STATISTICAL PREVENTION MODELS FOR WILDFIRE SUPPRESSION
Some of the most devastating natural disasters in the history of the United States have been caused by wildfires.
Environmental statistical research models fire occurrence as a marked spatial-temporal point process whose
conditional rate depends not only on the record of previous fires, but on other covariates including environmental
factors such as temperature, altitude, humidity, precipitation, vegetation, and soil characteristics. Using advanced
statistical research, investigators are constructing quantitative predictions of local fire hazard accompanied by
estimates of uncertainties in these predictions. In particular, research in the Los Angeles basin will integrate these
predicted hazards into detailed, regularly updated maps of risk that are available to the public. The strategy is to
exploit local trends in fire occurrence and the relationships between the incidence of fires and other environmental
factors. This basic research could have important public policy implications relating to more aggressive fire
suppression and prescribed burning.