Modeling of Wildfire Digital Twin: Research Progress in Detection, Simulation, and Prediction Techniques

Abstract

Wildfires occur frequently in various regions of the world, causing serious damage to natural and human resources. Traditional wildfire prevention and management methods are often hampered by monitoring challenges and low efficiency. Digital twin technology, as a highly integrated virtual simulation model, shows great potential in wildfire management and prevention. At the same time, the virtual–reality combination of digital twin technology can provide new solutions for wildfire management. This paper summarizes the key technologies required to establish a wildfire digital twin system, focusing on the technical requirements and research progress in fire detection, simulation, and prediction. This paper also proposes the wildfire digital twin (WFDT) model, which integrates real-time data and computational simulations to replicate and predict wildfire behavior. The synthesis of these techniques within the framework of a digital twin offers a comprehensive approach to wildfire management, providing critical insights for decision-makers to mitigate risks and improve emergency response strategies.