# Bushfire models

September 7, 2020 — August 19, 2020

geometry

how do science

machine learning

physics

statmech

straya

Press: Silicon valley wildfire spotting.

bushfire.io aggregates bushfire information.

Wildfire & Emergency Management

## 1 References

Dabrowski, Pagendam, Hilton, et al. 2023. “Bayesian Physics Informed Neural Networks for Data Assimilation and Spatio-Temporal Modelling of Wildfires.”

*Spatial Statistics*.
Hilton, Sullivan, Swedosh, et al. 2018. “Incorporating Convective Feedback in Wildfire Simulations Using Pyrogenic Potential.”

*Environmental Modelling & Software*.
Mandel, Beezley, Coen, et al. 2009. “Data Assimilation for Wildland Fires.”

*IEEE Control Systems Magazine*.
Rochoux, Emery, Ricci, et al. 2015. “Towards Predictive Data-Driven Simulations of Wildfire Spread – Part II: Ensemble Kalman Filter for the State Estimation of a Front-Tracking Simulator of Wildfire Spread.”

*Natural Hazards and Earth System Sciences*.
Rochoux, Ricci, Lucor, et al. 2014. “Towards Predictive Data-Driven Simulations of Wildfire Spread – Part I: Reduced-Cost Ensemble Kalman Filter Based on a Polynomial Chaos Surrogate Model for Parameter Estimation.”

*Natural Hazards and Earth System Sciences*.
Rothermel. 1972.

*A Mathematical Model for Predicting Fire Spread in Wildland Fuels*.