Precision mapping of mangroves and shoreline dynamics in the Sundarbans using cloud based vegetation indices analysis and advanced geospatial techniques

• A novel approach is taken for fusing multiple raster indices in Google Earth Engine dense time series datasets. • A new raster index, CBMMI (Cloud-Based Mangrove Mapping Index), is developed for accurate mapping of mangroves. • Fifty years of Landsat datasets were used from the GEE’s repository for time series analysis to quantify the mangrove loss and island boundary delineation. • Accurate island boundaries are delineated, minimizing the tidal effect using image averaging using the best representative datasets. • Precise island boundaries are analyzed in DSAS to map the boundary change metrics. Mangrove ecosystems play a crucial role in sustaining ecological balance, protecting coastlines from erosion and natural disasters, and conserving biodiversity. Presently, the Indian Sundarban, particularly the southern region within the Tiger Reserve and Territorial Division, has witnessed alarming erosion rates and substantial loss of mangrove cover. This study focuses on the STR (Sundarban Tiger Reserve), the southernmost part of the Indian Sundarban region. This research introduces a novel methodology by applying dense temporal remote sensing datasets and geospatial analysis performed through Google Earth Engine (GEE) and further analyzing the output datasets through the GIS-based DSAS (Digital Shoreline Analysis System) using a newly developed raster-based mangrove index named CBMMI (Cloud Based Mangrove Mapping Index). This study further aimed to leverage the potential of the time series data, integrating it into the DSAS to analyse the island boundary change metrics, studying multiple parameters, and further relate the change to the mangrove cover. The cloud-based approach in GEE enables efficient estimation of the mangrove cover with the most representative annual dataset, thereby enhancing the mapping accuracy and reducing the bias in a spatio-temporal space. Integration of DSAS identifies the mangrove change hotspots and their pattern over a 50-year span from 1973 to 2023. An alarming shift in the island boundary of 2,321 m and 2,369 m was observed at Dalhousie Island and Bhangaduni Island, located in the southern part of the STR. These change hotspots were further analysed using bathymetric and cyclone data to identify the transformation.