Improved Knowledge-Driven Flood Intelligent Monitoring (KDFIMv2): A Case Study of the 2024 Bangladesh Flood

Monitoring large-scale floods and tracking their evolution are essential for effective disaster response, particularly in regions where floods have widespread and dynamic impacts. Satellite-based flood detection using Synthetic Aperture Radar (SAR) and optical data faces challenges such as low spatial and temporal resolution, incomplete coverage, and cloud interference, which complicates the reliability of optical data. These issues hinder timely flood monitoring, which is critical for disaster management. This study introduces the Improved Knowledge-Driven Flood Intelligent Monitoring (KDFIMv2) method, which integrates SAR and optical data to improve flood monitoring by enhancing both spatial and temporal resolution.The main challenge in large-scale flood monitoring is low spatiotemporal resolution, caused by limited SAR sensor coverage, low temporal observation frequency, and cloud interference affecting optical…