Prescribed Fire Simulation with Dynamic Ignitions Using Data from UAS-based Sensing

ABSTRACT

Prescribed fire is an important tool for wildfire management and land management. Simulation of prescribed fires holds great potential in supporting planning of prescribed burn events. This paper presents a simulation-based study of a prescribed fire using data from Unmanned Aircraft System (UAS)-based sensing. A systematic approach for modelling and simulating prescribed fires with dynamic ignitions is developed. The developed approach is applied to a real prescribed fire where a UAS was used to monitor and collect data about the fire. The dynamic ignition process from multiple fire setting teams is specified, and simulation results are compared to real measurement data from UAS-based sensing. The results demonstrate the effectiveness of the developed modelling approach as well as the utility of using UAS-based fire measurements for prescribed fire simulations.

KEYWORDS:

• Prescribed fire
• Wildfire
• Prescribed fire simulation
• Unmanned aircraft system
• Sensing

Acknowledgments

The authors would like to thank Sheena Parsons, Dr. Dean Kettle, Bruce Johanning and Vaughn Salisbury from Kansas Biological Survey for their help with fire experiments and UAS data collection.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the US National Institute of Food and Agriculture (NIFA) under grant number 2019-67021-29011, 2019-67021-28992, and 2019-67021-28993.