REMOTE SENSING AND GOOGLE EARTH ENGINE FOR RAPID FLOOD MAPPING AND DAMAGE ASSESSMENT: A CASE OF TYPHOON GONI (ROLLY) AND VAMCO (ULYSSES)

Abstract. Flooding is a devastating natural disaster with global repercussions, affecting human life, crop production, and infrastructure. The increasing frequency and unpredictability of flood events, driven by climate change, highlight the urgent need for rapid and accurate flood mapping and damage assessment. This study explores the use of Google Earth Engine, a web-based platform that utilizes satellite imagery and geospatial data, for flood mapping and damage assessment. By incorporating localized datasets, such as region-specific land cover maps and population density information, the developed workflow provides a robust tool for assessing flood extent, identifying high-risk areas, and estimating the impact on cropland and urban centers. Key findings showed that Cagayan province presented the highest potential flood area, covering approximately 55,063 hectares. This province also had the largest population at risk, with around 39,440 individuals potentially exposed to the effects of flooding. Moreover, the cropland in Cagayan province experienced the most substantial impact, with around 91.26% being affected due to the swelling of the Cagayan River. Camarines Sur experienced severe devastation in urban areas, with about 269 hectares affected by flooding from the Bicol River. This study's findings contribute to a comprehensive understanding of flood impacts beyond the extent of flooding, facilitating informed decision-making, emergency response planning, and targeted interventions to mitigate the effects of floods on communities, agriculture, and urban areas. The approach presented here can be applied in other regions, supporting improved flood management and mitigation strategies for national.