基于Logistic回归模型的大兴安岭林火预测研究

Prediction of Forest Fire Occurrence in Daxing′an Mountains Based on Logistic Regression Model

基于2000—2016年卫星林火数据,选取气象、地形、植被及可燃物、人为活动等因素作为林火预测变量,采用Logistic回归模型对林火发生的主要驱动因子进行分析,并建立大兴安岭地区林火发生预测模型。模型结果表明:Logistic回归模型的预测精度较高为80.6%,模型的拟合度也高达0.868。火险等级总体呈南高北低、东高西低的地理分布,其中高火险区主要集中在南部;残差分析结果显示南部和东南部存在大面积低估区,表明模型对这些地区的预测能力不高。

Based on the satellite data of forest fire from 2000 to 2016,this study selected such factors as meteorology,topography,vegetation,fuels,human activities and other factors as forest fire prediction variables,used Logistic regression model to analyze the main driving factors of forest fire occurrence,and established a forest fire prediction model in Daxing′an mountains.The results showed that the Logistic regression model has a high prediction accuracy of 80.6%,and the goodness-of -fit of the model is 0.868.In general,the fire risk is high in the south and east but low in the north and west.The residual analysis results showed that there large areas were underestimated in the south and southeast,indicating that the prediction ability of the model for these areas was low.