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Evacuation routing is one of the fundamental instruments for flood risk mitigation. In this study, features extracted from LiDAR data are used to create dynamic network composed of buildings and roads. Flood prone areas identified through flood models from Phil-Lidar 1 Project are considered by Capacity Aware Shortest Path Evacuation Routing algorithm to determine optimal routes. Road capacity and location of building features were also considered. Uncertainties among possible paths taken are evaluated through Decision Theory. Specific DT technique implemented to generate alternative routes for the possibility of detours is the Analytic Hierarchy Process. This study can help city governance in terms of planning and disaster risk reduction management.

GIS-based Evacuation Routing using Capacity Aware Shortest Path Evacuation Routing Algorithm and Analytic Hierarchy Process for Flood Prone Communities