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 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