north fringe has 6 urban centers were as the southern fringe has only 3. Since, all the demographic parameters discussed shows a tremendous increase between the regions, it is inferred that both the fringe area have undergone an effective urban expansion. As a result the agriculture lands have been converted to builtup landuse which eventually affects the distribution of workers. Due to this particular urban expansion, the primary and secondary workers engaged in agricultural and other allied activities are force to change their nature of work. So, it is obvious from the table that the number of primary and secondary workers has been reduced in both the fringe areas and the number of tertiary workers has been considerably increased.

While comparing the change in total population between C. Change in Landuse and Landcover the regions, it is noted that the northern side has an increase of Change detection is the process of identifying differences 64,973 persons and the southern side of 25,557 with a total in the state of an object or phenomenon by observing it at increase in population of about 1, 01,848 between 1991 and different times [14]. Change detection is an important process 2001. Meanwhile, the population density shows a drastic in monitoring and managing natural resources and urban change of 206 persons per hectare in north and 19 persons per development because it provides quantitative analysis of the hectare in south respectively. Similarly, the total households spatial distribution of the population and other environmental also shows a notable increase of 27,017 and it is identified that related activities [7]-[11]. In the present investigation the the change in households in northern fringe has comparatively landuse/Landcover change detection is carried out for two increased more than twice that of southern fringe. The total different time points. The landuse / Landcover classification urban population has been increased to 90,530 persons adopted for the study is restricted to level one of classification between the years but when considering the change between schema. either sides of the fringe, it is again the northern side showing Landuse / Landcover change for the selected two time a positive trend in change holding an urban population of about 75,553 persons while south with 26,295 persons which point shows notable variation in the development of land is nearly three times lesser than north. The reason for the under settlements related uses in the expense of good wet incredible change in urban population and other demographic lands in the northern and southern fringe. Table 2: Demographic Details of Madurai Fringe Area 1991 N

1991 S

2001 N

2001 S

Change N

Change S

Total

Number of Villages

15

9

15

9

-

-

24

Area in Hec

6242.49

5852.01

6242.49

5852.01

-

-

12095

No. of Urban Centers

6 (3TP+3CT)

3 (2TP+CT)

6 (3TP+3CT)

3 (2TP+CT)

-

-

9

Households

20073

22164

39161

30093

19088

7929

27017

Total Population

91996

101372

167549

127667

75553

26295

101848

Pop Den

250

156

456

175

206

19

226

Urban Population

77840

75119

142813

100676

64973

25557

90530

% of Urban Population

84.612

74.102

85.237

78.858

0.624

4.756

5.38

Total Workers

25943

27311

61259

47507

35316

20196

55512

Primary workers

10259

10735

4966

4304

-5293

-6431

-11724

Secondary workers

7626

10794

3746

2765

-3880

-8029

-11909

Tertiary workers

14569

15124

48063

36631

33494

21507

55001

While comparing the changes in landuse / Landcover between both the fringes, the northern fringe shows notably high change than the southern fringe and it is mainly due to major roads closely constructed in the north. The National highways NH 7, NH45B and state highway SH 72, SH 33 and major district road connecting Alanganallur and Alagarkoil falls parallel to each other in the northern fringe. So, the increased in settlement landuse in the northern fringe (6.73sq.km) are comparatively more than the southern fringe (6.05sq.km). Similarly, the amount of decrease in the agricultural land in the northern fringe (10.49%) is higher than

the southern fringe (8.90%) and most of the agricultural lands are developed as settlements whereas the changes in the plantation is higher in the southern fringe (0.09%). Considering water bodies, a part of the Villapuram tank area is converted into settlements for the construction of housing board colonies by the government itself in the southern fringe and hence the decreasing trend in water bodies is found to be high in the southern fringe (-0.79%) of the study area. A portion of outcrop is clearly seen in both the fringes and they have not undergone any changes. The amounts of change in the land use land cover for two times point are illustrated in

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Table: 3.

Figure 3: Land Use / Land Cover Change Detection Table 3: Details of Land Use / Land Cover Change Between Two Time Points Northern Fringe Landuse Settlements Agriculture Plantation Water Bodies Outcrop Total Landuse Settlements Agriculture Plantation Water Bodies Outcrop Total

1997

2007

8.86 15.59 (14.2) (25.0) 41.57 35.02 (66.6) (56.1) 1.51 1.47 (2.4) (2.4) 10.27 10.13 (16.5) (16.2) 0.21 0.21 (0.3) (0.3) 62.42 62.42 Southern Fringe 1997

2007

4.44 (7.59) 44.06 (75.29) 0.39 (0.67) 8.68 (14.83) 0.95 (1.62) 58.52

10.49 (17.93) 38.85 (66.39) 0.34 (0.58) 7.89 (13.48) 0.95 (1.62) 58.52

Change in Sq.Km 6.73 (10.78) -6.55 (-10.49) -0.04 (-0.06) -0.14 (-0.22) 0 (0.00) Change in Sq.Km 6.05 (10.34) -5.21 (-8.90) -0.05 (-0.09) -0.79 (-1.35) 0 (0.00) -

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high, High, Medium, and Low. The villages Avaniyapuram (244.80hec), Thirupalai (219.51hec) and Anupanadi (121.14 hec) ranks first in development of builtup lands and falls in very high category while the villages Thiruparankundram (102.57 hec) Anaiyur (99.52hec), Vandiyur (80.92hec) holds second rank. Similarly, the villages Kannanendal (75.19hec), Villacheri (60.59hec) Paravai (51.51hec), Tattaneri (42.31hec) comes under medium category and others villages like Airavathanallur (17.93hec), Vadivelkarai (20.58hec), Sambakkudi(3.45hec) Erkudi(0.18hec), Achambattu (3.86hec), Vilangudi (17.24hec), Allatur(5.08hec), Kadaikenaru (7.12hec), Narasingam (19.30hec), Mangalakudi (3.05hec), Uttangudi (26.54hec), Melamadai (22.93hec), Managiri (3.15 hec) falls under low intensity of change in settlement class. Further, the Kannikudi village has no change in the settlement landuse since it has been marked as uninhabited village by census department. ii.

Agricultural Land Use

This landuse is considered as a key contributor for the development of settlement and other related activities. Based on their level of change they are classified into High, Medium, and Low. Nearly five villages rank first in devoting agricultural land for other development activities and out of that four are urban centers viz., Anupanadi (-115.54 hec), Avaniyapuram (-168.78), Thiruparankundram (-100.16hec), Anaiyur (-99.52hec) and one revenue village Thirupalai (212.09hec). Next, the medium level of changes are notice in the villages like Villacheri (-51.30hec), Paravai (-55.13hec), Tattaneri (-40.66hec), Kannanendal (-70.84hec) and Vandiyur (-79.80hec) and other villages like Airavathanallur (-17.18 hec), Vadivelkarai (-20.25hec), Sambakkudi (-3.45hec), Erkudi (-0.18hec), Achambattu (-3.83hec), Vilankudi (17.24hec), Allatur (-5.08hec), Kadaikenaru (-5.83hec), Narasingam (-19.02hec), Mangalakudi (-3.05hec), Uttangudi (-26.31hec), Melamadai (-22.28hec), Managiri (-2.57hec) are holding the last rank and falls in the low intensity of change category and again there is no change in Kannikudi village.

*percentage values are shown within parenthesis D. Intensity of change in Landuse / Landcover classes The intensity of change is calculated by analysis village wise landuse / Landcover change and sorting those obtain values hierarchically and classifying it as low, medium and high for every landuse classes. Here, for the present study three major classes viz., settlements, agricultural land and water bodies which show a considerable change are taken into account to analysis the intensity of change. i.

Settlements

According to the values obtained for settlement landuse and based on their level of change they are classified into Very

Figure 4: Intensity of Change in Settlement and Agricultural Land Use iii.

Water Bodies

Similar to the above discussed landuse classes, the water body class is also categorized into three low, medium and high. Here, no village is found under high degree of change

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category and only one village namely Avaniyapuram (76.02hec) falls in medium intensity of change category and that too because of construction of housing board colony within Villapuram tank area by the government. While remaining villages possess only a minimal change and comes under low intensity class. Further, the villages like Sambakkudi, Erkudi, Achambattu, Vilangudi, Tattaneri, Allatur, Kannikudi and Mangalakudi do not have any change. IV.

INFERENCES

Thus, the present investigation on urban expansion of Madurai fringe area is effectively analyzed with the help of multi-temporal remote sensing images and Geoinformatic techniques. Various analysts have made considerable progress in quantifying the urban sprawl and its pattern [1], [9], [14], [15], [18], [21]. However all these studies have come up with different methodologies in quantifying urban sprawl. The present study inferred, 1.

The pattern of urban sprawl of Madurai is identified as linear along major roads especially on State Highway SH 72 and National Highways NH 45B, NH 7. 2. Comparing the urban area expansion between the years, it is found that in 1997 the percentage of urban area to the total is 15.28% and in 2007 the urban area gets increased to 24.91% with a hike of about 9.63%. Likewise the total urban population has been increased to 90,530 persons between the years. 3. Comparing the changes in Landuse / Landcover between the fringes, the northern fringe (10.78%) shows notably high change than the southern fringe (10.34%). 4. The degree of intensity in landuse change for various landuse classes is found to be high in three villages namely Avaniyapuram, Thirupalai and Anuppanadi. The urban sprawl is one of the potential threats to sustainable development where urban planning with effective resource utilization and allocation of infrastructure initiatives are key concerns. Thus identification and analysis of the patterns of sprawl would help in effective landuse planning in urban area. It is important to study and understand the trend of urban sprawls, which ultimately focus for urban landscape planning and environmental management. ACKNOWLEDGMENT The authors are grateful to the UGC –UPE scheme for extending financial assistance to carry out this work and also express a sincere thanks to Prof.G.R.Parthasarathy (Project Coordinator) UGC-UPE Project No-6, Mapping and Managing Natural Resources and Environment, Prof.P.Ilangovan and Prof.N.Krishnan, School of Earth and Atmospheric Sciences, Madurai Kamaraj University, Madurai for their help and encouragement. REFERENCES [1]

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180, 1990. J. Epstein, K. Payne and E. Kramer, “Techniques for mapping suburban sprawl”, Photogrammetric Engineering and Remote Sensing, vol. 63, no 9, Pp. 913–918, 2002. [4] Q. Fang, K.L. Woller, and R. Briggs, “Modeling Urban Population Growth from Remotely Sensed Imagery and TIGER GIS Road Data”, Photogrammetric Engineering & Remote Sensing, vol. 69, no. 9, Pp.1031–1042, 2003. [5] P.M. Harris and S.J. Ventura, “The integration of geographic data with remotely sensed imagery to improve classification in an urban area”, Photogrammetric Engineering and Remote Sensing, Vol. 61, Pp. 993– 998, 1995. [6] B.S. Hoyle, “Geographical readings transport and development”, The Macmillan Press Ltd, London, 1973. [7] J. Huang, L. Jie and Z. Tu, “Detecting spatiotemporal change of land use and landscape pattern in a coastal gulf region, southeast of China”, Journal of Environment, Development and Sustainability, Vol. 23, Pp. 93-112, 2008. [8] J.R. Jensen, and D. L. Toll, “Detecting residential landuse development at the urban fringe”, Photogrammetric Engineering and Remote Sensing, Vol. 48, No. 4, Pp. 629-643, 1982. [9] R. Kaur, “Urban-rural relation: A geographical analysis”, Anmol Publication Pvt. Ltd., India, 1995. [10] J.Y. Liu, D. F. Zhuang, D. Luo and X. Xiao, “Land-cover classification of China: integrated analysis of AVHRR imagery and geophysical data”, International Journal of Remote Sensing, Vol. 24, No. 2, Pp. 485–500, 2003. [11] Lopeza, G. Boccoa, M. Mendozaa, E. Duhaub, “Predicting land-cover and land-use change in the urban fringe A case in Morelia city Mexico”, Landscape and Urban Planning, Vol. 55, Pp. 271–285, 2001. [12] P. Saravanan and P. Ilangovan, “Identification of Urban Sprawl Pattern for Madurai Region using GIS”, International Journal of Geomatics and Geosciences, vol. 1, pp 41-49, 2010. [13] M.S. Sarvestani, L. Ibrahim, P. Kanaroglou, “Three decades of urban growth in the city of Shiraz, Iran: A remote sensing and geographic information systems application”, Journal of Cities, Vol.28, Pp 320–329, 2011. [14] A. Singh, “Digital change detection techniques using remotely sensed data”, International Journal of Remote Sensing, Vol. 10, No. 6, Pp. 9891003, 1989. [15] H.S. Sudhira, T.V. Ramachandra and K.S. Jagadish, “Urban sprawl: metrics, dynamics and modelling using GIS”, International Journal of Applied Earth Observation and Geoinformation, vol. 5, pp 29–39, 2004. [16] S. Sulochana, “Colonial urban development in India-A conceptual clarification”, Transactions of the Institute of Indian Geographers, vol. 23, No.1, Pp. 29 – 38, 2001. [17] M. G. Tewolde and P. Cabral, “Urban Sprawl Analysis and Modeling in Asmara, Eritrea”, Journal of Remote Sensing, Vol. 3, Pp. 2148-2165, 2011. [18] D. M. Theobald, “Land use dynamics beyond the American urban fringe”, Geographical Review, vol.91, pp. 544–564, 2001. [19] Q. Weng, “A remote sensing–GIS evaluation of urban expansion and its impact on surface temperature in the Zhujiang Delta, China”, International Journal of Remote Sensing, Vol. 22, Pp. 1999–2014, 2002. [20] W. H. Whyte, “City: rediscovering the center”, New York: Doubleday, 1988. [21] J. Xiao, “Evaluating urban expansion and land use change in Shijiazhuang, China by using GIS and remote sensing”, Landscape and Urban Planning, Vol.75, Pp. 69–80, 2006 [22] Census of India Report 1991 and 2001 P.Saravanan is currently pursuing Ph.D in the field of Geoinformatics at Madurai Kamaraj University, Madurai, India. He has completed his post graduation in Environmental Remote Sensing and Geo-information Technology from the same institution and his under graduation was Applied Sciences from Thiagarajar College of Engineering, Madurai. He has worked as a project associate in Public Works Department (PWD), spatial engineer in Empower consultancy Pvt. Ltd and has seven years of experience with five years of research experience. He also worked as junior and senior research fellow in UGC –UPE funded project at Madurai Kamaraj University. He has published eleven articles with special reference to urban and transportation studies using Geoinformatics. [3]

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