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内蒙古大兴安岭林火驱动因素识别及预测模型

周庆 张恒 张秋良 赵鹏武 诺敏 王嘉夫 高健 赵梦玉 杨泽华

北京林业大学学报2024,Vol.46Issue(12):114-125,12.
北京林业大学学报2024,Vol.46Issue(12):114-125,12.DOI:10.12171/j.1000-1522.20230161

内蒙古大兴安岭林火驱动因素识别及预测模型

Identification and prediction models of driving factors for forest fires in Daxing'an Mountains of Inner Mongolia,northern China

周庆 1张恒 2张秋良 2赵鹏武 3诺敏 4王嘉夫 5高健 6赵梦玉 7杨泽华7

作者信息

  • 1. 内蒙古农业大学林学院,内蒙古 呼和浩特 010019||内蒙古大兴安岭森林生态系统国家野外科学观测研究站,内蒙古 根河 022350||南京大学国际地球系统科学研究所,江苏 南京 210023||江苏省地理信息技术重点实验室,江苏 南京 210023
  • 2. 内蒙古农业大学林学院,内蒙古 呼和浩特 010019||内蒙古大兴安岭森林生态系统国家野外科学观测研究站,内蒙古 根河 022350
  • 3. 内蒙古农业大学林学院,内蒙古 呼和浩特 010019
  • 4. 克一河森工公司,内蒙古 呼伦贝尔 021000
  • 5. 内蒙古大兴安岭林业生态研究院,内蒙古 牙克石 022150
  • 6. 北京市园林绿化局森林防火事务中心,北京 102100
  • 7. 内蒙古自治区呼和浩特市气象局,内蒙古 呼和浩特 010020
  • 折叠

摘要

Abstract

[Objective]This paper aims to select and validate suitable forest fire prediction models for the study area,identify key driving factors of fire occurrence,and map fire risk zoning,then providing scientific basis and decision support for forest fire prevention and management.[Method]Using historical fire data from 1981 to 2020 and integrating multi-source data(meteorological conditions,topography,vegetation,human activities,and socio-economic factors),the applicability of four machine learning methods in predicting forest fires in the Daxing'an Mountains of Inner Mongolia of northern China was compared.Based on the significant factors influencing fire occurrence,maps of fire occurrence probability and fire risk zoning were generated.[Result](1)The boosted regression tree model(BRT)showed an area under the curve(AUC)value of 0.967,and the random forest model(RF)achieved an AUC of 0.947,both demonstrating excellent predictive performance.The predictive accuracy of the Logistic regression model(LR)and the Gompit regression model(GR)was slightly lower than former two models,but still met the basic predictive requirements for the study area,with AUC values of 0.852 and 0.851,respectively.(2)Meteorological factors,such as diurnal temperature range and daily minimum relative humidity,were the dominant factors influencing forest fires in the Daxing'an Mountains of Inner Mongolia.Elevation also ranked high in the relative importance of driving factors.Human activities and socio-economic factors,such as distance to roads,distance to fire lookout towers,and per capita GDP,also had some influence on fire occurrence.(3)Large areas of medium to high fire risk were present in the eastern and southeastern parts of the Daxing'an Mountains of Inner Mongolia,while the northern China-Russia border and the southwestern China-Mongolia border also exhibited elevated fire risk.Factors such as average temperature and average surface temperature during fire prevention period in autumn of previous year influenced forest fire occurrences in the following year.[Conclusion]Among the four models compared,the BRT was identified as the most suitable one for predicting forest fire occurrence in the Daxing'an Mountains of Inner Mongolia.Meteorological factors and elevation significantly influence fire occurrence,while human activities and socio-economic factors also have a certain impact on the occurrence of fires.The high and medium fire risk areas are primarily concentrated in the eastern and southeastern parts of the study area,with some fire risks presenting in the northern and southwestern regions.

关键词

大兴安岭/模型比较/林火发生概率/林火驱动因素/火险区划

Key words

Daxing'an Mountains/model comparison/probability of forest fires/driving factors of forest fires/fire risk zoning

分类

农业科技

引用本文复制引用

周庆,张恒,张秋良,赵鹏武,诺敏,王嘉夫,高健,赵梦玉,杨泽华..内蒙古大兴安岭林火驱动因素识别及预测模型[J].北京林业大学学报,2024,46(12):114-125,12.

基金项目

国家自然科学基金项目(32060344),内蒙古自治区高等学校青年科技英才支持计划(NJYT24042),内蒙古自治区科技计划(2022YFSH0077),中央高校基本科研业务费专项(BFUKF202217),内蒙古自治区科技计划(2023KYPT0001). (32060344)

北京林业大学学报

OA北大核心CSTPCD

1000-1522

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