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ANALYZING DECADAL MANGROVE COVER CHANGE IN THE BANGLADESHI SUNDARBANS USING REMOTE SENSING

By: Md. Imran Hossain, Sabbir Ahmed Sweet, Nafia Muntakim, Mst. Tasnima Khatun, Shanita Tahnin, Tomalika Biswas, Md. Mujibor Rahman, Md. Redwanur Rahman

Key Words: Ecosystem monitoring, Land Cover Classification, Mangrove Degradation, Remote Sensing, Sundarbans

01 IES Volume- 12-01 pg1-15, December 2025.

Abstract

The Sundarbans Mangrove Forest in Bangladesh, the world’s largest tidal mangrove ecosystem, has undergone substantial ecological change over the past five decades. This study investigates land cover transformation from 1975 to 2025 using atmospherically corrected Landsat imagery and supervised Maximum Likelihood Classification (MLC). The landscape was categorized into four classes-Dense Forest, Sparse Forest, Bare Soil, and Water-across six periods to identify long-term spatial patterns and ecological vulnerabilities. Results reveal a 31.07% reduction in Dense Forest area (from 3914.06 km² to 2697.82 km²), accompanied by a 383.67% increase in Sparse Forest and a nearly 300% rise in Bare Soil. These trends reflect forest fragmentation, degradation, and progressive thinning of canopy cover, largely driven by upstream hydrological alterations, salinity intrusion, and increasing anthropogenic pressure. While the Water class showed minimal net change in surface extent, localized gains and losses aligned with tidal influence and sedimentation cycles. Transition matrices and gain-loss analyses identified southern estuarine margins and forest edges as degradation hotspots, while northern zones exhibited localized signs of regeneration. The classification results achieved high accuracy levels (84% to 92.3%) with Kappa values exceeding 0.80, confirming methodological reliability. This study emphasizes the need for integrated conservation, restoration planning, and improved freshwater governance to mitigate further degradation. The findings provide a scientific basis for adaptive ecosystem management in one of the world’s most climate-sensitive coastal environments.

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Md. Imran Hossain, Sabbir Ahmed Sweet, Nafia Muntakim, Mst. Tasnima Khatun, Shanita Tahnin, Tomalika Biswas, Md. Mujibor Rahman, Md. Redwanur Rahman

ANALYZING DECADAL MANGROVE COVER CHANGE IN THE BANGLADESHI SUNDARBANS USING REMOTE SENSING

01 IES Volume- 12-01 pg1-15, December 2025.

https://jenvosci.com/ies-publish/analyzing-decadal-mangrove-cover-change-in-the-bangladeshi-sundarbans-using-remote-sensing/

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