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Wildfire spread simulation plays important roles in wildfire management. Existing wildfire simulations are largely decoupled from real wildfires by making little usage of real time data. In this paper, a dynamic data driven application system is presented to incorporate the real time data into the simulation model, thus to improve the simulation results. The developed dynamic data driven application system is based on the DEVS-FIRE model and employs the particle filtering algorithm to estimate the state of fire spread. We describe the overall structure of the dynamic data driven application system for wildfire spread simulation. The major issues and computation models of this work are presented and experiment results are provided.