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VRFIS: An Immersive Framework for Real-Time Flood Monitoring, Visualization, and Interactive Environmental Analysis

VRFIS: An Immersive Framework for Real-Time Flood Monitoring, Visualization, and Interactive Environmental Analysis

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Authors

Uditha Mudiyanselage, Jerry Mount, Ramteja Sajja, Yusuf Sermet, Ibrahim Demir

Abstract

The rapid evolution of Mixed Reality (MR) technologies, particularly Virtual Reality (VR), offers powerful new means of visualizing and interacting with geographic and environmental data. This paper presents Virtual Reality Flood Information System (VRFIS), an immersive information platform developed using Unreal Engine 5 and Google Photo Realistic 3D Tiles to enable real-time exploration of high-resolution geospatial datasets across the United States. VRFIS integrates photorealistic terrain rendering, dynamic environmental simulation, and multimodal interaction within a fully immersive 3D environment, allowing users to visualize, query, and interpret complex environmental phenomena with unprecedented realism and spatial context. By coupling high-fidelity visualization with live data streams from authoritative sources such as USGS and NOAA, the system delivers an intuitive decision-support and educational tool for environmental science, hydrology, urban planning, and geography education. The results demonstrate how next-generation virtual reality environments, exemplified by VRFIS, can enhance spatial awareness, promote experiential learning, and improve data-driven decision-making in environmental and geospatial domains.

DOI

https://doi.org/10.31223/X5KF4P

Subjects

Environmental Engineering, Environmental Monitoring, Graphics and Human Computer Interfaces, Hydrology

Keywords

digital twin, Environmental Decision Support, hydrology, virtual reality, Real-Time Environmental Data, Unreal Engine, geospatial visualization

Dates

Published: 2025-12-31 16:09

Last Updated: 2025-12-31 16:09

License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
None

Data Availability (Reason not available):
All data produced and analyzed in the manuscript are readily available and presented in the manuscript.

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