Analysing Urban Sprawl and Spatial Expansion of Kolkata Urban Agglomeration Using Geospatial Approach

  • Mehebub Rahaman
  • Shyamal Dutta
  • Mehebub Sahana
  • Dipendra Nath Das


Since the last quarter of the twentieth century, India has been witnessing predominantly outward expansion of most large megacities in the form of sprawl, and peripheries have been engulfing many small towns and villages rather than accommodating the migrants from rural areas in the city core. Amidst this transformation, the condition of people living in peripheral areas becomes precarious which is explained by ‘degenerated periphery’. In this backdrop, the present study aims to assess the spatiotemporal urban expansion of different municipal areas and municipal corporation areas of Kolkata urban agglomeration of West Bengal, India, during 1990–2015. Landsat Thematic Mapper and Landsat 8 OLI satellite data of the years 1990 and 2015 along with Shannon’s entropy model and urban built-up index were used to assess the spatial dispersion of and consistency of urbanization. The investigations reveal a rapid increase of built-up areas outside the municipal boundaries during the last two and half decades. Shannon’s entropy at local level is computed, which shows dispersed unplanned urban growth, specifically in the outskirts of the city. The study indicates that the core of the city has experienced negative growth. Land use and land cover change analysis revealed that the built-up area has increased drastically over the study periods. The agriculture land and open land have transformed into built-up area, indicating the sprawl growth within the Kolkata urban agglomeration. The overall result shows that urban expansion of Kolkata urban agglomeration is not compact in nature and it is an evidence of concentration of sprawl growth over the municipalities.


Land use/land cover change Urban expansion Shannon’s entropy index Kolkata urban agglomeration 


  1. Abbas R (2016) Internal migration and citizenship in India. J Ethn Migr Stud 42(1):150–168 CrossRefGoogle Scholar
  2. Ahmed S, Bramley G (2015) How will Dhaka grow spatially in future?-modelling its urban growth with a near-future planning scenario perspective. Int J Sustain Built Environ 4(2):359–377CrossRefGoogle Scholar
  3. Al-shalabi M, Billa L, Pradhan B, Mansor S, Abubakr A, Al-Sharif A (2012) Modelling urban growth evolution and land-use changes using GIS based cellular automata and SLEUTH models: the case of Sana’a metropolitan city, Yemen. Environ Earth Sci 70:425–437 CrossRefGoogle Scholar
  4. Al-shalabi M, Billa L, Pradhan B, Mansor S, Al-Sharif AA (2013) Modelling urban growth evolution and land-use changes using GIS based cellular automata and SLEUTH models: the case of Sana’a metropolitan city, Yemen. Environ Earth Sci 70(1):425–437CrossRefGoogle Scholar
  5. Al-sharif AA, Pradhan B (2015) A novel approach for predicting the spatial patterns of urban expansion by combining the chi-squared automatic integration detection decision tree, Markov chain and cellular automata models in GIS. Geocarto Int 30(8):858–881CrossRefGoogle Scholar
  6. Angel S, Parent J, Civco D (2007) Urban sprawl metrics: an analysis of global urban expansion using GIS. Proceedings of ASPRS 2007 annual conference, Tampa, Florida May 7–11.
  7. Awasthi A, Chauhan SS, Goyal SK (2011) A multi-criteria decision making approach for location planning for urban distribution centers under uncertainty. Math Comput Model 53(1–2):98–109CrossRefGoogle Scholar
  8. Bhagat RB, Mohanty S (2009) Emerging pattern of urbanization and the contribution of migration in urban growth in India. Asian Popul Stud 5(1):5–20CrossRefGoogle Scholar
  9. Bhatta B (2009) Analysis of urban growth pattern using remote sensing and GIS: a case study of Kolkata, India. Int J Remote Sens 30(18):4733–4746CrossRefGoogle Scholar
  10. Bhatta B (2010) Analysis of urban growth and sprawl from remote sensing data. Springer, BerlinCrossRefGoogle Scholar
  11. Brenner N, Schmid C (2014) The ‘urban age’in question. Int J Urban Reg Res 38(3):731–755CrossRefGoogle Scholar
  12. Castle CJ, Crooks AT (2006) Principles and concepts of agent-based modelling for developing geospatial simulations, Centre for Advanced Spatial Analysis University College London, 1-19 Torrington Place, London, WC1E 6BT, UKGoogle Scholar
  13. Census of India (1991) Primary census abstract, census of India. The government of India, Registrar General and Census Commissioner of India, Ministry of Home Affairs, New Delhi, IndiaGoogle Scholar
  14. Census of India (2011) Primary census abstract, census of India. The government of India, Registrar General and Census Commissioner of India, Ministry of Home Affairs, New Delhi, IndiaGoogle Scholar
  15. Cohen J (1968) Weighted kappa: nominal scale agreement provision for scaled disagreement or partial credit. Psychol Bull 70(4):213CrossRefGoogle Scholar
  16. Cohen B (2004) Urban growth in developing countries: a review of current trends and a caution regarding existing forecasts. World Dev 32(1):23–51. CrossRefGoogle Scholar
  17. Cohen B (2006) Urbanization in developing countries: Current trends, future projections, and key challenges for sustainability. Technol Soc 28(1-2):63–80CrossRefGoogle Scholar
  18. Dasgupta S, Asvani K, Gosain K, Rao S, Roy S, Sarraf M (2013) A megacity in a changing climate: the case of Kolkata. Clim Chang 116:747–766 CrossRefGoogle Scholar
  19. Dewan AM, Yamaguchi Y (2009) Land use and land cover change in Greater Dhaka, Bangladesh: Using remote sensing to promote sustainable urbanization. Appl Geogr 29(3):390–401CrossRefGoogle Scholar
  20. Dhar Chakrabarti PG (2001) Urban crisis in India: New initiatives for sustainable cities. Dev Pract 11(2-3):260–272CrossRefGoogle Scholar
  21. Duany A, Plater-Zyberk E, Speck J (2001) Suburban nation: the rise of sprawl and the decline of the American dream. Macmillan, New YorkGoogle Scholar
  22. Dutta S, Sahana M, Guchhait SK (2017) Assessing anthropogenic disturbance on forest health based on fragment grading in Durgapur Forest Range, West Bengal, India. Spat Inf Res 25(3):501–512CrossRefGoogle Scholar
  23. Ghosh D, Sen S (1987) Ecological history of Calcutta’s wetland conversion. Environ Conserv 14(3):219–226CrossRefGoogle Scholar
  24. Grimm NB, Faeth SH, Golubiewski NE, Redman CL, Wu J, Bai X, Briggs JM (2008) Global change and the ecology of cities. Science 319(5864):756–760CrossRefGoogle Scholar
  25. Haack BN, Rafter A (2006) Urban growth analysis and modeling in the Kathmandu Valley, Nepal. Habitat Int 30(4):1056–1065CrossRefGoogle Scholar
  26. Hashem N, Balakrishnan P (2015) Change analysis of land use/land cover and modelling urban growth in greater Doha, Qatar. Ann GIS 21(3):233–247CrossRefGoogle Scholar
  27. Jat MK, Garg PK, Khare D (2008) Monitoring and modelling of urban sprawl using remote sensing and GIS techniques. Int J Appl Earth Obs Geoinf 10(1):26–43CrossRefGoogle Scholar
  28. Jamil M, Sahana M, Sajjad H (2018) Crop suitability analysis in the Bijnor District, UP, using geospatial tools and fuzzy analytical hierarchy process. Agricultural research, Springer 1-17. CrossRefGoogle Scholar
  29. Jiang F, Liu S, Yuan H, Zhang Q (2007) Measuring urban sprawl in Beijing with geo-spatial indices. J Geogr Sci 17:469–478CrossRefGoogle Scholar
  30. Jokar J, Helbich M, De-Noronha E (2013) Spatio-temporal simulation of urban growth patterns using agent-based modeling: the case of Tehran. Cities 32:33–42. CrossRefGoogle Scholar
  31. KMC (2015) Basic statistics of Kolkata. Accessed May 2016
  32. KMDA (2011) Kolkata metropolitan development authority. Accessed May 2016
  33. Li X, Yeh AGO (2004) Analyzing spatial restructuring of land use patterns in a fast growing region remote sensing and GIS. Landsc Urban Plan 69:335–354CrossRefGoogle Scholar
  34. Luo L, Mountrakis G (2010) Integrating intermediate inputs from partially classified images within a hybrid classification framework: an impervious surface estimation example. Remote Sens Environ 114(6):1220–1229CrossRefGoogle Scholar
  35. Mondal B, Das DN, Dolui G (2015) Modeling spatial variation of explanatory factors of urban expansion of Kolkata: a geographically weighted regression approach. Model Earth Syst Environ 1:29. CrossRefGoogle Scholar
  36. Mondal B, Das DN, Bhatta B (2016) Integrating cellular automata and Markov techniques to generate urban development potential surface: a study on Kolkata agglomeration. Geocarto Int. CrossRefGoogle Scholar
  37. Mukherjee M (2012) Urban growth and spatial transformation of Kolkata metropolis: a continuation of colonial legacy. ARPN J Sci Technol 2:365–380Google Scholar
  38. Montgomery MR (2008) The urban transformation of the developing world. Sci 319(5864):761–764CrossRefGoogle Scholar
  39. Nuissl H, Haase D, Lanzendorf M, Wittmer H (2009) Environmental impact assessment of urban land use transitions—a context-sensitive approach. Land Use Policy 26(2):414–424CrossRefGoogle Scholar
  40. Population Division (2014) World urbanization prospects: The 2014 revision, highlights (ST/ESA/SER.A/352)Google Scholar
  41. Prenzel B (2004) Remote sensing-based quantification of land-cover and land-use change for planning. Prog Plan 61(4):281–299CrossRefGoogle Scholar
  42. Puyravaud JP (2003) Standardizing the calculation of the annual rate of deforestation. For Ecol Manag 177(1–3):593–596CrossRefGoogle Scholar
  43. Ramachandra TV, Aithal BH, Sowmyashree MV (2014) Urban structure in Kolkata: metrics and modelling through geo-informatics. Appl Geomat 6:229–244. CrossRefGoogle Scholar
  44. Roy D, Lees M, Palavalli B, Pfeffer K, Sloot M (2014) The emergence of slums: a contemporary view on simulation models. Environ Model Softw 59:76–90CrossRefGoogle Scholar
  45. Sahana M, Sajjad H (2017) Evaluating effectiveness of frequency ratio, fuzzy logic and logistic regression models in assessing landslide susceptibility: a case from Rudraprayag district, India. J Mt Sci 14(11):2150–2167CrossRefGoogle Scholar
  46. Sahana M, Sajjad H (2018) Assessing influence of erosion and accretion on landscape diversity in sundarban biosphere reserve, lower ganga basin: a geospatial approach in quaternary geomorphology in india. Springer, Cham, pp 191–203 2019Google Scholar
  47. Sahana M, Hong H, Sajjad H (2018) Analyzing urban spatial patterns and trend of urban growth using urban sprawl matrix: A study on Kolkata urban agglomeration, India. Sci Total Environ 628–629:1557–1566CrossRefGoogle Scholar
  48. Sajjad H, Iqbal M (2012) Impact of urbanization on land use/land cover of Dudhganga watershed of Kashmir Valley, India. Int J Urban Sci 16(3):321–339CrossRefGoogle Scholar
  49. Sajjad H (2014) Living standards and health problems of lesser fortunate slum dwellers: evidence from an Indian City. Int J Environ Protect Policy 2(2):54–63. CrossRefGoogle Scholar
  50. Sang L, Zhang C, Yang J, Zhu D, Yun W (2011) Simulation of land use spatial pattern of towns and villages based on CA–Markov model. Math Comput Model 54(3–4):938–943CrossRefGoogle Scholar
  51. Shannon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27(3):379–423CrossRefGoogle Scholar
  52. Shaw A, Satish MK (2007) Metropolitan restructuring in post-liberalized India: separating the global and the local. Cities 24(2):148–163CrossRefGoogle Scholar
  53. Su S, Xiao R, Jiang Z, Zhang Y (2012) Characterizing landscape pattern and ecosystem service value changes for urbanization impacts at an eco-regional scale. Appl Geogr 34:295–305CrossRefGoogle Scholar
  54. Sugiyama M (2008) The study on climate impact adaptation and mitigation in Asian coastal mega cities of integrated research system for sustainability science. University of Tokyo. Final Report to JICAGoogle Scholar
  55. Taubenböck H, Wegmann M, Roth A, Mehl H, Dech S (2009) Urbanization in India–spatiotemporal analysis using remote sensing data. Comput Environ Urban Syst 33(3):179–188CrossRefGoogle Scholar
  56. Torrens PM, Alberti M (2000) Measuring sprawl. Centre for Advanced Spatial Analysis, LondonGoogle Scholar
  57. UN (2011) World urbanization prospects: the 2011 revision. United Nations Department of Economic and Social Affairs/Population Division, New YorkGoogle Scholar
  58. United Nations Population Fund (2007) The state of world population 2007: unleashing the potential of urban growth, United Nations publications, and chapter 1Google Scholar
  59. United Nations (2014) World urbanization prospects. The 2014 revision department of economic and social affairs population division New YorkGoogle Scholar
  60. Velmurugan A, Sajjad H (2009) The study of land transformation and land degradation in Dehradun District, Uttrakhand. Deccan Geographer 48. (ISSN-0011-7269)Google Scholar
  61. World Bank Group (2013) World development indicators 2013. World Bank PublicationsGoogle Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Mehebub Rahaman
    • 1
  • Shyamal Dutta
    • 2
  • Mehebub Sahana
    • 3
  • Dipendra Nath Das
    • 1
  1. 1.Centre for the Study of Regional Development, School of Social SciencesJawaharlal Nehru UniversityNew DelhiIndia
  2. 2.Department of GeographyThe University of BurdwanBarddhamanIndia
  3. 3.Department of GeographyJamia Millia IslamiaNew DelhiIndia

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