Integrative Biology Journals

JOURNAL OF FORESTRY RESEARCH ›› 2025, Vol. 36 ›› Issue (1): 1-.DOI: 10.1007/s11676-024-01810-x

• Review Article •    

Review and perspectives of digital twin systems for wildland fire management

Yizhou Li1, Tianhang Zhang1, Yifei Ding1, Rahul Wadhwani1, Xinyan Huang1   

  1. 1Research Centre for Smart Urban Resilience and Firefighting, Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, ZS832, 181 Chatham Road South, Kowloon 999077, Hong Kong, People’s Republic of China
  • Received:2024-08-26 Accepted:2024-10-05 Online:2024-12-14 Published:2025-01-01
  • Supported by:
    This work is funded by the National Natural Science Foundation of China (NSFC No. 52322610) and Hong Kong Research Grants Council Theme-based Research Scheme (T22-505/19-N).

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.

Key words: Decision support, Wildfire mitigation, Fire modeling, Emergency response, WUI fire safety, Smart f irefighting