The use of survival analysis methods to model the control time of forest fires in Ontario, Canada

This paper presents the results from employing survival analysis methods to model the probability distribution of the control time of forest fires. The Kaplan-Meier estimator, log-location-scale models, accelerated failure time models, and Cox proportional hazards (PH) models are described. Historical lightning and people-caused forest fire data from the Province of Ontario, Canada from 1989 through 2004 are employed to illustrate the use of the Cox PH model. We demonstrate how this methodology can be used to examine the association between the control time of a suppressed forest fire and local factors such as weather, vegetation and fuel moisture, as well as fire management variables including the response time between when a fire is reported and the initiation of suppression action. Significant covariates common to both the lightning and people-caused models were the size of the fire at the onset of initial attack, the Fine Fuel Moisture Code and the Initial Spread Index. The response time was also a significant predictor for the control time of lightning-caused fires, whereas the Drought Code and time of day of initial attack were significant for people-caused fires. Larger values of the covariates in these models were associated with larger survival probabilities.