The Fully-Automatic Sentinel-1 Global Flood Monitoring Service: Scientific Challenges and Future Directions

Abstract

One of the critical factors in operational satellite-based flood monitoring efforts is the time it takes from the acquisition of the satellite image to the delivery of the flood maps to users. Any human involvement, such as coordinating satellite acquisitions or manually interpreting images, can delay this process. To avoid such delays, a fundamentally new approach was adopted for the Sentinel-1 based Global Flood Monitoring (GFM) service: All Synthetic Aperture Radar (SAR) images acquired by the Sentinel-1 satellites in VV polarisation over land are processed entirely automatically, enabling flood maps to be delivered within eight hours of acquisition. The flood maps, along with a novel flood likelihood layer, are generated using ensemble approaches that integrate three complementary flood mapping algorithms along with reference water maps to distinguish flooded areas from permanent and seasonal water bodies. A notable feature of the service is its capability not only to depict flood-pixels evident in the Sentinel-1 images but also to provide contextual information that identifies areas where flood mapping is not feasible or problematic due to land cover and environmental conditions. These advancements were made possible through the use of a global 20 m backscatter datacube, which has enabled the characterisation of the backscatter behaviour for approximately 379 billion land surface pixels and deriving the reference water maps and a global flood archive. The GFM service was launched in 2021 as a new component of the Copernicus Emergency Management Service (CEMS) and has quickly garnered attention from users worldwide. In this review, we offer the first comprehensive overview of the scientific accomplishments and challenges faced during the first three years of operations. This analysis discloses discrepancies between the current service capabilities and the requirements of operational users, and provides directions for future research and service improvements, anticipating the increasing availability of systematic SAR data coverage from ROSE-L and other future SAR missions.