FIRETWIN: Digital Twin Advancing Multi-Modal Sensing, Interactive Analytics for Wildfire Response

2025/09/13 by Mayamin Hamid Raha, Alireza Tavakkoli, Raha, Mayamin Hamid +11
Engineering · Environmental Science · #FOS: Computer and information sciences #Fire Detection and Safety Systems #Fire effects on ecosystems #Human-Computer Interaction (cs.HC) #Remote Sensing and LiDAR Applications

paper · pdf · doi:10.48550/arxiv.2510.18879

openalex publication_date 2025/09/13 · openalex created_date 2025/10/24 · openalex updated_date 2026/07/28

Abstract

Current wildfire management systems lack integrated virtual environments that combine historical data with immersive digital representations, hindering deep analysis and effective decision making. This paper introduces FIRETWIN, a cyber-physical Digital Twin (DT) designed to bridge complex ecological data and operationally relevant, high-fidelity visualizations for actionable incident response. FIRETWIN generates a dynamic 3D virtual globe that visualizes evolving fire behavior in real time, driven by output from physics-based fire models. The system supports multimodal perspectives, including satellite and drone viewpoints comparable to NOAA GOES-18 imagery - enabling comprehensive scenario analysis. Users interact with the environment to assess current fire conditions, anticipate progression, and evaluate available resources. Leveraging Google Maps, Unreal Engine, and pre-generated outputs from the CAWFE coupled weather-wildland fire model, we reconstruct the spread of the 2014 King Fire in California Eldorado National Forest. Procedural forest generation and particle-level fire control enable a level of realism and interactivity not possible in field training.

Citations

• Seeing Heat with Color -- RGB-Only Wildfire Temperature Inference from SAM-Guided Multimodal Distillation using Radiometric Ground Truth
• FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management
• Role of flow topology in wind-driven wildfire propagation
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