Abstract

Floods induced by heavy precipitation are one of the most frequent and devastating natural disasters, posing significant risks to human lives, infrastructure, and ecosystems. Accurate flood risk assessment is essential for disaster preparedness, response, and mitigation efforts. Remote sensing technologies have emerged as valuable tools for monitoring precipitation, analyzing flood risks, and improving the early warning systems. By providing real-time, largescale, and detailed data, remote sensing allows for the identification of flood-prone areas, the estimation of rainfall patterns, and the monitoring of hydrological changes that lead to flooding. This paper reviews the various remote sensing applications used in precipitation-induced flood risk analysis, highlighting key satellite platforms, sensor types, and methodologies. Through case studies, we assess how remote sensing data has been integrated into flood risk models and discuss the challenges and advantages of using such technology. The findings suggest that remote sensing plays a crucial role in enhancing flood prediction accuracy, guiding risk management strategies, and supporting climate adaptation efforts in flood-prone regions.