Abstract
Mangrove forests are disappearing at a faster rate than any other forests in many places around the world due to natural and anthropogenic causes; as a result, natural resources are decreasing. Considering these issues, present study focuses on the changing pattern of the world’s largest mangrove forest which locally known as Sundarbans, and utilized Landsat satellite imagery during the periods 2000 to 2021 as the primary data source. Using Google Earth Engine, the Normalized Difference Vegetation Index (NDVI) was applied to classify the images into 4 LULC categories (water bodies, sediment, forest, and others). The accuracies of the image classifications were between 89.76 and 92.21 percent. Classified images for the years 2000, 2010, and 2021 were then used to train and validate the ANN-CA (artificial neural network-based cellular automaton) model applied to produce the LULC scenario for the year 2031. On the other hand, a questionnaire survey was conducted in Sarankhola, and Shyamnagar Upazila to identify locals’ perceptions of the causes of LULC changes in the study area. The findings reveal a great change from 4036.92 to 3969.33 km2 of forest cover between 2000 and 2021, and further degradation of 3913.03 km2 by the projected year (2031). The results show that all the 13 identified causes are driving the LULC changes in Sundarbans. The study also suggests if the appropriate management practices are not implemented, the study area's forest land degradation will likely continue in the years to come.
 The Dhaka University Journal of Earth and Environmental Sciences, Vol. 12(1), 2023, P 89-105
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