ijrar.orgijrar.org/papers/IJRAR_225217.docx  · Web viewImmigration from Bangladesh to Barasat was the main factor of urbanisation since 1971. Rural-urban migrations have being happened

Monitoring Land Use- Land Cover Change and Urban Sprawl: A Case Study of Barasat Town in North 24 Parganas District, West Bengal

MADHUSUDAN PRAMANICK

Assistant Professor, Department of Geography, Prabhu Jagatbandhu College, Howrah

e-mail: [email protected], mobile no.- 9433402382 & 8336057947

Abstract

The uncontrolled spread of urban growth in peripheral region is the burning and challenging issue in urban area of developing country like India. In the present study, an attempt has been made to investigate the effect of land use and land cover (LULC) change on urban sprawl in the years of 1990, 2000, 2010 and 2020 in Barasat town, North 24 Parhanas District. Rapid growth of urban expansion is the causes of LULC change in this region. The maximum likelihood algorithm of supervised classification was used to show the changing pattern of LULC as well as urban sprawl by applying Remote Sensing and GIS techniques in Arc GIS 10.2. It is found that the built-up and fallow lands have increased in above 550 percent and 130 percent while agriculture, vegetative, fallow lands and wetlands have decreased 76 percent, 60 percent 75 percent respectively during four decades. Shannon Entropy was used to analyse for monitoring and measuring of urban sprawl in the study area. It is known that the pattern of urban growth was shifted from infill to leapfrogging, edge expansion as well as strip or ribbon fallowing the Barasat-Barrackpor road, Taki road Jessore raod (NH35) and Krishnanagar Road (NH34). The urbanisation was concentrated primarily around the city centre. Later the urban sprawl happens fallowing the road connectivity in northern, north-eastern, eastern, western and south-western direction. This study can be helped to devise proper urban landscape planning and management for sustainable urban growth in the study area.

Key words: Urban sprawl, LULC Classification, Shannon’s entropy, leapfrog and strip or ribbon urban growth

Introduction

Urban expansion is natural process and it consumes many hectares of prime agricultural lands from their surrounding every years. This results to the change and loss of livelihood pattern for the agrarian communities. Urbanization involves changes in the physical and functional components of the built environment and subsequently accelerates the transition of landscape to urban forms (Castle and Crooks, 2006). In today’s world, more than half of the global population lives in urban areas and by 2050, this figure is projected to increase to more than 65 percent (United Nations, 2014). The term ‘urban sprawl’ has been used commonly to describe physical expansion of urban area. The rapid urbanization is observed in peri-urban areas and urban fringe resulting in the growth of urban sprawl (Harris and Ventura, 1995). Nelson (1995) describe as “unplanned, uncontrolled, and uncoordinated single use development that does not provide for a functional mix of land use and/or is not functionally related to surrounding land uses and which variously appears as low density, ribbon or strip, scattered, leapfrog, or isolated development”. The urban expansion is particular important because it have strong effect on LULC change such as agricultural lands and water bodies (Attua & Fisher, 2011; Mohan et al., 2011). The expansion of urban requires more land and promotes the conversion of rural to urban LULC cover (Farooq & Ahmad, 2008; Mohan et al., 2011). The remote sensing and GIS techniques have been widely used for assessing and monitoring spatial patterns of urban growth in the past few years (Yeh and Li, 2001). Shannon’s entropy (Hn) is also used to assess the urban sprawl for the compact or dispersed pattern of settlement by using the equation for measuring the dispersion of geographical variables within class or zones (Singh, 2000). The built-up pixel is considered as an indicator of quantifying the urban growth based upon satellite imagery in urban studies (Sudhira et al., 2004; Joshi and Suthar, 2002). Managing and controlling this urban explosion is a very important challenge for developing countries like India (Cohen, 2004).

Study Area

Barasat town is the nodal city and headquarter of North 24 Parganas District. It is located between 22º40ʹ18ʺ - 22º44ʹ32ʺN latitudes and 88º26ʹ44ʺ - 88º 31ʹ21ʺE longitudes. The study area is also located in the north-eastern part of Kolkata Metropolitan Area (KMA) (Fig. 1). It is bounded by Khilkapur and Chhoto Jagulia in Northern, Madhyamgram Municipality and Khamarpara in the South, Kadambagachhi and Simultala in the East and Nilganj in the West. The eastern and northern parts of Kolkata are more sprawling than southern and western part (Bhatta, 2009). Similarly, north-eastern and south-eastern region of Kolkata Urban Agglomeration area has experienced urban growth in their sub urban fringe in the form of satellite towns (Sahana et al., 2018). Sardar and Hazra (2015) noticed that the peri-urbanisation was taken in peripheral area of municipalities, urban centres and daily commuters’ zones in Peri-urban area of North 24 Parganas district. Biswas and Sarkar (2019) have highlighted the urbanisation as well as urban sprawl such as leapfrog and ribbon pattern within Barasat municipality up to 2014. The urban sprawl is happing toward the eastern direction in peri-urban agricultural, fallow and wetland lands between Barrackpore Trank Road and Kalyani Expressway in Barrackpore Subdivision (Pramanick, 2018). The urban expansion of sub-centres is the result of altering the agricultural and barren land into built-up area due to exponential population growth, rural-urban migration and developmental activities like transport facilities and railway network in North 24 Parganas district (Dhali, Chakraborty and Sahana, 2018). The uneven growth of built-up area is the most outstanding feature of urbanisation in the discussion of land transformation pattern, rate and their change ‘hotspot’ in western and southwestern part of the North 24 Parganas District (Bera & Chatterjee, 2019). The edge expansion of in Barasat Municipality is the most important factor for determining of Land Surface Temperature (LST) than leapfrog urban growth (Mukherjee & Das, 2018).

Fig. 1 Location Map of the Study Area

Objectives

1. To show land use and land cover classification and change detection analysis during the 40 years

2. To explore the pattern of urban sprawl and growth in Barasat town

3. To analyse the driving factors of urban expansion in the study area.

Methods and Methodology

Urbanisation has been calculated based on secondary data like population growth, decadal growth rate and population density collected from District Census Handbook, Census of India, 2011. The cloud-free and geometrically corrected Landsat Satellite images namely Thematic Mapper (TM) image (path 138 & row 44) from 14th November, 1990, Enhanced Thematic Mapper (ETM+) 17th Nov, 2000 (path 138 row 44), 6th Feb, 2010 (path138 row 44) and OLI 2nd Feb, 2020 with spatial resolution 30 m × 30 m were collected from USGS Earth Explorer.

The LULC classification was prepared by conducting maximum likelihood algorithm in supervised classification method of Arc GIS 10.2. Change detection analysis is very much helpful to identify various changes occurring in different classes of LULC like increase or decrease. It can be expressed in a simple formula as follows

I

A conversion of LULC class was presented to analyse the change of LULC classes using cross tabulation in Arc GIS 10.2 and M.S.Office. Accuracy assessment was measured by Kappa Index (Cohen, 1960). Cohen’s Kappa index is a multi-nominal sampling model used to measure the accuracy assessment (Galton, 1892). The kappa coefficient lies between 0 and 1. The value is closer to 1 represents the perfectly accurate and nearer 0 means lose their perfectness.

Shannon’s entropy is one of the commonly used and effective techniques for monitoring and measuring urban sprawl (Yeh and Li, 2001). It applied to study the relative concentration urbanisation phenomena (Shannon, 1948). This is used to measure the degree of compactness and dispersion of a geophysical variable among ‘n’ spatial units (Theil, 1967; Thomas, 1981). Following the work of Ramachandra, Aithal, and Sanna (2012), the built area divided into six different buffers zones using concentric circles with 1km radius around the Barasat city in Arc GIS 10.2.

II

Where, pi is the probability of the variable occurring in the ith blocks and n is the total number of zones. The Shannon’s entropy values lie between ‘0’ and loge (n). The value closer to zero means compact urban growth (higher density), while value closer to 'logen' indicates the dispersed distribution of the city’s built environment (Yeh and Li, 2001).

Results and Discussion

1. Pattern of Urbanisation

Barasat is the district town and part of Kolkata Metropolitan Area (KMA) in district North 24 Parganas. The urban expansion was started after partition of 24 Parganas into North and South 24 Parganas on March, 1986 and Barasat became district headquarter of the district . It has also a regional transportation hub as a rail and road junction. NH 12 (formerly NH 34/ Krishnanagar Road towards North Bengal), NH 112 (formerly NH 35/ Jessore Road, leading to the Bangladesh border at Petropole), Taki Road and Barrackpore-Barasat are the main road connectivity in the city. The municipality started to became populated following the creation of Bangladesh in 1971. The non- urban LULC is being converted into urban land. The rapid, hasty urbanisation associated with the population growth has become a significant challenge in this area. Since 1981, Barasat emerged as the most important trade centre due to its vast agricultural hinterland and proximity to Kolkata. Barasat was one of the 10 municipalities in Bengal formed in 1869 under the supervision of British rulers. The Partition of Bengal (1947) contributed a huge population to get shelter in this border Municipality. It is the popular class-I city among the twenty two municipalities of the District. The growth rate of urban population was 115 percent in Barasat Municipality after Dum Dum Municipality in 2011. The negative decadal growth rate of urban population is observed below 10 percent in Halisahar, Kanchanapara, Titagrah and Baranagar and above 10 percent in Khardah and Bhatpara municipalities Whereas, low positive decadal growth rate of population (above 10 percent) is noticed in Bongaon, Naihati, Ashoknaga-Kalyanagar Barrascpore, Kamarhati and South Dum Dum, North Dum Dum, Basirhat ,Madhyamgram, Bidhannagar and Rajarhat-Gopalpur municipalities respectively in 2011. So Barasat municipality is high urbanised in terms of population growth rate in the district.

Fig. 2 Population growth Fig. 3 Decadal Growth Rate of Population Fig. 4 Growth of Population Density

The population size of Barasat town (Class-V city) was below 10000 and decadal growth rate of population below 5% from 1901 to 1931 (Fig. 2). The reason of low growth rate of population might be mentioned as high fertility and mortality and poor socio-economic and health conditions in Barasat town. This town became Class- IV city with 7000 population growth and 29% and 42% decadal growth rate of population in 1941 and 1951. This period was great socio-political change and India became Independent. A large number of migrant came from Bangladesh (East Pakisthan) after partition of India they set up Bharam Colony, Laxmi Narayan Colony at Nabapally, Srijani Pally, and Gupta Colony etc. in Barasat town. The population growth has reached to 42000 person resulting the Barasat town became Class-III city. The decadal growth rate population in the city was 82 percent, and 45 percent respectively from 1951 to 1971. This town became Class-II city with population 70000 and decadal population rate have reached in 62% in 1981. The freedom fighting of Bangladesh had to immigrate here during this period. The rural people have started to come in urban area for searching job and opportunities. This town have reached in Class-I city with 10.7 lacks population and 54% decadal growth rate of population in 1991. Lastly the urban population has grown in 2.78 lacks and growth rate was 125 percent and 20.26 percent in 2001 and 2011 (Fig. 3) respectively. Trend of growth of population is given by the exponential curve: Y = 3079e with a goodness-of-fit of 92%. The density of population increased from 416 persons / sq. km. in 1901 to 772 persons / sq. km. in 1951 by almost 86%. It has suddenly jumped to 2055 persons / sq. km. by about 166% during 1951-61. After that the population density has steadily and rapidly increased from 2992 persons / sq. km. to 8071 persons / sq. km. in 2011. The trend of growth rate of population density can be explained by the exponential growth curve Y= 176.1e with a goodness-of-fit of 92% (Fig. 4).

2. Land Use- Land Cover classification and Change Detection Analysis

Land-use and land-cover change is one of the main driving forces of urban expansion. Encroachment of urban settlements on agricultural lands may pose terrible consequences such as land degradation and desertification (Shalaby, Ghar & Tateishi, 2004). The vegetative including forest scrub, orchard and degraded forest (Fig. 5) have reduced from 63.63 sq. km to 15.03 sq. km i.e. 76.38 percent from 1990 to 2000 (Table 1). Similarly the agriculture lands covering cultivated lands and plantation have decreased from 52.75 sq. km. to 21.09 sq. km. i.e. 60.02 percent during the last 40 years. On the other hand, built-up area including residential, Government Offices, educational institute, cantonments and market places etc. have drastically increased from 14.95 sq. km. to 98.19 sq. km. i.e. 550 percent during this periods. In this context, the fallow lands included barren lands and speculated fallow lands etc. have also increased from 4.86 sq. km. to 9.01 sq. km. i.e. 85.39 percent in the periods. Lastly, wetlands- the heart of the urban area- covering marshy land, lowlands, rivers, streams canals, lakes, tanks and reservoirs etc. reduced from 8.22 sq. km. to 2.04 sq. km. i.e. 4.28 percent during these periods in the study area.

The accuracy assessment (Table 1) all LULC types, the producer and user accuracy values were greater than 80 percent. The overall accuracy of LULC was 85%, 87%, 88% and 86% and kappa coefficients values were 0.82, 0.84, 0.83 and 0.85 in 1990, 2000, 2010 and 2020 respectively. Based on Congalton (1991), the above results indicate strong agreement between the ground truth and the classified classes. Furthermore, the overall accuracy and κ values met the minimum accuracy requirements for LULC change detection studies (Anderson et al. 1976).

Fig. 5 Land Use and Land Cover Classification in the year of 1990, 2000, 2010 and 2020.

Table 1 Land sue and land cover classification, change detection and Kappa co-efficient

LULC

Type

1990

2000

2010

2020

LULC Change (%)

Sq. km.

%

Sq. km.

%

Sq. km.

%

Sq. km.

%

1990-2000

2000-2010

2010-2020

1990-2020

Vegetation

63.63

44.75

56.08

38.70

28.25

19.57

15.03

10.38

-8.72

-51.36

-46.80

-76.38

Agriculture

52.75

36.53

49.14

34.26

29.65

20.54

21.09

14.51

-6.84

-39.66

-28.87

-60.02

Built-up Area

14.95

10.35

25.07

17.30

71.1

49.26

98.19

67.55

67.69

183.61

107.10

556.79

Fallow Lands

4.86

2.67

10.11

7.01

12.72

8.81

9.01

6.20

66.87

56.84

-29.17

85.39

Wet Lands

8.22

5.69

3.96

2.73

2.62

1.82

2.04

1.40

-51.82

-33.84

-22.14

-75.18

Total Area

144

100

144.36

100

144.34

100

390.17

100

Kappa Co-efficient

0.82

0.84

0.83

0.85

The vegetative lands have drastically reduced to 8.72 percent, 51.36 percent and 46.80 percent accordingly for the periods of 1990-2000, 2000-2010 and 2010-2020. The agricultural lands have decreased to 6.84 percent, 39.66 percent and 28.87 percent during the periods. On the hand the built-up areas have drastically increased in 67.87 percent, 183.51 percent and 107.10 percent respectively. The fallow lands have also increased to 66.87 percent, 56.84 percent, 1990- 2010 and decreased to 29.17 percent respectively, 2010- 2020. Lastly, the wetland lands have reduced to 51.82 percent, 33.84 percent and 22.14 percent in the same period.

Fig. 6 c

Fig. 6 b

Fig. 6 a

Fig. 6 Land Use and Land Cover Conversion to Built-up Area from LULC Classes

Fig. 7 a LULC classes conversion from 1990 to 2000 Fig. 7 b LULC classes conversion from 2000 to 2010 Fig. 7 c LULC classes conversion from 2010 to 2020 Vg- Vegetation, Ag Agricultural, Bu- Built-up, Fl- Fallow Lands and W- Wetlands

Landsue and land cover conversion helps to identify which type of lands have been converted another LULC classes (Fig. 6). The built-up area has increased 11.82 sq. km. from the conversion of 6.69 sq. km. agricultural lands, 2.47 sq. km. fallow lands, 2.01 sq. km. vegetative and 0.38 sq. km. wetlands during 1990 to 2000 (Fig. 6a & 7a). For the period of 2000- 2010, the built-up area has increased 46.25 sq. km. from the conversion of 18.62 sq. km. agricultural lands, 6.25 sq. km. fallow lands, 16.75 sq. km. vegetative and 4.63 sq. km. wetlands respectively (Fig. 6b & 7 b). Lastly, the 12.05 sq. km. agricultural lands, 5.31 sq. km. fallow lands, 7.37 sq. km. vegetative lands and 2.96 sq. km. wet lands have been transformed to 27.69 sq. km. built-up area during 2010-2020 (Fig. 6c & 7 c). So, the urban growth have less converted from other LULC classes, 1991-2000 and major increased from lands classes mainly agriculture and vegetative lands respectively during the last two decades in Barasat town.

3. Spatio-Temporal Urban Expansion

The process of urban expansion of Barasat town has experienced some as high- and low-speed stages. The urban built-up area of Barasat town has increased 83.75 sq. km. during last 40 years. I) Slow urban growth rate (1990-2000): The annual growth rate of urban expansion was 0.84 sq. Km. / year. It was concentrated around the three places namely Champadali More, Colony More, Duckbanglow More (Fig. 8e). So it was the period of starting of urban expansion in this region. II) Very Fast Urban Growth Rate (2000-2010): The urban expansion was raised to 3.88 sq. km. / year because of large scale migration from rural to urban area, cheap land value nearer the city area and development of urban facilities and amenities. III) Fast Urban Growth Rate (2010-2020): The rate of urban expansion was almost 2.22 sq. km. /year due to administrative, health, academic and other social services facilities. As a result the new urban growth center are flourishing at Borbaria, Loknath Mandir along with Barasat- Barrackpore Road, Khilkapur, Algaria, Maina and S. P. Office along with Krishnanagar Road, Kazipara and Foretun Township along with Jessore Road and Koyra Kodamagachi along with Taki Road in the study area.

Shannon entropy was computed for the year of 1990, 2000, 2010 and 2020. It ranges from 0.847 to 1.745 presented in Table 2. The entropy value is 0.847 which is the closer to zero and below the half of the logen indicates compact pattern of settlement in 1990 (Fig 8 a). The congested and overcrowded municipal urban area is observed in 1st and 2nd buffer and dispersed pattern of settlement in remaining. The entropy value is 0.882 which is similar above mentioned pattern in 2000 (Fig. 8 b). The relative entropy value is 0.27 which is also indicates compactness of settlement in the study area. The built-up area was 41.27 percent within 2 km radial distance and 49.73 percent within the next 4 km radial distance from the city centre. The entropy value is 1.518 which is the almost closer logen indicates dispersed pattern of settlement in 2010 (Fig. 8 c).The entropy value of 1st and 2nd around the city centre is compact pattern of settlement and remaining buffers in dispersed pattern of settlement. The built-up area was 31.27 percent within 2 km radial distance and 68.73 percent within the next 4 km radial distance from the city centre. The relative entropy value is maximum i. e. 0.836 indicates that drastic urban growth have happened fallowing the road connectivity during 2000-2010.

Fig. 8 a -8d Growth of Urban Built-up Area during the 1990, 2000, 2010 and 2020. Fig. 8 e Decadal growth of urban built-up area. Fig. 8 F Growth of urban built-up boundaries.

Table 2 Shannon Entropy values of concentric zones

Year

pilog(pi

Hn

Relative

entropy

loge (n)

loge (n/2)

1

2

3

4

5

6

1990

0.302

0.254

0.107

0.036

-0.094

-0.054

0.847

0.04

0.836

0.27

1.791

0.895

2000

0.306

0.257

-0.116

-0.041

-0.096

-0.066

0.882

2010

-0.266

-0.282

-0.302

-0.305

-0.208

-0.155

1.518

2020

-0.207

-0.251

-0.342

-0.352

-0.315

-0.278

1.745

The entropy value is 1.745 closers to logn indicate the overall dispersed pattern of settlement in 2020 (Fig. 8 d). The disparsed pattern of settlement have noticed in 1st 2nd and zones where 28.46 percent settlement belongs within municipal area and dispersed pattern of settlement notices in remaining zones 71.54 percent settlement belongs outside municipal area. The relative entropy value is 0.27 which indicates the urban sprawl in Barbaori, Loknath Mandir along the Barasat-Barrackpore Raod, Khilakapur, Maina and Aloria along with the Krishnanagar Road, Kyora Kaddamagachi and Kalikapur fallowing the Taki Road, Kazipara and Foretune Township along the Jessore Road and infill urban growth in between Barasat and Madhyamgram city allong the Jessore Road. So, urban growth has being started fallowing the National and State Highway in the peripheral of Barasat.

The trend of entropy was gentle slope indicates compactness pattern of settlement (Fig. 9) during 1990-2000. This curve have changed from gentle to steep, resulting the changing pattern of urban settlement from compactness to dispersed or sprawling during 2000-2010. Finally the curve represents the moderate nature also notices the leapfrog and strip or ribbon urban sprawling pattern during 2010-2020 in the study area.

Wilson et al. (2003) have identified three categories of urban growth: i) infill growth- development of a small tract of land mostly surrounded by urban land cover, ii) expansion growth- metropolitan fringe development or urban fringe and iii) outlaying growth: a change from non-developed to developed land. According to Holcombe (PERC, 1999), have recognized the three distinct kinds of urban growth i) leapfrog development: building on cheaper land at some distance from the existing urban area, ii) strip or ribbon development: building along the course of major roadways that radiate from the main urban area and iii) single-dimensional development: building houses on large lots with no commercial zones.

Fig. 9 Trend of urban growth in Barasat Town Fig. 10 Direction of urban growth in Barasat Town

The urban growth primarily concentrated with core urban area around the city centres in 1990. But the urban growth was happened towards Madhyamgram in south and south-western directions fallowing the infill and edge expansion urban growth during 1990-2000. It have maximum flourished starting leapfrog and strip or ribbon pattern along the road connectivity in all directions in the study area 2000-2010. Finally, the urban growth reached high level in Barasat town and surroundings fallowing the same urban growth pattern and process during 2010- 2020 (Fig. 10). The new sub-urban centres have started above mentioned places taking advantages of transport connectivity and availability of land buying cheap rate by the building developer and planners (Fig. 8 f). As a result, the low lands, marshy land, wetland, sickness brick field, fallow land and agricultural lands have converted to built-up land in the study area during the last 20 years. Consequently, Barasat and Madhyamgram municipalities have overlapped with each other and it is going to develop a large urban area in in North 24 Parganas District.

Table 3 Shannon’s entropy values in each zones

Year

NNE

ENE

ESE

SSE

SSW

WSW

WNW

NNW

Hn

Loge(n)

1990

-0.133

-0.131

-0.111

-0.115

0.163

-0.078

-0.053

-0.024

0.81

2.079

2000

0.125

0.138

0.131

0.053

-0.212

0.115

0.085

0.054

0.913

 

2010

-0.173

-0.251

-0.178

-0.116

-0.363

-0.366

-0.206

-0.074

1.727

 

2020

-0.152

-0.225

-0.153

-0.195

-0.373

-0.348

-0.215

-0.081

1.742

 

The patter of urbanisation was triangular shape and compactness pattern of settlement in Barasat town in 1990 when entropy value was 0.81, below the half of the entropy (Table 3). This pattern was similar in 2000, but the tendency of growth pattern was the expanding in south and south-west direction towards Madhyamgram. The entropy have increased in 1.727 closer to logen indicates urban sprawling in SSW, WSW, ENE and WNW in 2010. Lastly in it have reached in 1.742 also explores urban sprawl continuing the same orientations in 2020 in the study area.

Table 4 Relative Shannon’s entropy values in each zones

Zone

NNE

ENE

ESE

SSE

SSW

WSW

WNW

NNM

1990-2000

0.027

0.150

0.084

0.038

0.111

0.128

0.142

0.036

2000-2010

0.207

0.250

0.164

0.038

0.301

0.342

0.128

0.032

2010-2020

0.321

0.350

0.304

0.038

0.361

0.372

0.308

0.021

Hn

0.555

0.749

0.553

0.113

0.774

0.842

0.578

0.090

Loge(n)

1.099

Loge(n)/2

0.5449

The entropy value is higher than the half of the entropy value i.e. 0.5449 (Table 4) indicates high urban sprawling. The entropy value is higher than the half of the entropy value in north and north-eastern direction indicates urban sprawling mainly ribbon pattern along the Krishnanagar road connectivity. Similar urban growth observes in east and north-eastern zone fallowing the Jessore Road and east and south-east zone fallowing the Taki Road from Barasat town. Besides, the high expanding urban growth- entropy value closer to logen- mainly edge expansion, leapfrog and outlaying notices in south and south-west and west and south-west fallowing the Jessore Road from Barasat towards Madhyamgram. Lastly another urban growth observes in west and north- west zone along the Barasat-Barrackpore raod in the study area.

The leapfrog urban development have occurred on cheaper lands at Noapara (north-easterly), Maina and S.P. Office in north-westerly, Choto Bazar in westerly, Kalikapur in westerly etc. at 10 to 20 minutes by Toto, Ricksharw and bi-cycle from the city centre of Barasat. The strip or ribbon urban development has observed towards westerly at Tallykhola, Barboria, Loknathmandir and fallowing the Barasat-Barrackpore Road (SH2), Northerly at Maina, Chotto Jagulia along the With Krishnanagar Road (NH34), Northerly at Kazipara and Foretun City (Table 3) fallowing the Jessore Road (NH34) and easterly Kaira Kadambagachi and Simutala along the Taki Road during the concern periods (Fig. 8 e).

4. Driving factors the Urban Growth and Sprawl

The availability of land at nearer the city and fallowing the road connectivity is the main factor of very fast growing urban expansion in Barasat town. Many villages around the Barasat towns namely Jirat, Kashimpur, Kanthalia, Mandalganti, Bahera, Bara, Kadambagachhi are converting into census towns and increasing built-up area dispersed pattern (Hasnine & Rukhsana, 2020). The land value is lower i. e. 2-3 lacks / Khata in peri-urban area or around the city area than urban core area i.e. 8-15 lacks in the study area, 2011 (Biswas and Sarkar, 2019). Consequently, the developer, building planners and commercial projectors are choosing the low cast marshy lands that are available fallowing the Krishnagar (NH34), Jessore (NH35), Taki road (SH2) and Basarat- Barrackpore. Besides, Barasat urban area are selecting for residential purposes of low and middle income group people who are buying the low price land nearer the city in the study area. As a result, urbanisation as well as urban sprawl such as leapfrog patter are developing at Noapara, Chotobazar and Nabapally and ribbon patters are developing fallowing road connecivity (SH2) in Barasat urban area (Biswas and Sarkar, 2019). The speed of land transformation indicating urban ‘hotpots’ have noticeable changed during the past 27 years in Barasat-Barrackpore urban area in south-western part of the district (Bera and Das, 2019).

Demographic factors are the main causes of urbanisation in Barasat Town started from independence of India. Immigration from Bangladesh to Barasat was the main factor of urbanisation since 1971. Rural-urban migrations have being happened likewise stream migration from surrounding rural area namely Hingalganj and Sandeshkali-I and II. Large scale daily migrants regularly come to here for jobs and occupations in the study area. Fertility rate is high of slum population in Barasat Municipality. The is social service sectors mainly education, heatlth (District Hospital proposed to Medical College), banking West Bengal State University (Barasat University and Adamas University, Barasat Government College and Barasat College, popular English medium convent school name Auxilium convent school at Simultala, Delhi Public School, Narayana School, Kalyani Public School, Calcutta Public School and Barasat Jaurge Court etc. take role of pull factors for urban sprawling in this area.

Similarly, economic factors lead to urban sprawl in the study area. Marketing hub is located here namely Suncity Mall and Icore, Buget Bazar etc. Barasat have the wholesale marketing of medicine, grocery and fish market. Popular jewellry namely P C Chandra, M P Jewellers and Anjali Jewwleries at Duckbunlow More, and Sen Co. Ltd. Champadali More are located here. Tutimir Bus Stand locates at Chamapadali more from which one can go Durgapur, Asansole, Bankura, Digha, Krishnagar, North Bengal, Dhaka, Bongaon and Basirhat and hat, Hasnabad, Deganga, Baduria, Habra, Swarupnaga and Nabad Kati (DN35) and Barraskpore (81 and S-34) etc. Change of economic activities from agricultural activities to household and other services activities promote the level of urbanisation (Pramanick, 2019)

Finally, the administrative offices such as District Magistrate office, S.P. Office, Transport office, BLLRO office, Regional office of School Service Commission, Jourge Court etc. are located in Barasa town. As a result, daily migrants come to here for their official activities. The development of transport connectivity takes the pull factor for urban growth. Barasat town is the regional hub of transportation and communication of North- Eastern region of KMA. The Krishnanagar Road (NH34) towards North Bengal, Jessore Road (NH35), leading to the Bangladesh border at Petrapole, Taki Road and Barrackpore- Barasat Road are the main connectivity links to the city. The railway junction connecting Sealdah-Bongaon railway- towards Khulna, Bangladesh and Seahdal-Hasnabad railway leads to urban expansion in the area.

5. Conclusion

Urban expansion and LULC change in Barasat town have extremely changed during the three decades. The population growth rate is second highest in Barasat town among the twenty two class-I city in North 24 Parganas District. Decadal growth rate of population and population density in Barasat town was fast and steady since independence of India. The vegetative, agriculture and wetlands and fallow lands have rapidly decreased whereas built-up lands have increased in conversion of LULC classes during the four decades in the study area. The various types of driving factors such as district and administrative town, roads and railway connectivity, low land value nearer the city area, international and rural-urban migration, wholesale market, nearer location of Kolkata city, health facilities and social service etc. The pattern of urban growth was infill and concentrated around the Barasat city from 1990-2000. After that it is being switched over to edge-expansion, leap-frogging and ribbon urban growth and multi-cell urban growth develops at Barbaria, Loknath Mandir, Maina, Kalikapur and Kazipara fallowing the road connectivity during the last 20 years. The unplanned urban growth happens here and there along road network. So, proper urban land use map and urban planning should be introduced which will reduced the problems as well as give suitable places for urban expansion. The urban vegetation, open spaces, wetlands urban agriculture and control of rural- urban migration would help to set-up the sustainable urban growth.

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1901191119211931194119511961197119811991200120118.63400000000000038.78999999999999918.21100000000000038.672000000000000611.2316.02700000000000129.28099999999999942.64200000000000369.585999999999999107.53700000000001231.52099999999999278.435

Population in thousands

191119211931194119511961197119811991200120115.0932568149210908-6.58703071672354935.614419680915845329.49723247232472542.71593944790738882.69794721407625145.63027219015744263.18652971249003554.538269192078872115.2942708091168720.263388634292355

Population Growth Rate

190119111921193119411951196119711981199120012011415.6957149735195423.20654790563316395.3298025999037417.52527684159844540.6836783822821771.641791044776142054.80701754385972992.42105263157873436.34567901234555310.46913580246936710.7536231884068070.579710144928

Population Density

Ag-BuFa-BuBu-BuVe -BuW-Bu6.96451885404395732.46525821114636926.31287085939234242.01365597347383260.38014221624597927

Area in Sq. km.

Ag-BuFa-BuBu-BuV-BuW-Bu18.623095875502616.246778573062050212.02268449765621316.7476567829864784.6275170704202502

Area in sq km

Ag-BuBU-BuFa-BuV-BuW-Bu12.05241928132199531.29314060370535.30705329535324397.37007329615532042.95811711509179

Area in Sq km

19902000201020200.846999999999999980.882000000000000011.5181.7450000000000001

Year

Shannon's Entropy Value

1990NNEESESSWWNW1.65691.67690000000000011.90440000000000011.86123.66122.19960000000000021.88281.76842000NNEESESSWWNW1.97500000000000012.04999999999999982.1252.523.952.932.3551.85200000000000012010NNEESESSWWNW3.17430000000000012.94573.30569999999999994.54499999999999996.78209999999999988.38899999999999934.94460000000000033.20650000000000012020NNEESESSWWNW5.76199999999999965.52880000000000045.58629999999999964.51890000000000048.353500000000000410.4510000000000016.18670000000000013.7233000000000001

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