A logistic model for predicting daily people-caused forest fire occurrence in Ontario

Abstract

The authors describe the development of a procedure that can be used to predict daily people-caused forest fire occurrence in the Northern Region of the province of Ontario. The procedure is based on the use of logistic regression analysis techniques to predict the probability of a fire day and the assumption that a Poisson probability distribution can be used to model daily people-caused forest fire occurrence. The results of a field test that was conducted during the summer portion of the 1984 fire season indicate the procedure works well during relatively wet periods.