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Forest and Grassland Resources Research ›› 2023›› Issue (5): 48-55.doi: 10.13466/j.cnki.lczyyj.2023.05.006

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Study on Spatio-Temporal Distribution Characteristics and Susceptibility Analysis of Forest Fire

ZHANG Guoli(), CI Xuelun, YANG Xueqing(), JIANG Chunying, SUN Zhichao, MENG Haiding   

  1. Academy of Forestry Inventory and Planning,National Forestry and Grassland Administration,Beijing 100714,China
  • Received:2023-07-24 Revised:2023-08-29 Online:2023-10-28 Published:2023-12-20

Abstract:

The situation of forest fire prevention in China is severe.Analyzing and studying the spatial-temporal characteristics and susceptibility of forest fire can provide scientific basis for forest fire prevention.Based on the data of the first national forest and grassland fire risk survey,the temporal and spatial distribution characteristics of forest fire in China's 31 provinces during 2011—2020 were analyzed,and the forest fire susceptibility model in China's 31 provinces was established by using the random forest algorithm through the construction of forest fire driving factors such as fuel,meteorological conditions and terrain.The results were as follows:1)The interannual change of the frequency and burned areas of forest fire in 31 provinces showed a downward trend from 2011 to 2020.The difference was significant in different geographical regions.Forest fires in winter and spring accounted for 85.48%.2)The fuel load per unit area is the most important driving factor of forest fire susceptibility,followed by monthly mean temperature,monthly minimum relative humidity and monthly mean precipitation.3)Receiver operating characteristic curve(ROC),area under curve(AUC)and accuracy(ACC)were used to analyze the accuracy of the prediction model.The values of AUC and ACC were 0.87 and 0.84,respectively,indicating a high accuracy of the susceptibility model.4)The forest fire susceptibility in China's 31 provinces had obvious regional differences.Northeast,Southwest and East China were dominated by high and medium-high susceptibility levels,Central China and South China were dominated by medium-low susceptibility levels,and North and Northwest China were dominated by low and very low susceptibility levels.

Key words: forest fire, random forest algorithm, spatial-temporal characteristic, susceptibility analysis

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