Flood Mapping and Damage Assessment Using Synthetic Aperture Radar (SAR) Data in GIS and Google Earth Engine—A Case Study of 2020 Riverine Flood in Gaibandha, Kurigram, and Jamalpur Districts of Bangladesh

Floods are one of the greatest hazards in Bangladesh, however, in most cases, household-level risk-reduction strategies are inadequate for ensuring a livelihood resilient to floods. To formulate effective risk-reduction policies and programmes for riverine areas, it is crucial to measure flood risk at the local level. The monsoon floods coupled with prolonged inundation and the ravages of the COVID-19 pandemic have exacerbated the negative impacts on the flood-affected people. The creation of inundation maps are a very important tool to prevent or reduce flood hazards and risks by providing useful and reliable information to the population and remote sensing (RS)-based data provide multi-resolution satellite data for flood inundation mapping and flood risk zones identification, which are the first steps for the formulation of any flood management. RS technologies have made it easier to map large areas under flooding and provide early warnings of the disaster that helps in providing support in crisis situations and minimizing damage. Space-based sensors are comparatively more effective than ground-based techniques in providing near real-time data for monitoring the extent of floods and satellite platforms and other advances in RS have provided a wide range of applications of satellite data. The case study author conducts a flood extent mapping and damage assessment using Synthetic Aperture Radar (SAR) data captured by the Sentinel-1 satellite. The case study author recommends that Google Earth Engine, a free, cloud-based tool, is very useful for developing countries like Bangladesh to assess damages in emergency situation in a cost-effective way and that Synthetic Aperture Radar (SAR) data can also be utilized for estimating the extent of flooding in affected areas.