Review and perspectives of digital twin systems for wildland fire management

Abstract

Abstract

Effective wildland fire management requires real-time access to comprehensive and distilled information from different data sources. The Digital Twin technology becomes a promising tool in optimizing the processes of wildfire prevention, monitoring, disaster response, and post-fire recovery. This review examines the potential utility of Digital Twin in wildfire management and aims to inspire further exploration and experimentation by researchers and practitioners in the fields of environment, forestry, fire ecology, and firefighting services. By creating virtual replicas of wildfire in the physical world, a Digital Twin platform facilitates data integration from multiple sources, such as remote sensing, weather forecasting, and ground-based sensors, providing a holistic view of emergency response and decision-making. Furthermore, Digital Twin can support simulation-based training and scenario testing for prescribed fire planning and firefighting to improve preparedness and response to evacuation and rescue. Successful applications of Digital Twin in wildfire management require horizontal collaboration among researchers, practitioners, and stakeholders, as well as enhanced resource sharing and data exchange. This review seeks a deeper understanding of future wildland fire management from a technological perspective and inspiration of future research and implementation. Further research should focus on refining and validating Digital Twin models and the integration into existing fire management operations, and then demonstrating them in real wildland fires.

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Funding

The Hong Kong Polytechnic University

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