Assessing Land Cover Changes in the Sundarbans After Cyclone Remal Using Remote Sensing

The Sundarbans, the world's biggest mangrove forest and swamp, is notable for its biodiversity, ecology, and local economy. However, the ecosystem's distinct structure is increasingly vulnerable to both natural disasters, particularly cyclones, and pressurized human activity. The purpose of this study was to evaluate changes in land use and land cover (LULC) before and after Cyclone Remal (May 2024) in the Sundarbans region of Bangladesh, utilizing the Sentinel 2 imageries in the Google Earth Engine (GEE) platform. Here, the Normalized Difference Vegetation Index (NDVI) and supervised classification techniques have been used to assess the changes in landcover pattern, including the waterlogging, vegetation loss, and built-up areas, following the disaster. Here, an increase in water bodies (1.4%) and healthy vegetation (29.41%), where a decrease in built-up (0.17%), mudflat (1.83%), and less healthy vegetation (28.82%) have been observed, which crucially impacts the residents of the Sundarbans. Therefore, this study urges the utilization of satellite remote sensing-based management techniques to address the ecological and socioeconomic impacts that result from extreme weather events, such as cyclones.