Skip to main content
Log in

Analyzing risk factors for shrinkage and transformation of East Kolkata Wetland, India

  • Published:
Spatial Information Research Aims and scope Submit manuscript

Abstract

The East Kolkata Wetland, called the ‘kidney’ of city Kolkata has now become a significant issue for its gradual loss and modification of anthropogenic activities. A socioeconomic elucidation had been used in this article through the analysis using GIS and field observation. Changes of wetland area have been determined from 1991 to 2017 with Landsat images and accuracy assessment through ground truth verification. It is seen that loss of wetland from 1991 to 2001 was 23.55% where it was 7.34% in 2011 to 2017, mainly due to the result of land transformation for aquaculture activity. Hence, three phases of degradation have been observed in this study, these are: the phase of rapid degradation, the phase of controlled degradation and phase of transforming degraded. At the same time, it’s highlighted the loophole of management actions. A multi-criteria analysis technique with the analytic hierarchy process has been applied to determine the risk factors of wetland degradation and it is seen that expansion of built-up area, encroachment of cropland, the transformation of wetland into fishing ponds are responsible for wetland degradation. In the conclusion, it highlights the approaches of land developers and real estate agents in their wetland hunting process and emergence consequences on the environment as well as conserving approaches for sustainable management.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
€32.70 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Indonesia)

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Mitsch, W. J., & Gosselink, J. G. (2007). Wetlands (4th ed.). Hoboken: Wiley. ISBN 978-0-471-69967-5.

    Google Scholar 

  2. Millennium Ecosystem Assessment. (2005). Ecosystems and human well-being: Synthesis. Washington, DC: Island Press.

    Google Scholar 

  3. Mitsch, W. J., & Gosselink, J. G. (1993). Wetlands (2nd ed.). New York: Wiley.

    Google Scholar 

  4. Barbier, E. B., Acreman, M., & Krowler, D. (1997). Economic valuation of wetlands: A guide for policy makers and planners. Gland: Ramsar Convention Bureau.

    Google Scholar 

  5. Malekmohammadi, B., & Rahimi Blouchi, L. (2014). Ecological risk assessment of wetland ecosystems using multi criteria decision making and geographic information system. Ecological Indicators, 41, 134–144. https://doi.org/10.1016/j.ecolind.2014.01.038.

    Article  Google Scholar 

  6. Papastergiadou, E. S., Retalis, A., Apostolakis, A., & Georgiadis, T. (2005). Environmental monitoring of spatio-temporal changes using remote sensing and GIS in a Mediterranean Wetland of Northern Greece. Water Resources Management, 22(5), 579–594. https://doi.org/10.1007/s11269-007-9179-7.

    Article  Google Scholar 

  7. Ehrenfeld, J. G. (2000). Evaluating wetlands within an urban context. Ecological Engineering, 15(3–4), 253–265. https://doi.org/10.1016/S0925-8574(00)00080-X.

    Article  Google Scholar 

  8. Huang, Y., Zhang, T., Wu, W., Zhou, Y., & Tian, B. (2017). Rapid risk assessment of wetland degradation and loss in low-lying coastal zone of Shanghai, China. Human and Ecological Risk Assessment, 23(1), 82–97. https://doi.org/10.1080/10807039.2016.1223536.

    Article  Google Scholar 

  9. Zedler, J. B., & Kercher, S. (2005). Wetland resources: Status, trends, ecosystem services and restorability. Annual Review of Environment Resource, 30, 39–74.

    Article  Google Scholar 

  10. Jiang, W., Lv, J., Wang, C., Chen, Z., & Liu, Y. (2017). Marsh wetland degradation risk assessment and change analysis: A case study in the Zoige Plateau, China. Ecological Indicators, 82, 316–326. https://doi.org/10.1016/j.ecolind.2017.06.05.

    Article  Google Scholar 

  11. Ziaul, S., & Pal, S. (2017). Estimating wetland insecurity index for Chatra wetland adjacent English Bazar municipality of West Bengal. Spatial Information Research, 25(6), 813–823. https://doi.org/10.1007/s41324-017-0147-x.

    Article  Google Scholar 

  12. Wanda, E. M. M., Mamba, B. B., Msagati, T. A. M., & Msilimba, G. (2016). Determination of the health of Lunyangwa wetland using Wetland Classification and Risk Assessment Index. Physics and Chemistry of the Earth, 92, 52–60. https://doi.org/10.1016/j.pce.2015.09.010.

    Article  Google Scholar 

  13. Zhang, W., Lu, Q., Song, K., Qin, G., Wang, Y., Wang, X., et al. (2014). Remotely sensing the ecological influences of ditches in Zoige Peatland, eastern Tibetan Plateau. International Journal of Remote Sensing, 35(13), 5186–5197. https://doi.org/10.1080/01431161.2014.939779.

    Article  Google Scholar 

  14. Zhou, H., Jiang, H., Zhou, G., Song, X., Yu, S., Chang, J., et al. (2010). Monitoring the change of urban wetland using high spatial resolution remote sensing data. International Journal of Remote Sensing, 31(7), 1717–1731. https://doi.org/10.1080/01431160902926608.

    Article  Google Scholar 

  15. Baker, C., Lawrence, R. L., Montage, C., & Patten, D. (2007). Change detection of wetland ecosystems using imagery and change vector analysis. Wetlands, 27, 610–619.

    Article  Google Scholar 

  16. Anderson, J. R., Hardy, E. E., Roach, J. T., & Witmer, R. E. (1976). A land use and land cover classification system for use with remote sensor data. In Geological survey professional paper 964, U.S. Government Printing Office, Washington, DC.

  17. Mahmud, M. S., Habiba, U., Haider, F., Ishtiaque, A., & Masrur, A. (2011). Remote sensing and map: GIS based spatio-temporal change analysis of Wetland in Dhaka City, Bangladesh. Journal of Water Resource and Protection, 3(11), 781–787. https://doi.org/10.4236/jwarp.2011.311088.

    Article  Google Scholar 

  18. Munyati, C. (2000). Wetland change detection on the Kafue Flats, Zambia, by classification of a multitemporal remote sensing image dataset. International Journal of Remote Sensing, 21, 1787–1806.

    Article  Google Scholar 

  19. Jones, K., Lanthier, Y., Van der Voet, P., Van Valkengoed, E., Taylor, D., & Fernandez-Prieto, D. (2009). Monitoring and assessment of wetlands using Earth observation: The GlobWetland project. Journal of Environment Management, 90, 2154–2169.

    Article  Google Scholar 

  20. Chen, S., Zeng, S., & Xie, C. (2000). Remote sensing and GIS for urban growth analysis in China. Photogrammetric Engineering and Remote Sensing, 66, 593–598.

    Google Scholar 

  21. Du, N., Ottens, H., & Sliuzas, R. (2010). Spatial impact of urban expansion on surface water bodies—a case study of Wuhan China. Landscape and Urban Planning, 94, 175–185. https://doi.org/10.1016/j.landurbplan.2009.10.002.

    Article  Google Scholar 

  22. Holland, C. C., Honea, J., Gwin, S. E., & Kentula, M. E. (1995). Wetland degradation and loss in the rapidly urbanizing area of Portland, Oregon. Wetlands, 15, 336–345. https://doi.org/10.1007/BF03160888.

    Article  Google Scholar 

  23. Zubair, O., Ji, W., & Weilert, T. (2017). Modeling the impact of urban landscape change on urban wetlands using similarity weighted instance-based machine learning and Markov model. Sustainability, 9(12), 2223. https://doi.org/10.3390/su9122223.

    Article  Google Scholar 

  24. Seti, R., Singh, K. V., Sahoo, S., Prasad, A., & Pateriya, B. (2015). Evaluation of NDWI and MNDWI for assessment of water logging by integrating digital elevation model and groundwater level. Geocarto International, 30(6), 650–661. https://doi.org/10.1080/10106049.2014.965757.

    Article  Google Scholar 

  25. Ashraf, M., & Nawaz, R. (2015). A comparison of change detection analyses using different band algebras for Baraila Wetland with Nasa’s multi-temporal landsat dataset. Journal of Geographic Information System, 7(7), 1–19. https://doi.org/10.4236/jgis.2015.71001.

    Article  Google Scholar 

  26. Zhou, H., Jiang, H., Zhou, G., Song, X., Yu, S., Chang, J., et al. (2010). Monitoring the change of urban wetland using high spatial resolution remote sensing data. International Journal of Remote Sensing, 31(7), 1717–1731. https://doi.org/10.1080/01431160902926608.

    Article  Google Scholar 

  27. Liu, G., Zhang, L., Zhang, Q., Musyimi, Z., & Jiang, Q. (2014). Spatio-temporal dynamics of wetland landscape patterns based on remote sensing in yellow river delta. China. Wetlands, 34(4), 787–801. https://doi.org/10.1007/s13157-014-0542-1.

    Article  Google Scholar 

  28. Rokni, K., Ahmad, A., Selamat, A., & Hazini, S. (2014). Water feature extraction and changed detection using multi temporal landsat imagery. Remote Sensing, 6(5), 4173–4189. https://doi.org/10.3390/rs6054173.

    Article  Google Scholar 

  29. Narumlani, S., Mishra, D. R. M., & Rothwell, R. G. (2004). Change detection and landscape metrics for inferring anthropogenic process in the greater EFMO area. Remote Sensing Environment, 91, 478–489.

    Article  Google Scholar 

  30. Ji, W., Xu, X., & Murambadoro, D. (2015). Understanding urban wetland dynamics: Cross-scale detection and analysis of remote sensing. International Journal of Remote Sensing, 36(7), 1763–1788. https://doi.org/10.1080/01431161.2015.1024895.

    Article  Google Scholar 

  31. East Kolkata Wetland Management Report of 2014–15 to 2015–16. (2016). East Kolkata Wetland Management Authority. http://ekwma.in/ek/documents/publications.

  32. National Wetland Atlas: Wetlands of International Importance under Ramsar Convention. (2013). Space Application Centre, ISRO, Ahmadabad. ISBN 9789382760054.

  33. Bhattacharya, S., Ganguli, A., Bose, S., & Mukhopadhyay, A. (2012). Biodiversity, traditional practishes and sustainability issues of East Kolkata wetlands: A significance Ramsarsite of West Bengal (India). BioSciences, 6(11), 340–347.

    Google Scholar 

  34. Mitra, D., & Banerji, S. (2018). Urbanisation and changing waterscapes: A case study of New Town, Kolkata, West Bengal, India. Applied Geography, 97, 109–118. https://doi.org/10.1016/j.apgeog.2018.04.012.

    Article  Google Scholar 

  35. Smith, G. M., Spencer, T., Murray, A. L., & French, J. R. (1998). Assessing seasonal vegetation change in coastal wetlands with airborne remote sensing: An outline methodology. Mangroves and Salt Marshes, 2(1), 15–28. https://doi.org/10.1023/A:1009964705563.

    Article  Google Scholar 

  36. Deng, C., & Wu, C. (2013). A spatially adaptive spectral mixture analysis for mapping subpixel urban impervious surface distribution. Remote Sensing of Environment, 133, 62–70. https://doi.org/10.1016/j.rse.2013.02.005.

    Article  Google Scholar 

  37. Bhatti, S. S., & Tripathi, N. K. (2014). Built-up area extraction using Landsat 8 OLI imagery. GIScience and Remote Sensing, 51(4), 445–467. https://doi.org/10.1080/15481603.2014.939539.

    Article  Google Scholar 

  38. McFeeters, S. K. (1996). The use of normalized difference water index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17, 1425–1432.

    Article  Google Scholar 

  39. Singh, V. K., Setia, R., Sahoo, S., Prasad, A., & Pateriya, B. (2015). Evaluation of NDWI and MNDWI for assessment of water logging by integrating digital elevation model and groundwater level. Geocarto International, 30(6), 650–661.

    Article  Google Scholar 

  40. Ko, B. C., Kim, H. H., & Nam, J. Y. (2015). Classification of potential water bodies using landsat 8 OLI and a combination of two boosted random forest classifiers. Sensors (Switzerland), 15(6), 13763–13777. https://doi.org/10.3390/s150613763.

    Article  Google Scholar 

  41. Chen, X. L., Zhao, H. M., Li, P. X., & Yin, Z. Y. (2006). Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sensing of Environment, 104(2), 133–146. https://doi.org/10.1016/j.rse.2005.11.016.

    Article  Google Scholar 

  42. Zha, Y., Gao, J., & Ni, S. (2003). Use of normalised difference built-up index in automatically mapping urban area from TM imagery. International Journal of Remote Sensing, 24, 583–594.

    Article  Google Scholar 

  43. Zhang, Y., Odeh, I. O. A., & Han, C. (2009). Bi-temporal characterization of land surface temperature in relation to impervious surface area, NDVI and NDBI, using a sub-pixel image analysis. International Journal of Applied Earth Observation and Geoinformation, 11(4), 256–264. https://doi.org/10.1016/j.jag.2009.03.001.

    Article  Google Scholar 

  44. Foody, G. M. (1992). On the compensation for chance agreement in image classification accuracy assessment. Photogrammetric Engineering and Remote Sensing, 58(10), 1459–1460.

    Google Scholar 

  45. Monserud, R. A., & Leemans, R. (1992). Comparing global vegetation maps with the Kappa statistic. Ecological Modelling, 62(4), 275–293. https://doi.org/10.1016/0304-3800(92)90003-W.

    Article  Google Scholar 

  46. Saaty, T. L. (1980). The analytical hierarchy process: Planning, priority setting, resource allocation (pp. 1–287). New York: McGraw-Hill.

    Google Scholar 

  47. Onuma, O. Y., & Tateishu, R. (2014). Urban flood vulnerability and risk mapping using integrated multi-parametric AHP and GIS: Methodological overview and case study assessment. Water, 6, 1515–1545.

    Article  Google Scholar 

  48. Sarkar, S., Parihar, S. M., & Dutta, A. (2016). Fuzzy risk assessment modelling of East Kolkata Wetland Area. A remote sensing and GIS based approach. Environmental Modelling and Software, 75, 105–118.

    Article  Google Scholar 

  49. Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83–98.

    Article  Google Scholar 

  50. Jiang, W., Wang, W., Chen, Y., Liu, J., Tang, H., Hou, P., et al. (2012). Quantifying driving forces of urban wetlands change in Beijing City. Journal of Geographical Sciences, 22(2), 301–314. https://doi.org/10.1007/s11442-012-0928-z.

    Article  Google Scholar 

  51. Ghosh, A., Maity, B., Chakrabarti, K., & Chattopadhyay, D. J. (2007). Bacterial diversity of east Calcutta wetland area: Possible identification of potential bacterial population for different biotechnological uses. Microbial Ecology, 54, 452–459.

    Article  Google Scholar 

  52. Sahu, P., & Sikdar, P. K. (2011). Threat of land subsidence in and around Kolkata City and East Kolkata Wetlands, West Bengal. India. Journal of Earth System Science, 120(3), 435–446. https://doi.org/10.1007/s12040-011-0077-2.

    Article  Google Scholar 

  53. Mondal, B., Dolui, G., Pramanik, M., Maity, S., Biswas, S. S., & Pal, R. (2017). Urban expansion and wetland shrinkage estimation using a GIS-based model in the East Kolkata Wetland, India. Ecological Indicators, 83, 62–73. https://doi.org/10.1016/j.ecolind.2017.07.037.

    Article  Google Scholar 

  54. Lehtinen, R. M., Galatowitsch, S. M., & Tester, J. R. (1999). Consequences of habitat loss and fragmentation of wetland amphibian assemblage. The Society of Wetlands Scientists, 19(1), 1–12.

    Article  Google Scholar 

  55. Ghosh, A. K. (1990). Biological resources of wetlands of east Kolkata. Indian Journal of Landscape System and Ecological Studies, 13, 10–23.

    Google Scholar 

  56. Ghosh, A., Maity, B., Chakrabarti, K., & Chattopadhyay, D. J. (2007). Bacterial diversity of east Calcutta wetland area: Possible identification of potential bacterial population for different biotechnological uses. Microbial Ecology, 54, 452–459.

    Article  Google Scholar 

  57. Bhattacharya, A., Sen, S., Roy, P. K. & Majumdar, A. (2008). A critical study on status of east Kolkata wetlands on special emphasis on water birds as bio-indicators, In M. Sengupta & R. Dalwani (Ed.), The 12th World Lake conference (Taal), 28th October–2nd November Jaipur, India (pp. 1561–1570).

  58. Raychaudhuri, S., Mishra, M., Nandy, P., & Thakur, A. R. (2008). Waste management: A case study of ongoing traditional practices at east Calcutta Wetland. American Journal of Agricultural and Biological Science, 3(1), 315–320. https://doi.org/10.3844/ajabssp.2008.315.320.

    Article  Google Scholar 

  59. Sahu, P., & Sikdar, P. K. (2011). Threat of land subsidence in and around Kolkata city and East Kolkata wetlands, West Bengal. India. Journal of Earth System Science, 120, 435446.

    Google Scholar 

  60. Ministry of Urban Development and Central Public Health and Environmental Engineering Organization (MoUD & CPHEEO) (2013). Advisory on conservation and restoration of water bodies in urban areas. New Delhi: Government of India. http://moud.gov.in/.

Download references

Acknowledgements

We are thankful to Rabi Saw to cooperate during field survey and also in debt to Mr. Sudip Bera (UGC-JFR) for supporting to map generation. We are also like to thanks to the anonymous reviewers of Spatial Information Research for their valuable suggestion and comments. We are also thankful to Editor-in-Chief of the journal of the Spatial Information Research.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Subrata Ghosh.

Ethics declarations

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ghosh, S., Dinda, S., Chatterjee, N.D. et al. Analyzing risk factors for shrinkage and transformation of East Kolkata Wetland, India. Spat. Inf. Res. 26, 661–677 (2018). https://doi.org/10.1007/s41324-018-0212-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41324-018-0212-0

Keywords

Navigation