Flood disaster management: integrating machine learning and geospatial data analysis for optimal assembly areas in Bartın river Basin, Turkiye

This study focuses on the identification of optimal safe assembly areas in the case of urban flash floods using Geographic Information System (GIS) and machine learning techniques. Floods are among the most devastating natural disasters worldwide, necessitating effective disaster management strategies to mitigate their impacts. The primary obstacle in developing a successful evacuation strategy during flood management preparedness is locating “safe zones” that are vulnerable to flooding, particularly in heavily populated urban areas (Sahmutoglu et al. 2023). Safe zones are defined as areas that are safer than their surroundings and have a lower flood risk (Bubeck et al. 2012). Early identification of these locations might help lessen the effects of floods by serving as temporary shelters and assembly places, where people can congregate before being taken to safe areas by search and rescue teams.