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Mapping Long-Term Changes in Mangrove Species Composition and Distribution in the Sundarbans

Ecosystem Management, School of Environmental and Rural Science, University of New England, Armidale 2351, NSW, Australia
Geography and Environmental Studies, University of Rajshahi, Rajshahi 6205, Bangladesh
Author to whom correspondence should be addressed.
Academic Editors: Christian Ginzler and Timothy A. Martin
Forests 2016, 7(12), 305;
Received: 27 September 2016 / Revised: 23 November 2016 / Accepted: 29 November 2016 / Published: 3 December 2016
PDF [6474 KB, uploaded 3 December 2016]


The Sundarbans mangrove forest is an important resource for the people of the Ganges Delta. It plays an important role in the local as well as global ecosystem by absorbing carbon dioxide and other pollutants from air and water, offering protection to millions of people in the Ganges Delta against cyclone and water surges, stabilizing the shore line, trapping sediment and nutrients, purifying water, and providing services for human beings, such as fuel wood, medicine, food, and construction materials. However, this mangrove ecosystem is under threat, mainly due to climate change and anthropogenic factors. Anthropogenic and climate change-induced degradation, such as over-exploitation of timber and pollution, sea level rise, coastal erosion, increasing salinity, effects of increasing number of cyclones and higher levels of storm surges function as recurrent threats to mangroves in the Sundarbans. In this situation, regular and detailed information on mangrove species composition, their spatial distribution and the changes taking place over time is very important for a thorough understanding of mangrove biodiversity, and this information can also lead to the adoption of management practices designed for the maximum sustainable yield of the Sundarbans forest resources. We employed a maximum likelihood classifier technique to classify images recorded by the Landsat satellite series and used post classification comparison techniques to detect changes at the species level. The image classification resulted in overall accuracies of 72%, 83%, 79% and 89% for the images of 1977, 1989, 2000 and 2015, respectively. We identified five major mangrove species and detected changes over the 38-year (1977–2015) study period. During this period, both Heritiera fomes and Excoecaria agallocha decreased by 9.9%, while Ceriops decandra, Sonneratia apelatala, and Xylocarpus mekongensis increased by 12.9%, 380.4% and 57.3%, respectively. View Full-Text
Keywords: mangroves; Sundarbans; remote sensing; image classification; change detection; Landsat mangroves; Sundarbans; remote sensing; image classification; change detection; Landsat

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Ghosh, M.K.; Kumar, L.; Roy, C. Mapping Long-Term Changes in Mangrove Species Composition and Distribution in the Sundarbans. Forests 2016, 7, 305.

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