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.

This research reveals the magnitude of mangrove area loss and future impacts on mangrove species composition and distribution due to rise in Mean Sea Level (MSL). In this study, a geospatial model of potentially inundated areas was developed using Digital Elevation Model (DEM) data to assess the potential impacts of sea level rise (SLR) on the spatial distribution of mangrove species and estimate the potential inundation and subsequent mangrove area loss. The mangrove areas of 2646 ha, 9599 ha and 74,720 ha are projected to be inundated and subsequently lost by the end of the twenty first century for the low, medium and high SLR scenarios respectively under the net subsidence rate −2.4 mm/year relative to the baseline year 2000. All the major five mangrove species of the Bangladesh Sundarbans will be affected and this can potentially contribute to a change in the present species composition and biodiversity of the forest. Results suggest that, under the extreme scenario, inundation and subsequent loss of different mangrove species will be substantial and this can bring a massive change in the species composition and their spatial distribution in the Bangladesh Sundarbans.

Land cover change is a significant issue for environmental managers for sustainable management. Remote sensing techniques have been shown to have a high probability of recognizing land cover patterns and change detection due to periodic coverage, data integrity, and provision of data in a broad range of the electromagnetic spectrum. We evaluate the applicability of remote sensing techniques for land cover pattern recognition, as well as land cover change detection of the Hatiya Island, Bangladesh, and quantify land cover changes from 1977 to 1999. A supervised classification approach was used to classify Landsat Enhanced Thematic Mapper (ETM), Thematic Mapper (TM), and Multispectral Scanner (MSS) images into eight major land cover categories. We detected major land cover changes over the 22-year study period. During this period, marshy land, mud, mud with small grass, and bare soil had decreased by 85%, 46%, 44%, and 24%, respectively, while agricultural land, medium forest, forest, and settlement had positive changes of 26%, 45%, 363%, and 59%, respectively. The primary drivers of such landscape change were erosion and accretion processes, human pressure, and the reforestation and land reclamation programs of the Bangladesh Government.

Mangrove ecosystems are complex in nature. For monitoring the impact of climate variability in this ecosystem, a multidisciplinary approach is a prerequisite. Changes in temperature and rainfall pattern have been suggested as an influential factor responsible for the change in mangrove species composition and spatial distribution. The main aim of this study was to assess the relationship between temperature, rainfall pattern and dynamics of mangrove species in the Sundarbans, Bangladesh, over a 38 year time period from 1977 to 2015. To assess the relationship, a three stage analytical process was employed. Primarily, the trend of temperature and rainfall over the study period were identified using a linear trend model; then, the supervised maximum likelihood classifier technique was employed to classify images recorded by Landsat series and post-classification comparison techniques were used to detect changes at species level. The rate of change of different mangrove species was also estimated in the second stage. Finally, the relationship between temperature, rainfall and the dynamics of mangroves at species level was determined using a simple linear regression model. The results show a significant statistical relationship between temperature, rainfall and the dynamics of mangrove species. The trends of change for Heritiera fomes and Sonneratia apelatala show a strong relationship with temperature and rainfall, while Ceriops decandra shows a weak relationship. In contrast, Excoecaria agallocha and Xylocarpus mekongensis do not show any significant relationship with temperature and rainfall. On the basis of our results, it can be concluded that temperature and rainfall are important climatic factors influencing the dynamics of three major mangrove species viz. H. fomes, S. apelatala and C. decandra in the Sundarbans.