A satellite imagery-driven framework for rapid resource allocation in flood scenarios to enhance loss and damage fund effectiveness.

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" to assist low-income countries impacted by climate change. However, allocating the resources required for post-flood reconstruction and reimbursement is challenging 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 near the flood peak, such as buildings and population. 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 asses the flood extension using pre- and post-flood Sentinel-1 Synthetic Aperture Radar (SAR) data. 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 study revealed that the municipality of Palamas has the highest need for resource allocation, with an exposure index rating of 5/8. Any government can use this framework for rapid decision-making and to expedite post-flood recovery.