Flood Hazard Assessment and Cropland Damage Estimation Using Harmonized Sentinel-2 and SAR Data

Floods significantly threaten agricultural productivity, particularly in regions prone to seasonal events. This study focuses on flood hazard assessment and cropland damage estimation in Tripura, India, during the August 2024 flood. Using multi-temporal Harmonized Sentinel-2 NDVI and Sentinel-1 SAR data, we evaluated the flood's impact on agricultural and built-up areas. Between August 1 and August 30, 2024, the flood affected 19,788 hectares, including approximately 17,170 hectares of cropland and 16 hectares of built-up areas, exposing an estimated 4,377 people to floodwaters. NDVI data from 2018 to 2024 was analyzed to track the pre- and post-flood vegetation health and assess recovery in the affected regions, while high-resolution flood extent mapping was made possible by Sentinel-1 SAR data. The integration of NDVI and SAR data enabled an accurate and timely assessment of flood damage across large areas, highlighting the potential of remote sensing technologies in disaster monitoring. This method works especially well for assessing agricultural risk since the findings offer important information about how floods affect crop health in different geographic locations. The study shows how multi-source remote sensing data can assist decision-making in flood management and agricultural recovery by monitoring vegetation recovery and determining the degree of flooding. This work underscores the importance of timely, accurate damage assessments for disaster response and recovery efforts, particularly in regions like Tripura, where agriculture is a critical component of the local economy. The findings can inform flood mitigation strategies and long-term planning for flood-prone areas.