考虑自然因素和人类活动影响的川西高原林火风险区划及模型构建

Forest Fire Risk Zoning and Modeling in the Western Sichuan Plateau Integrating Natural Factors and Human Activities

  • 摘要: 为明确川西高原林火发生的关键驱动因子并合理建立火险区划体系,通过多源数据融合与模型构建,揭示区域林火空间分布规律,为火灾精准防控及生态安全屏障保护提供科技支撑。本文基于2003—2022年MOD14A1卫星火点数据,综合气象、地形、植被及人为活动等13个驱动因子,构建二项Logistic回归模型(模型AUC=0.8,预测准确率76.1%),并进行火险等级区划。研究表明:(1)川西高原显著影响林火发生的因子有7个,分别是距居民点距离、距公路距离、海拔、月平均降水量、月平均地表温度、月太阳净短波辐射和月平均相对湿度;(2)低、中、高火险区面积占比分别为67.8%、18.5%、13.4%,其中高火险区集中分布于九龙县、康定市、雅江县等甘孜州南部与阿坝州北部若尔盖县等地;(3)气象要素(低温、低湿、少雨和强辐射等)是林火主控因子,叠加人类活动密集特征(距居民点、公路6 km内)进一步加剧火灾风险;(4)基于驱动因子量化与空间概率建模的火险区划方法可为川西高原林火动态监测与分级管理提供科学依据。

     

    Abstract: To identify the key drivers of forest fire occurrence in the West Sichuan Plateau and establish a scientific fire risk zoning system, multi-source data and constructed models were integrated to reveal the spatial distribution patterns of regional forest fires, providing scientific and technological support for precise fire prevention and ecological security barrier protection. Based on MOD14A1 satellite fire point data from 2003 to 2022 and 13 driving factors including meteorology, topography, vegetation, and human activity, a binary logistic regression model was constructed (model AUC=0.8, prediction accuracy 76.1%) for fire risk zoning. The results show that: (1) Seven factors significantly influence fire occurrence in the West Sichuan Plateau: distance to settlements, distance to roads, elevation, monthly average precipitation, monthly average land surface temperature, monthly average net shortwave solar radiation, and monthly average relative humidity. (2) The area proportions of low, medium, and high fire risk zones are 67.8%, 18.5%, and 13.4%, respectively, with high-risk areas concentrated in southern Ganzi Prefecture (Jiulong County, Kangding City, Yajiang County) and northern Aba Prefecture (Zoigê County). (3) Meteorological factors (low temperature, low humidity, low precipitation, and strong radiation) are the dominant drivers of forest fires. The combination with intensive human activity characteristics (within 6 km of settlements and roads) further exacerbates fire risk. (4) The fire risk zoning method based on driver quantification and spatial probability modeling can provide a scientific basis for dynamic monitoring and hierarchical management of forest fires in the Western Sichuan Plateau.

     

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