Determination of Flood Subsidy (2023/2024) Based on SAR Images for Agricultural Land in Lower Saxony, Germany - C.-H. Yang; C. Stemmler; C. Röttger; C. Büker (The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences)
Following the severe flood event over the 2023/2024 New Year period, the Lower Saxony Ministry of Food, Agriculture, and Consumer Protection initiated a flood subsidy program for agricultural businesses. To evaluate the extent and duration of flooding across approximately 10,000 parcels, manual assessment was impractical. EFTAS leveraged Synthetic Aperture Radar (SAR) data, primarily from Sentinel-1, to develop a semi-automated process for detecting and quantifying flood coverage over multiple time points. The workflow is designed to integrate modules from SNAP and custom algorithms on a cloud-computing platform, generating backscatter coefficients to distinguish flooded and non-flooded areas. A GIS-based decision tree further refined the results by excluding permanent water bodies. Our project covers an area of 47,618 km2, utilizing 45 Sentinel-1 image packages, with observations every 3–5 days. The image quality was enhanced through adaptive non-local filtering. The results included precise flood extents, exemplified by dynamic changes near Lake Dümmer. The additional datasets, such as Sentinel-2 imagery and local photos, validated our flood evaluations. Our operational workflow demonstrates the adaptability of SAR for diverse applications, from post-event flood evaluation to near real-time emergency response. Future improvements include incorporating high-resolution imagery for urban assessments and leveraging rapid-revisit SAR constellations like Capella and ICEYE. This project underscores the cost-effectiveness and reliability of SAR-based flood detection, aiding decision-makers in subsidy allocation while paving the way for broader applications in disaster management.