湖南省森林火灾驱动因子及火险区划研究

消防科学与技术 ›› 2024, Vol. 43 ›› Issue (11): 1603-1609.

湖南省森林火灾驱动因子及火险区划研究

张国琛¹, 张佳男², 石宽^3,4, 白夜^3,4

（1. 福建省森林消防总队，福建福州 350012；2. 黑龙江省庆安国有林场管理局，黑龙江庆安 152499；3. 中国消防救援学院，北京 102202；4. 森林草原火灾风险防控应急管理部重点实验室，北京 102202）

收稿日期:2023-06-30 修回日期:2024-04-25 出版日期:2024-11-15 发布日期:2024-11-15
作者简介:张国琛（1997- ），男，山东临沂人，福建省森林消防总队四级指挥员，学士，主要从事森林火灾监测、预测研究，福建省福州市晋安区鹅峰村鹅峰路325号，350012。
基金资助:
基金项目：中国消防救援学院森林灭火指挥与战术创新团队（XF2020-XM01）

A Study on the driving factors and fire risk zoning of forest fire in Hunan Province

Zhang Guochen¹, Zhang Jianan², Shi Kuan^3,4, Bai Ye^3,4

(1. Forest fire brigade in Fujian Province, Fujian Fuzhou 350012, China; 2. Heilongjiang Qing’an State Forestry Administration, Heilongjiang Qingan 152499, China; 3. China Fire and Rescue Institute, Beijing 102202, China; 4.Key Laboratory of Forest and Grassland Fire Risk Prevention, Ministry of Emergency Management, Beijing 102202, China)

Received:2023-06-30 Revised:2024-04-25 Online:2024-11-15 Published:2024-11-15

摘要/Abstract

摘要： 建立湖南省林区的森林火灾发生预测模型，为该省的林火防控和管理工作提供一定的理论依据。提取湖南省2016-2020年森林火灾热点监测卫星数据，利用ArcGIS 10.7软件建立与火点形成1：1数据的随机点，使数据符合二项分布，对日平均最高气温、日平均降水量、日照时长、海拔等24类驱动因子进行空间信息提取，并利用GWR 4.0软件进行GWLR预测，分析影响湖南省森林火灾发生的驱动因子，构建该地区的森林火灾发生预测模型，利用AIC值、BIC值、ROC曲线和AUC值进行模型拟合检验，对该地区进行火险区划。研究结果表明：“日平均风速”“日平均气压”“日照时间”“日平均气温”“日平均相对湿度”“海拔”和“归一化指数值”等9个变量是影响湖南省森林火灾发生的驱动因子；GWLR模型在湖南省森林火灾发生预测中拟合效果良好，模型的AUC值为0.966，最佳划分阈值为0.810；在火险区划中，中高火险地区主要集中在湖南省中部和南部地区，该区域应进一步加强护林防火的宣传教育、建立健全野外用火管控制度、加强重点火险区基础设施建设等森林火灾预防工作。

关键词: 森林火灾预测, 地理加权逻辑斯蒂回归模型, 林火驱动因子, 火险区划

Abstract: A forest fire prediction model was established in the forest areas of Hunan Province, to provide a theoretical basis for the prevention, control and management of forest fires. Extracted forest fire hotspot monitoring satellite data from 2016 to 2020, and used ArcGIS 10.7 to establish random points that formed 1:1 data with fire points, making the data conform to binomial distribution. Spatial information was extracted from 24 types of driving factors such as daily average maximum temperature, daily average precipitation, sunshine duration, and altitude, and GWR 4.0 was used to predict and analyze the driving factors that affect the forest fires. A forest fire prediction model for the region was built, using AIC, BIC, ROC curves, and AUC for model fitting testing, and conduct fire risk zoning for the region. The research results indicate that: nine variables, including "daily average wind speed" "daily average pressure" "sunshine time" "daily average temperature" "daily average relative humidity" "altitude", and "normalized index value", are the driving factors; The GWLR model has a good fitting effect, with an AUC value of 0.966 and an optimal classification threshold of 0.810; In the fire risk zoning, medium to high fire risk areas are mainly concentrated in the central and southern regions of Hunan Province, and this area should further strengthen the publicity and education of forest fire prevention, establish and improve the control of outdoor fire pipes, and strengthen the construction of infrastructure in key fire risk areas.

Key words: forest fire prediction, geographically weighted logistic regression, forest fire driving factors, fire hazard area division

张国琛, 张佳男, 石宽, 白夜. 湖南省森林火灾驱动因子及火险区划研究[J]. 消防科学与技术, 2024, 43(11): 1603-1609.

Zhang Guochen, Zhang Jianan, Shi Kuan, Bai Ye, . A Study on the driving factors and fire risk zoning of forest fire in Hunan Province[J]. Fire Science and Technology, 2024, 43(11): 1603-1609.