Problem
Research questions and friction points this paper is trying to address.
Flood Simulation
Urban Environment
Disaster Response
Submerse: Visualizing Storm Surge Flooding Simulations in Immersive Display Ecologies
🤖 AI Summary
To address the low efficiency in urban flood situation awareness and emergency decision-making, this paper proposes an end-to-end immersive storm surge inundation visualization framework. Methodologically, it integrates high-precision geospatial data to construct a real-scale 3D urban scene and introduces an adaptive quadtree-based dynamic mesh discretization scheme to efficiently represent large-scale flood simulation outputs. The framework further incorporates Level-of-Detail (LOD) rendering, synthesized water-wave animation, point-of-interest–driven automatic camera navigation, and augmented reality (AR)-enhanced focus-context interaction for real-time, multi-perspective, and interactive flood process visualization. Evaluated on the Stony Brook Reality Deck platform using a Hurricane Sandy scenario for New York City, the system received strong endorsement from emergency managers and domain experts, demonstrating significant improvements in spatial comprehension of flood dynamics and timeliness of response decisions.
📝 Abstract
We present Submerse, an end-to-end framework for visualizing flooding scenarios on large and immersive display ecologies. Specifically, we reconstruct a surface mesh from input flood simulation data and generate a to-scale 3D virtual scene by incorporating geographical data such as terrain, textures, buildings, and additional scene objects. To optimize computation and memory performance for large simulation datasets, we discretize the data on an adaptive grid using dynamic quadtrees and support level-of-detail based rendering. Moreover, to provide a perception of flooding direction for a time instance, we animate the surface mesh by synthesizing water waves. As interaction is key for effective decision-making and analysis, we introduce two novel techniques for flood visualization in immersive systems: (1) an automatic scene-navigation method using optimal camera viewpoints generated for marked points-of-interest based on the display layout, and (2) an AR-based focus+context technique using an aux display system. Submerse is developed in collaboration between computer scientists and atmospheric scientists. We evaluate the effectiveness of our system and application by conducting workshops with emergency managers, domain experts, and concerned stakeholders in the Stony Brook Reality Deck, an immersive gigapixel facility, to visualize a superstorm flooding scenario in New York City.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Submerse
Augmented Reality
Automatic Viewpoint Guidance
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