湖南省森林火灾驱动因子及火险区划研究

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

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。

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.