Flood direct damage assessment due to Typhoon Ulysses by satellite images

Distributing recovery funds after disasters is challenging. Often, some municipalities get excess funds while others do not get enough, therefore, this imbalance causes delays in reconstruction due to inefficient use of resources. Hence, during and after disasters, accurate quantification of monetary damages is crucial for policy decision. This paper presents a method for rapid evaluation of direct flood damage using Google Earth Engine (GEE) for swift action in flood-related disaster response, recovery, and reconstruction. The methodology uses the water detection algorithm utilizing Sentinel-1, equipped with Synthetic Aperture Radar (SAR), and incorporates the Floodwater Depth Estimation Tool (FwDET-GEE ver2.0) to estimate past flood depth of past events. Additionally, a land-cover map is generated through Random Forest Mapping using various satellite images, enabling precise classification of flood-affected agricultural areas. Subsequently, flood-induced damage is computed using damage curves, along with unit prices of the respective exposed element. The methodology is applied to assess the direct flood damage caused by Typhoon Ulysses which hit the Philippines on November 11th, 2020. The results are compared with field survey reports to evaluate the tool’s effectiveness and discuss its potential for rapid damage assessment. This comprehensive approach aims to provide a prompt and precise foundation for informed decision-making in the intricate disaster response, recovery and reconstruction process.