基于随机森林模型的海南岛热带森林火灾发生概率预测

doi:10.13466/j.cnki.lczyyj.2024.06.016

林草资源研究 ›› 2024›› Issue (6): 140-145.doi: 10.13466/j.cnki.lczyyj.2024.06.016

基于随机森林模型的海南岛热带森林火灾发生概率预测

陈小花¹^,²^,³(), 陈宗铸¹^,²^,³, 杨青青¹^,²^,³(), 雷金睿¹^,²^,³, 吴庭天¹^,²^,³, 李苑菱¹^,²^,³, 潘小艳¹^,²^,³

1.海南省林业科学研究院(海南省红树林研究院),海口 571100
2.海南省热带林业资源监测与应用重点实验室,海口 571100
3.海南省院士工作站,海口 571100

收稿日期:2024-07-16 修回日期:2024-10-28 出版日期:2024-12-28 发布日期:2025-04-18
通讯作者: 杨青青,高级工程师,主要研究方向森林火灾生态学。Email:624767243@qq.com
作者简介:陈小花,高级工程师,主要研究方向为森林生态。Email:965819833@qq.com
基金资助:
海南省科技计划项目-省属科研院所技术创新专项“海南岛森林火灾时空分布、驱动机制及预测模型研究”(SQKY2022-0021)

Predicting the Probability of Tropical Forest Fires in Hainan Island Based on Random Forest Model

CHEN Xiaohua¹^,²^,³(), CHEN Zongzhu¹^,²^,³, YANG Qingqing¹^,²^,³(), LEI Jinrui¹^,²^,³, WU Tingtian¹^,²^,³, LI Yuanling¹^,²^,³, PAN Xiaoyan¹^,²^,³

1. Hainan Academy of Forestry(Hainan Academy of Mangrove),Haikou 571100,China
2. Key Laboratory of Tropical Forestry Resources Monitoring and Application of Hainan Province,Haikou 571100,China
3. The Innovation Platform for Academicians of Hainan Province,Haikou 570100,China

Received:2024-07-16 Revised:2024-10-28 Online:2024-12-28 Published:2025-04-18

摘要/Abstract

摘要：

分析海南岛热带森林火灾的驱动因素,构建适用性强的预测模型,为森林火灾的精准预防提供技术支撑。基于地面调查的历史森林火灾数据和MOD14A火灾数据集,结合气候、植被、地形及人类活动等数据,利用随机森林模型构建森林火灾发生概率预测模型。结果表明:1)月均气温是影响海南岛森林火灾发生风险的最强因子,其次为月均降水量。2)随机森林模型预测森林火灾发生概率的曲线下面积(AUC)值为1.00,高于地理加权逻辑斯蒂回归模型的AUC值(0.88),表明随机森林模型在海南岛的热带森林火灾风险预测中表现更高的适用性。3)海南岛森林火灾风险的高发区域主要集中在西部。总体来看,随机森林模型在构建热带森林火灾风险预测模型方面,比地理加权逻辑斯蒂回归模型具有更高的适用性。

关键词: 海南岛, 森林火灾, 广义线性模型, 随机森林模型, 发生概率预测

Abstract:

In the context of global climate change,the forest fire prevention situation on Hainan Island is becoming increasingly severe,and it is urgently needed to analyze the driving factors of tropical forest fires on Hainan Island and build a strong predictive model that is applicable.Utilizing historical forest fire data compiled by the forestry department from ground surveys and MOD14A fire detection,a comprehensive dataset was established for Hainan Island.This dataset was combined with climate,vegetation,topography,and human activity data to construct a predictive model using the random forest methodology.1)The average monthly temperature is the most influential factor on forest fire risk in Hainan Province,followed by the average monthly precipitation.2)Comparative model analysis shows the random forest model,with an AUC value of 1,outperforms the geographically weighted logistic regression model,which has an AUC value of 0.88,indicating that the random forest model is more suitable for predicting the probability of tropical forest fires on Hainan Island than the geographically weighted logistic regression model.3)The spatial distribution of forest fire risk on Hainan Island mainly occurs in the west.This study believes that the random forest model is more applicable than the geographically weighted logistic regression model in building a predictive model for tropical forest fire risk.

Key words: Hainan Province, forest fires, generalized linear model, random forest model, probability of occurrence prediction

中图分类号:

S762.2

陈小花, 陈宗铸, 杨青青, 雷金睿, 吴庭天, 李苑菱, 潘小艳. 基于随机森林模型的海南岛热带森林火灾发生概率预测[J]. 林草资源研究, 2024,(6): 140-145.

CHEN Xiaohua, CHEN Zongzhu, YANG Qingqing, LEI Jinrui, WU Tingtian, LI Yuanling, PAN Xiaoyan. Predicting the Probability of Tropical Forest Fires in Hainan Island Based on Random Forest Model[J]. Forest and Grassland Resources Research, 2024,(6): 140-145.

图/表 4

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基于随机森林模型的海南岛热带森林火灾发生概率预测

Predicting the Probability of Tropical Forest Fires in Hainan Island Based on Random Forest Model

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