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Abstract The impact of climate change and urbanization has increased the risk of flooding. During the UN Climate Change Conference 28 (COP 28), an agreement was reached to establish "The Loss and Damage Fund" with the specific purpose of providing assistance to low-income countries impacted by climate change. However, allocating the resources required for post-flood reconstruction and reimbursement is a challenging task due to the limited availability of data and the absence of a comprehensive tool. Here, we propose a novel resource allocation framework based on remote sensing and geospatial data, such as buildings and population, near the flood peak. The quantification of resource distribution utilizes an exposure index for each municipality, which interacts with various drivers, including flood hazard drivers, buildings exposure, and population exposure. The proposed framework assesses the flood map using images derived from pre- and post-flood Sentinel-1 Synthetic Aperture Radar (SAR) data for flood extent and Sentinel-2 optical images for ground truth. To demonstrate the effectiveness of this framework, an analysis was conducted on the flood that occurred in the Thessaly region of Greece in September 2023. The analysis revealed that the municipality of Palamas has the highest need for resource allocation, with an exposure index rating of 6/6. This framework can be used by any government for rapid decision-making and to expedite post-flood recovery.
Eudaric et al. (Mon,) studied this question.