LAUSR

Forest fire forecasting is a key component of effective and science⁃based forest management and has been comprehensively addressed in the scientific literature. The logistic regression (LR) technique has been used in forest fire prediction models. However, some scholars have recently reported that the technique does not adequately consider the spatial correlation and heterogeneity of fire impact factors, which results in poorly fitting models. In contrast, geographically weighted logistic regression (GWR) models consider the spatial correlation of model variables, which improves the model′s goodness of fit. In order to explore the applicability of the GWLR model in Fujian forest fire forecasting, the present study htt p:/ /w ww .ec olo gic a.c n http: / / www.ecologica.cn used both the LR and GWLR methods to establish forecast model for forest fires and meteorological factors in Fujian Province, and the model fitting ability of two models were compared. Based on the forest fire and meteorological data for Fujian from 2000 to 2005, the original dataset was randomly divided into training (60%) and validation (40%) samples, with five replications and five sample groups, and predictors that were significant (ɑ = 0.05) for at least three of the five sample groups were included in the final models. The goodness of fit, residual error, spatial autocorrelation, and prediction accuracy of the GWLR model were all better than those of the LR model, and the GWLR comprehensively explained the spatial heterogeneity of model variables and helped to improve the prediction accuracy of the model. The study also verified the suitability of the GWLR model on the forest fire forecasting in Fujian area. In addition, the results also indicated that the occurrence of Fujian forest fires is significantly affected by eight parameters, including minimum and maximum surface temperature, daily average wind speed, daily precipitation, highest station pressure, hours of sunshine, daily maximum temperature, and daily minimum relative humidity. Therefore, the GWLR model may provide a new technique for the prediction of forest fires in Fujian Province.