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<p>Human-caused fires account for over 90% of wildfires in China, with drivers varying across forest regions. Identifying and comparing these drivers is critical for effective fire management and prevention. This study employs a binary logistic regression (BLR) model, utilizing verified human-caused fire data from 2000 to 2022, to analyze fire ignition drivers and map fire probabilities in three forested regions of China: northeastern (NEF), southeastern (SEF) and southwestern (SWF). Results indicate that fire weather and vegetation dominate NEF and SEF, whereas anthropogenic factors are more influential in SWF. In the NEF, regions with very high (VH) and high (H) fire risk are mainly concentrated along the eastern national border and at the junction of the Daxing’an and Xiaoxing’an Mountains, encompassing 33.33% of the forested area. In the SEF, VH and H fire risk zones are primarily situated in the far southern and northern parts, accounting for 35.54% of the forest area. In the SWF, VH and H fire risk areas are predominantly located in Yunnan Province, covering 26.43% of the forested region. Within regions, fire risk varies with vegetation type but aligns with similar levels of human activity. In NEF, high fire risk correlates with increased broadleaf and decreased mixed broadleaf-conifer cover. In SEF and SWF, high-risk areas exhibit reduced broadleaf presence, with SWF also showing less shrubland, emphasizing the critical role of fuel characteristics. Analysis of climate change scenarios revealed no significant trends, underscoring the multifaceted nature of fire ignition drivers.</p>

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Drivers of human-caused fire ignitions in China’s forest regions: a comparative analysis

  • 期刊论文

  • 发表日期：

    2026年7月22日

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  • Jianuo Li,
  • Bo Zhang,
  • Xiaoxue Xu,
  • Xianli Wang,
  • Meng Guo

摘要

Human-caused fires account for over 90% of wildfires in China, with drivers varying across forest regions. Identifying and comparing these drivers is critical for effective fire management and prevention. This study employs a binary logistic regression (BLR) model, utilizing verified human-caused fire data from 2000 to 2022, to analyze fire ignition drivers and map fire probabilities in three forested regions of China: northeastern (NEF), southeastern (SEF) and southwestern (SWF). Results indicate that fire weather and vegetation dominate NEF and SEF, whereas anthropogenic factors are more influential in SWF. In the NEF, regions with very high (VH) and high (H) fire risk are mainly concentrated along the eastern national border and at the junction of the Daxing’an and Xiaoxing’an Mountains, encompassing 33.33% of the forested area. In the SEF, VH and H fire risk zones are primarily situated in the far southern and northern parts, accounting for 35.54% of the forest area. In the SWF, VH and H fire risk areas are predominantly located in Yunnan Province, covering 26.43% of the forested region. Within regions, fire risk varies with vegetation type but aligns with similar levels of human activity. In NEF, high fire risk correlates with increased broadleaf and decreased mixed broadleaf-conifer cover. In SEF and SWF, high-risk areas exhibit reduced broadleaf presence, with SWF also showing less shrubland, emphasizing the critical role of fuel characteristics. Analysis of climate change scenarios revealed no significant trends, underscoring the multifaceted nature of fire ignition drivers.