An efficient flood dynamic visualization approach based on 3D printing and augmented reality

Flood visualization is an effective and intuitive tool for representing flood information from abstract spatiotemporal data.With the growing demand for flood disaster visualizations and mitigation,augmented flood visualizations that support decision makers’perspectives are needed,which can be enhanced by emerging augmented reality(AR)and 3D printing technologies.This paper proposes an innovative flood AR visualization method based on a 3D-printed terrain model and investigates essential techniques,such as the suitable size calculation of the terrain models,the adaptive processing of flood data,and hybridizing virtual flood and terrain models.A prototype experimental system(PES)based on the proposed method and a comparison experimental system(CES)based on a virtual terrain are developed to conduct comparative experiments,which combine the system performance and questionnaire method to evaluate the efficiency and usability of the proposed method.The statistical results indicate that the method is useful for assisting participants in understanding the flood hazard and providing a more intuitive and realistic visual experience compared with that of the traditional AR flood visualization method.The frame rate is stable at 60 frames per second(FPS),which means that the proposed method is more efficient than the traditional AR flood visualization method.

Tunnel vision optimization method for VR flood scenes based on Gaussian blur

The visualization of flood disasters in virtual reality(VR)scenes is useful for the representation and sharing of disaster knowledge and can effectively improve users’cognitive efficiency in comprehending disaster information.However,the existing VR methods of visualizing flood disaster scenes have some shortcomings,such as low rendering efficiency and poor user experience.In this paper,a tunnel vision optimization method for VR flood scenes based on Gaussian blur is proposed.The key techniques are studied,such as region of interest(ROI)calculation and tunnel vision optimization considering the characteristics of the human visual system.A prototype system has been developed and used to carry out an experimental case analysis.The experimental results show that the number of triangles drawn in a flood VR scene is reduced by approximately 30%–40%using this method and that the average frame rate is stable at approximately 90 frames per second(fps),significantly improving the efficiency of scene rendering and reducing motion sickness.