title: [Forest lighting fire forecasting for Daxing'anling Mountains based on MAXENT model].
abstract: Daxing'anling Mountains is one of the areas with the highest occurrence of forest lighting fire in Heilongjiang Province, and developing a lightning fire forecast model to accurately predict the forest fires in this area is of importance. Based on the data of forest lightning fires and environment variables, the MAXENT model was used to predict the lightning fire in Daxing' anling region. Firstly, we studied the collinear diagnostic of each environment variable, evaluated the importance of the environmental variables using training gain and the Jackknife method, and then evaluated the prediction accuracy of the MAXENT model using the max Kappa value and the AUC value. The results showed that the variance inflation factor (VIF) values of lightning energy and neutralized charge were 5.012 and 6.230, respectively. They were collinear with the other variables, so the model could not be used for training. Daily rainfall, the number of cloud-to-ground lightning, and current intensity of cloud-to-ground lightning were the three most important factors affecting the lightning fires in the forest, while the daily average wind speed and the slope was of less importance. With the increase of the proportion of test data, the max Kappa and AUC values were increased. The max Kappa values were above 0.75 and the average value was 0.772, while all of the AUC values were above 0.5 and the average value was 0. 859. With a moderate level of prediction accuracy being achieved, the MAXENT model could be used to predict forest lightning fire in Daxing'anling Mountains.
authors.forename: Yu
authors.initials: Y
authors.lastname: Sun
authors.forename: Ming-Chang
authors.initials: MC
authors.lastname: Shi
authors.forename: Huan
authors.initials: H
authors.lastname: Peng
authors.forename: Pei-Lin
authors.initials: PL
authors.lastname: Zhu
authors.forename: Si-Lin
authors.initials: SL
authors.lastname: Liu
authors.forename: Shi-Lei
authors.initials: SL
authors.lastname: Wu
authors.forename: Cheng
authors.initials: C
authors.lastname: He
authors.forename: Feng
authors.initials: F
authors.lastname: Chen
mesh_terms: D005390:Fires; D005544:Forecasting; D065928:Forests; D008030:Lightning; D008962:Models, Theoretical; D014197:Trees; D014919:Wind