Integrated DSAS–InVEST modeling for quantitative assessment of shoreline dynamics and coastal exposure along the raigad coast, India

Coastal zones worldwide are increasingly threatened by climate change, rising sea levels, and intensified human activities, underscoring the urgent need for comprehensive vulnerability assessment frameworks. The present research conducts a comprehensive geospatial assessment of the Raigad district coastline in Maharashtra, India, by integrating the Digital Shoreline Analysis System (DSAS) with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Coastal Vulnerability Model. Multi-temporal Landsat imagery (2014–2025) was analysed using DSAS v6.0.170 to quantify historical shoreline changes across 1,481 transect at 100-meter intervals. Results reveal a complex coastal dynamic where 80.62% of transects exhibited accretion (mean + 58.78 m; maximum + 1,066.25 m), 19.38% showed erosion (mean − 23.80 m; maximum − 284.12 m). Linear Regression Rate analysis indicated an average erosion rate of -4.06 m/year, with maximum retreat reaching − 49.81 m/year. Complementarily, the InVEST model integrated seven biophysical variables such as geomorphology, elevation, bathymetry, wave and wind exposure, surge potential, sea-level rise, and natural habitat to generate a Coastal Exposure Index (CEI).Spatial analysis revealed pronounced vulnerability gradients, with northern coastal segments near Uran and Rewas exhibiting high exposure indices (EI ≥ 4) due to low elevation, sandy geomorphology, and degraded mangrove buffers. Conversely, southern zones demonstrated lower vulnerability (EI ≤ 2), attributed to dense mangrove cover and elevated terrain. This dual-model framework provides a scalable, evidence-based methodology for coastal zone management, supporting ecosystem-based adaptation strategies and climate resilience planning in similar geophysical contexts globally.