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生态学杂志 ›› 2024, Vol. 43 ›› Issue (1): 282-289.doi: 10.13292/j.1000-4890.202401.017

• 技术与方法 • 上一篇    下一篇

贵州省林火发生驱动因子及预测模型

张运林1,2,田玲玲1,丁波1,2,张延威1,2,刘讯1,2,武燕1,2*


  

  1. 1贵州师范学院生物科学学院, 贵阳 550018; 2贵州省高等学校林火生态与管理重点实验室, 贵阳 550018)
  • 出版日期:2024-01-10 发布日期:2024-01-11

Driving factors and prediction model of forest fire in Guizhou Province.

ZHANG Yunlin1,2, TIAN Lingling1, DING Bo1,2, ZHANG Yanwei1,2, LIU Xun1,2, WU Yan1,2*#br#

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  1. (1School of Biological Sciences, Guizhou Education University, Guiyang 550018, China; 2Key Laboratory of Forest Fire Ecology and Management of Guizhou Province, Guizhou Education University, Guiyang 550018, China).

  • Online:2024-01-10 Published:2024-01-11

摘要: 中国西南林区火源复杂,人为干扰大,多为喀斯特地貌和农林交错区,山形复杂,是中国林火发生的重灾区。分析该区域林火发生驱动因子,并进行火险区划,对于该地区合理的林火管理工作具有重要意义。本研究以西南地区的贵州省为对象,基于2011—2020年的森林火点数据、地理空间数据、气象数据、植被数据和人类活动数据等,利用ArcGIS 10.7的空间分析和R Studio等软件分析贵州省近10年林火分布时空格局,得到林火发生的驱动因子和概率预测模型,分别绘制春夏秋冬4个季节的贵州省林火发生概率和森林火险区划图。结果表明:近10年,贵州省火点数量逐年呈下降趋势,每年主要集中在1—3月,占全年火点数量的61%;距居民点距离、距铁路距离、人口密度、逐月平均空气温度、逐月平均相对湿度和逐月累计降雨量对贵州省林火发生概率有显著影响,得到模型的预测准确率为81.9%,曲线下面积为0.904;贵州省春季林火发生概率高于其他季节,且春、秋和冬季的森林火灾高火险区主要集中在贵州省西部,而夏季则主要是贵州东部的林火发生概率较高。研究得到贵州省林火发生驱动因子和基于季节火险区划图,对于该地区科学林火管理具有重要意义,贵州西部林火发生概率主要在偏远地区,应该增加瞭望塔和视频监控等设备,加强巡护,提高监测范围和时效,对于贵州东部夏季,应该加强防火宣传和人为活动管控,减少火源出现概率。


关键词: 驱动因子, Logistic回归, 预测模型, 火险区划,  贵州省

Abstract: The forest area of southwest China has complex fire sources and human interference, most of which are karst landform and in the ecotone of agriculture and forestry, leading to the most serious forest fire disaster area in China. The area has high mountains and steep slopes, making it extremely difficult to extinguish a fire once it occurs. It is of great significance to analyze the driving factors of forest fire in this region and to carry out fire risk zoning for rational forest fire management. Based on the forest fire point data, geospatial data, meteorological data, vegetation data and human activity data from 2011 to 2020, the spatiotemporal pattern of forest fire distribution in Guizhou in the past decade was analyzed, and the driving factors and probability prediction model of forest fire occurrence were obtained. The forest fire occurrence probability and forest fire risk zoning map of Guizhou in different seasons were analyzed. The results showed that in the past 10 years, the number of fire points in Guizhou showed a downward trend year by year. Fire points were mainly concentrated from January to March, accounting for 61% of the total number of fire points in a whole year. Distance from residential areas, distance from railways, population density, monthly average air temperature, monthly average relative humidity and monthly cumulative rainfall had significant effects on the probability of forest fire in Guizhou. A Logistic regression model was established. The prediction accuracy of the model was 81.9%, and the area under the curve was 0.904. The occurrence probability of forest fire in spring was higher than that in other seasons. The high-risk areas of forest fires in spring, autumn, and winter was mainly concentrated in western Guizhou, while the high-risk areas in summer were mainly distributed in eastern Guizhou. Research on the driving factors of forest fire occurrence and fire risk zoning maps based on the seasons is of great significance to the scientific management of forest fires in Guizhou. Forest fires in western Guizhou mainly occur in remote areas with a high probability of fire occurrence. Observation towers and video surveillance equipment should be added, patrol should be strengthened, and monitoring scope and timeliness should be improved. Fire prevention publicity and the control of human activities should be strengthened in eastern Guizhou in summer to reduce the probability of fire occurrence.


Key words: driving factor, Logistic regression, prediction model, fire risk rating, Guizhou Province