Flood Mapping in the Coastal Region of Bangladesh Using Sentinel-1 SAR Images: A Case Study of Super Cyclone Amphan

Floods are triggered by water overflow into drylands from several sources, including rivers, lakes, oceans, or heavy rainfall. Near real-time (NRT) flood mapping plays an important role in taking strategic measures to reduce damage after a event. There many satellite imagery based remote sensing techniques that widely used generate maps. Synthetic aperture radar (SAR) images have proven be more effective due its high spatial resolution and cloud penetration capacity. This case study is focused on the super cyclone, commonly known as Amphan, stemming west Bengal-Bangladesh coast across Sundarbans 20 May 2020, with wind speed between 155 -165 gusting up 185 . The flooding extent determined analyzing pre post-event synthetic images, using change detection thresholding (CDAT) method. results showed inundated landmass of 2146 22 excluding Sundarban. However, area became 1425 about week event, precisely 28 2020 persistency generated severe intense flood, broken embankments. Furthermore, 13 out 19 coastal districts were affected flooding, while 8 highly inundated, Bagerhat, Pirojpur, Satkhira, Khulna, Barisal, Jhalokati, Patuakhali Barguna. These findings subsequently compared inundation map created validation survey immediately event also disposed location machine learning-based image classification technique. Consequently, comparison close similarity scenario reports secondary sources. circumstance envisages significant CDAT application providing relevant information for decision support system.