Flood Impact Analysis of Typhoon Yagi in Vietnam

Abstract

On September 7, 2024, Typhoon Yagi struck Northern Vietnam, severely affecting the coastal city of Hai Phong and neighboring Quang Ninh Province. The typhoon caused extensive flooding, significant infrastructure damage, and substantial economic and human losses. This research integrates remote sensing and GIS-based spatial analysis to evaluate the flood impacts and predict flood-prone areas. Sentinel-1 satellite data, processed using the Sentinel Application Platform (SNAP), was employed to extract flood-affected regions through pre- and post-crisis imagery differencing. Flood extent was identified by subtracting pre-crisis from post-crisis imagery, isolating inundated areas. Additionally, a predictive flood risk analysis was conducted using the weighted sum tool in ArcGIS Pro, incorporating seven key variables: DEM, terrain slope, drainage density, LULC derived from Sentinel-2 data, monthly rainfall data for September 2024 from PERSIANN-CCS, distance to roads, and distance to rivers. Each raster variable was reclassified into a standardized scale ranging from 1 (very low risk) to 5 (very high risk) to ensure comparability, followed by the assignment of weighted contributions to each variable based on its influence on flooding. The resulting analysis produced a flood risk map for the study area, highlighting the interplay of topography, hydrology, and infrastructure in flood dynamics. These findings offer critical insights for flood risk assessment, disaster response, and the development of mitigation strategies tailored to Hai Phong and Quang Ninh.