Enhancing Flood Risk Management for Urban Coastal Communities Using LiDAR Applications

Abstract

Within urban centres, underground spaces such as storage areas, transportation corridors, basement car parks, public facilities, retail & office as well as private spaces (e.g., residential basements), present priority risk areas during flood events with respect to timely evacuation.  However, often the location, geometry and volume of these underground spaces is not well known.  Furthermore, these underground spaces are commonly not considered in flood prediction models for urban centres.  At the same time, communicating flood risks and enhancing emergency preparedness poses further challenges.  Thus emergency planners need engaging communication tools to increase community resilience and preparedness to flooding events. Low-cost Mobile Laser Scanning (MLS) and Airborne Laser Scanning (ALS) technologies as well as other remote sensing applications and street view imagery data are becoming increasingly available and affordable, providing high-resolution data for the urban environment.  The presented project focusses on gaining better knowledge of the location and internal geometry of underground spaces in urban centres by using low-cost MLS data. The presented project is developing efficient database approaches to handle the large data sets and to integrate the information into flood prediction models.  These models provide refined information on urban flood levels and flooding rates into the underground spaces, which in turn may be used as part of risk communication tools using low-cost virtual reality applications which provide an immersive experience of flood risk with the aim to better engage communities in emergency preparedness.  The comparison of rapid low-cost high-resolution terrestrial MLS with ALS data for an urban case study site in Belfast (Northern Ireland) highlights the advantages of the rapid low-cost MLS approaches and their use for the detection and surveying of urban underground spaces and the integration of these identified priority flood risks into urban flood models.  Incorporating the identified underground spaces provides more realistic inundation scenarios and enhanced information with regard to accessible evacuation routes to inform flood risk mitigation plans.