甘肃省林火发生的驱动因子与火险区划  

Driving Factors of Forest Fire Occurrence and Fire Risk Zoning in Gansu Province

作　　者：逯真佳 罗永忠[1] 王旭虎 王康锋 马立鹏 张存焘 郭鹏 马婧 赵亮生 Lu Zhenjia;Luo Yongzhong;Wang Xuhu;Wang Kangfeng;Ma Lipeng;Zhang Cuntao;Guo Peng;Ma Jing;Zhao Liangsheng(College of Forestry,Gansu Agricultural University,Lanzhou 730070;Gansu Provincial Ecological Resources Monitoring Center,Lanzhou 730030)

机构地区：[1]甘肃农业大学林学院,兰州730070 [2]甘肃省生态资源监测中心,兰州730030

出　　处：《林业科学》2025年第3期63-71,共9页Scientia Silvae Sinicae

基　　金：甘肃省生态资源监测中心省级林业草原资源保护与发展基金·林业和草原火灾风险普查(701−03723041)。

摘　　要：【目的】探明甘肃省森林火灾发生的主要影响因素和全省林火危险性地理分区,为甘肃省林火预测提供理论依据并为森林防火提供重要参考。【方法】以甘肃省2000—2021年的历史火灾数据为基础,运用ArcGIS10.8提取地形、气象、植被、人为活动、社会经济等因素的空间信息,运用Logistic回归模型筛选甘肃省林火发生的主要驱动因子;使用标准化回归系数检验各驱动因子对林火发生的相对重要性,并利用ROC曲线对模型拟合效果进行检验;根据模型预测结果对林火发生概率进行等级区划。【结果】1)建立的空间Logistic森林火灾风险模型拟合效果较好,5个训练样本的AUC值都大于0.970,预测准确率为89.6%~90.6%,全样本的AUC值为0.972,预测准确率为89.1%。2)海拔、坡度、月均气温、植被覆盖度、到铁路距离与林火发生概率呈正相关,月均降水量、到公路距离、到居民点距离与林火发生概率呈负相关。3)标准化回归系数结果显示,各驱动因子对甘肃省林火发生的重要性表现为植被覆盖度(15.31)>月均气温(4.647)>坡度(1.055)>到铁路距离(1.015)>海拔(1.007)>到公路距离(0.985)>到居民点距离(0.852)>月均降水量(0.808)。4)依据林火发生概率等间距地将甘肃省森林火险划分为5个等级:极低火险区(0~0.2)、低火险区(0.2~0.4)、中火险区(0.4~0.6)、高火险区(0.6~0.8)和极高火险区(0.8~1),其对应的森林面积分别为462640、850160、1611550、1715680和705050 hm2。【结论】植被覆盖度、月均气温、坡度、到铁路距离、海拔、到公路距离、到居民点距离、月均降水量为甘肃省林火发生的主要驱动因子。林火发生概率总体呈东南高、西北低的空间分布特征,其中极高火险区主要分布在甘南藏族自治州、临夏回族自治州、兰州以及陇南部分地区,高火险区主要分布在陇南和天水东南部、平凉西部、兰州和临夏回族自治州部分�【Objective】The objective of this study is to explore the main influencing factors of forest fires in Gansu Province and the geographical division of forest fire risk in the Province.【Method】Based on the historical fire data of Gansu Province from 2000 to 2021,ArcGIS 10.8 was used to extract the spatial information of topography,meteorology,vegetation,human activities,and socio-economic factors,and the Logistic regression model was used to determine the main driving factors of forest fires in Gansu Province.The standardized regression coefficient was used to test the relative importance of each driving factor to the occurrence of forest fires,and the ROC curve was used to test the fitting effect of the model.According to the prediction results of the model,the probability of forest fire occurrence was classified into hierarchical regions.【Result】1)The spatial logistic forest fire risk model established was well fitted.The AUC value of the five training samples was all greater than 0.970,and the prediction accuracy was between 89.6%-90.6%,and the AUC value of the whole sample was 0.972,and the prediction accuracy was 89.1%,indicating that the model was suitable for the predicting of forest fire occurrence in Gansu Province.2)Elevation,slope,mean monthly temperature,vegetation coverage,and distance to the railway were positively correlated with the probability of forest fires,while mean monthly precipitation,distance to the highway,and distance to the settlement were negatively correlated with the probability of forest fires.3)According to the standardized regression coefficients,the importance of each driving factor to the occurrence of forest fires in Gansu Province was ranked as follows:vegetation coverage(15.31)>mean monthly temperature(1.647)>slope(1.055)>distance to the railway(1.015)>elevation(1.007)>distance to the highway(0.985)>distance to the settlement(0.852)>mean monthly precipitation(0.808).4)According to the probability of forest fires,the forest fire risk in Gansu Province was divided int

关 键 词：甘肃省 LOGISTIC回归模型 自然因素 人为因素 火险区划 

分 类 号：S762.2[农业科学—森林保护学]