Estimation of Changes of Vegetation Cover in Sundarban Using Multi-Temporal Satellite Data

Estimation of Changes of Vegetation Cover in Sundarban Using Multi-Temporal Satellite Data

Krishan KunduPrasun Halder Jyotsna Kumar Mandal 

Department of Computer Science and Engineering, Govt. College of Engineering & Textile Technology, Serampore, India

Department of Computer Science and Engineering, Ram Krishna Mahato Government Engineering College, Purulia, West Bengal, India

Department of Computer Science and Engineering, University of Kalyani, Kalyani, Nadia, West Bengal, India

Corresponding Author Email:
22 August 2018
16 November 2018
31 December 2018
| Citation



Present study focuses the changes of vegetation cover (mangroves in forest region) in Sundarban during 2005 to 2015 based on the normalized difference vegetation index (NDVI). Seven vulnerable islands also reviewed which are positioned on the edge of south surface of Sundarban. The current survey reveals that approximately 1.07% vegetation area has been reduced during the period 2005-2010 and that of about 1.88% during 2010-2015. From the inspection of seven islands, it is seen that most of the islands are eroded more than 15% on the south region of the Sundarban because of submerging due to rising sea level. About 2.95% net vegetation area has been decreased during 2005 to 2015. This affect directly or indirectly on the normal biodiversity in Sundarban. It may also be inferred that the rate of depletion may be increased further in future. Therefore the study focuses to draw proper attention on extensive monitoring and managing the situation by arranging improvement of area of mangrove plantation.


vegetation cover, sundarban, NDVI, satellite data, change detection

1. Introduction
2. Study Area
3. Data and Methodology
4. Results and Dicussions

[1] Alongi DM. (2008). Mangrove forests: Resilience; protection from tsunamis; and responses to global climate change. Estuar. Coast. Shelf Sci. 76: 1-13.

[2] Fromard F, Vega C, Proisy C. (2004). Half a century of dynamic coastal change affecting mangrove shorelines of French Guiana. A case study based on remote sensing data analyses and field surveys. Marine Geology 208: 265-280.

[3] Cochard R, Ranamukhaarachchi SL, Shivakoti GP, Shipin OV, Edwards PJ, Seeland KT. (2008). The 2004 tsunami in Aceh and Southern Thailand: A review on coastal ecosystems; wave hazards and vulnerability. Perspect. Plant Ecol. Evol. Systemat. 10: 3-40.

[4] Ghosh A, Schmidt S, Fickert T, Nüsser M. (2015). The Indian Sundarban Mangrove Forests: History, utilization, conservation strategies and local perception. Diversity 7: 149-169.

[5] Giri C, Pengra B, Zhu Z, Singh A, Tieszen LL. (2007a). Monitoring mangrove forest dynamics of the

Sundarbans in Bangladesh and India using multi-temporal satellite data from 1973 to 2000. Estuarine, Coastal and Shelf Science 73: 91-100.

[6] Datta D, Deb S. (2012). Analysis of coastal land use/land cover changes in the Indian Sunderbans using remotely sensed data. Geo-spatial Information Science 15: 241-250.

[7] Giri C, Long J, Abbas S, Murali R, Qamer FM, Pengra B, Thau D. (2014). Distribution and dynamics of mangrove forests of South Asia. Journal of Environmental Management 148: 1-11.

[8] Morawitz DF, Blewett TM, Cohen A. (2006). Using NDVI to assess vegetative land cover change in central puget sound. Environ. Monit. Assess 114(1–3): 85–106.

[9] Nandy S, Kushwaha SPS. (2011). Study on the utility of IRS 1D LISS-III data and the classification techniques for mapping of Sunderban mangroves. J. Coast. Conserv. 15: 123-137.

[10] Rahman MM, Ullah M, Lan M, Sumantyo JT, Kuze H, Tateishi R. (2013). Comparison of Landsat image classification methods for detecting mangrove forests in Sundarbans. Int. J. Remote Sens. 34: 1041-1056.

[11] Raha AK, Zaman S, Sengupta K, Bhattacharyya SB, Raha S, Banerjee K, Mitra A. (2013). Climate change and sustainable livelihood programme: A case study from Indian Sundarbans. J. Ecol. 107: 335–348.

[12] Raha A, Das S, Banerjee K, Mitra A. (2012). Climate change impacts on Indian Sunderbans: A time series

analysis (1924–2008). Biodivers. Conserv. 21: 1289–1307.

[13] Unnikrishnan AS, Kumar MRR, Sindhu B. (2011). Tropical cyclones in the Bay of Bengal and extreme sea-level projections along the east coast of India in a future climate scenario. Curr. Sci. India 101: 327–331.

[14] Hazra S, Ghosh T, DasGupta R, Sen G. (2002). Sea level and associated changes in the Sundarbans. Sci. C. 68: 309–321.

[15] Nandy S, Bandopadhyay S. (2011). Trend of sea level change in the Hugli estuary, India. Indian J. Geo-Mar. Sci. 40: 802–812.

[16] Jayappa KS, Mitra D, Mishra AK. (2006). Coastal geomorphological and land-use and land cover study of Sagar Island, Bay of Bengal (India) using remotely sensed data. Int. J. Remote Sens. 27(17): 3671–3682.

[17] Mitra D, Karmekar S. (2010). Mangrove classification in sunderban using high resolution multi spectral remote sensing data and GIS. Asian J. Environ. Disast. Manage. 2(2): 197–207.

[18] Thomas JV, Arunachalam A, Jaiswal R, Diwakar PG, Kiran B. (2014). Dynamic land use and coastline changes in active estuarine regions – a study of sundarban delta, the international archives of the photogrammetry. Remote Sensing and Spatial Information Sciences, Volume XL-8, 2014 ISPRS Technical Commission VIII Symposium, Hyderabad, India.