Geospatial Intelligence for Modelling Shoreline Dynamics in a Mangrove-encompassed Bhitarkanika region, Odisha, India

Serving as significant coastal ecosystems, mangroves and coastlines offer wide range of services and contribute majorly to the socio-economic persistence to the communities. Coastal zones of the Bhitarkanika region (encompasses Bhitarkanika mangrove), in the eastern coastal state of India, exhibit pronounced geomorphic instability driven by hydrodynamic forcing, sediment disequilibrium, and expanding anthropogenic activities. This study formulates an integrated geospatial framework combining Digital Shoreline Analysis System (DSAS), Coastal Vulnerability Index (CVI), and Binary Logistic Regression (BLR) to quantify shoreline dynamics and assess multi-hazard coastal vulnerability. Multi-temporal shorelines derived from Landsat-8 (2013) and Sentinel-2 (2016, 2019, 2022, and 2025) datasets, corrected for tidal variability and validated using Google Earth. The results revealed a predominantly erosional trend, with 87.80% of transect undergoing shoreline retreat and a mean erosion rate of –11.57 m yr⁻¹. Field observations corroborate approximately 174 m of sediment deposition in accretion zones and ~189 m of land loss across rapidly eroding around the mangrove tract. The CVI was developed using elevation, slope, land use land cover (LULC), proximity to shoreline, river, and road, wherein the parameter weights were computed through Principal Component Analysis (PCA), correlation, entropy weighting, and an Ensemble Weighted Model (EWM). The CVI-based outputs indicate that ~47% of the coastline falls within high to very high vulnerability zone, primarily influenced by low-lying terrain, fluvio-marine interactions, and intense human activities. The BLR-based model demonstrates strong predictive performance (accuracy> 85%) and statistically validates the CVI-based output (>75% spatial agreement). The BLR and ensemble-based approaches represents a robust, multi-criteria framework for coastal vulnerability assessment and critical high-risk zonation. The findings provide reliable spatial intelligence to support shoreline management, mangrove restoration strategies, and climate-resilience planning in the Bhitarkanika coastal system.