GIS based 3-D landscape visualization for promoting citizen's awareness of coastal hazard scenarios in flood prone tourism towns

- This research aims to develop a comprehensive geospatial method for visualizing GIS based 3-D landscape visualizations.
- This research has improved accuracy for the small geographic objects which can enhance a 3-D flooding visualization.
- The GIS-based 3-D landscape is visualized through three flood risk scenarios at the finest geographic scale.
- Web GIS application is developed to distribute out the GIS-based 3-D landscape visualization for the public.
- Thus, this research helps coastal residents improve lack of personal experience on the coastal hazards.

This research aims to develop a comprehensive geospatial method for visualizing GIS based 3-D landscape visualizations in flood prone tourism towns and geospatial web applications containing multimedia information. In particular, the research determines potentially vulnerable portions generated by the SLOSH and SLR models on a global scale, statistically computed by the historical shorelines and the most recent LiDAR-derived shoreline on a local scale. The flood risk areas selected in the global and local scales are assessed by a field trip survey and finally visualized through integration of GIS and remotely sensed LiDAR data. In order to visualize the GIS based 3-D landscape, the most accurate geographic objects are extracted through the LiDAR multiple return points flown in 2010. This research proposes improved accuracy for identifying the small geographic objects which can enhance a 3-D flooding visualization and then, the GIS based 3-D landscape is visualized based on three flood risk scenarios which have accurately georeferenced geographic information. Furthermore, this research develops a geospatial web application which allows the general public to communicate with coastal managers, or even policy makers, and which provides the chance to aid the public's participation in coastal management planning. Accordingly, the geospatial approaches used in this research not only help non-experts or policy makers have a better understanding of the coastal hazards through realistic visualization, but can also improve the public's spatial perception in the primary coastal tourism towns. Of significance, being able to predict future flooding portions is likely to become important as development of coastal areas continues. Thus, this research helps coastal residents improve lack of personal experience on the coastal hazards and communicate with the coastal management planners.