People living in the lower valley of the St. John River, New Brunswick, Canada, frequently experience flooding when the river overflows its banks during spring ice melt and rain. To better prepare the population of New Brunswick for extreme flooding, we developed a new flood prediction model that computes floodplain polygons before the flood occurs. This allows emergency managers to access the impact of the flood before it occurs and make the early decisions for evacuation of the population and flood rescue. This research shows that the use of GIS and LiDAR technologies combined with hydrological modelling can significantly improve the decision making and visualization of flood impact needed for emergency planning and flood rescue. Furthermore, the 3D GIS application we developed for modelling flooded buildings and infrastructure provides a better platform for modelling and visualizing flood situations than previously done in 2D maps. All parts of a building could be studied in detail in the event of flooding. This provides a better tool for analyzing and preparing for emergency measures. It also presents a photo-realistic situation that can easily be understood. Public administrators who may not be familiar with GIS analytical tools like Query Languages, can still understand technical discussions on flood analysis through the use of 3D models, which are close to reality.
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Gi4DM (Geoinformation for Disaster Management) Conference, 2012