Rapid Flood Assessment Using SAR Data and Cloud-Based Geospatial Apps

Floods are one of the most destructive natural hazards that causes severe loss to human life, infrastructure, agriculture, and the environment. Rapid identification of flood-affected areas is essential for the effective disaster response and recovery planning. Conventional flood mapping approaches based upon optical satellite imagery often fails during flood events due to cloud cover, heavy rainfall, and poor visibility. Synthetic Aperture Radar (SAR) overcomes these limitations by providing all-weather and day night observation capability. In this work, an interactive flood mapping and assessment system is developed by using Sentinel-1 SAR data on the Google Earth Engine (GEE) cloud platform. A before-and-after image comparison approach is employed to detect the newly flooded areas by analyzing the changes in SAR backscatter values. The proposed system allows the users to dynamically select the flood location, event date, area of interest, buffer distance, and SAR polarization (VV or VH) through a web-based interface. Flood extent maps are generated automatically, along with the quantitative statistics such as flooded area and percentage of affected region. The proposed SAR-based framework enables reliable and cloud-independent flood detection and provides rapid, user-driven flood assessment. The developed system has strong potential to support disaster management authorities in flood monitoring, impact assessment, and decision-making processes