Comprehensive geospatial approaches to delineate near real-time (NRT) flood inundation and damage assessment of Tripura, India

Floods are among the most devastating hydro-meteorological hazards, leaving behind a trail of destruction to life, property, agriculture, and infrastructure. In northeastern India, Tripura stands resilient yet vulnerable to the onslaught of monsoon-driven floods, shaped by its hilly terrain and heavy rainfall. This study embarks on a mission to assess flood inundation mapping and the impact on agricultural and built-up areas in four districts: Gomati, Sipahijala, South Tripura, and West Tripura, during the severe monsoon floods of August 2024. Harnessing the power of Sentinel-1 Synthetic Aperture Radar (SAR) and EOS 04 MSR SAR data, this study unveil near real-time insights into the flood's extent and effects. By utilizing Google Earth Engine (GEE) and SigmaSAR V3.1, satellite datasets have been processed and analyzed in a very short time. The integration of SAR imagery with Random Forest land use and land cover (LULC) classification techniques proves invaluable for mapping flood inundation and assessing damage. The results reveal that out of 85021.46 ha (ha) of agricultural land, 10,510.32 ha were inundated, with Gomati and West Tripura facing the greatest challenges, where 13 % of the total farmland was flooded. In the realm of built-up areas, 928.72 ha of the total 75180.26 ha were affected, with Gomati District experiencing the most significant inundation, marking 1.5 % of its built-up regions flooded. These findings serve as a strong impetus for enhanced flood management strategies, igniting the need for improved early warning systems and innovative urban planning.