Geospatial Analysis of Coastal Inundation in Maharashtra Using DEM and IPCC Forecasts: A Google Earth Engine Approach for Climate Resilience
Keywords: SLR, DEM, IPCC, Inundation, GEE, Cartosat
Abstract. Coastal regions are increasingly vulnerable to sea level rise (SLR) due to climate change, threatening ecosystems, infrastructure, and livelihoods. This study presents a geospatial analysis of SLR and coastal inundation in Maharashtra, India, by integrating high-resolution Cartosat DEM (2015–2019), JRC Global Surface Water (1984–2020), and IPCC AR6 projections (2020–2030) using the Google Earth Engine (GEE) cloud platform. Permanent water bodies were masked, and percentile-based inundation scenarios were generated for 2020, 2024, and 2030. The methodology also involved applying percentile-based SLR thresholds (25th, 50th, and 75th) to assess multiple risk scenarios. Resulting inundation maps provide spatial insights essential for regional planning and disaster management. With predicted inundated areas ranging from 1851 km² to 1885 km², the findings emphasize areas at critical danger of floods. The resulting spatial maps identify critically vulnerable coastal zones, enabling evidence-based climate adaptation and disaster risk planning. This study supports sustainable coastal development, aligns with SDG 13 (Climate Action), and showcases the transformative potential of frontier geospatial technologies in building climate-resilient communities.
