基于GEE的中国不同生态系统林火驱动力研究  

Exploration Analysis of Fire Drives in Different Chinese Ecosystems Based on Google Earth Engine

作　　者：马丹[1] 汤志伟 马小玉 邵尔辉 黄达沧 MA Dan;TANG Zhiwei;MA Xiaoyu;SHAO Erhui;HUANG Dacang(College of Resources and Environment,Fujian Agriculture and Forestry University,Fuzhou 350002,Fujian,China;National&Local Joint Engineering Research Center of Satellite Geospatial Information Technology,Fuzhou University,Fuzhou 350108,Fujian,China;Beijing Haidian District Health School,Beijing 100192,China)

机构地区：[1]福建农林大学资源与环境学院,福建福州350002 [2]福州大学卫星空间信息技术综合应用国家地方联合工程研究中心,福建福州350108 [3]北京市海淀区卫生学校,北京100192

出　　处：《应用科学学报》2024年第4期684-694,共11页Journal of Applied Sciences

基　　金：国家自然科学基金(No.41971050);福建省社会科学基金(No.JAS160179);福建农林大学重点项目(No.111420015,No.KCXTF052A)资助。

摘　　要：针对同时对大尺度范围内的不同生态系统林火驱动力研究的难题,提出一种基于谷歌地球引擎(google earth engine,GEE)实现大范围不同生态系统林火驱动力的分析方法。首先基于GEE在线获取中国4个主要不同生态系统林火数据集、Sentinel-2卫星影像和驱动因子等信息,再通过Sentinel-2影像提取的归一化燃烧率差值筛选真实林火点,然后利用随机森林、支持向量机和增强回归树法对林火点分类并评价其表现,最后筛选最佳方法进行林火驱动力重要性分析。研究结果表明:随机森林预测林火的精度最高,均超过92%;山西省长治市和内蒙古大兴安岭地区林火最重要的驱动力分别为人口分布和最高温度,而四川省凉山彝族自治州和江西省赣州市林火发生最重要的两个驱动因子均为帕默尔干旱指数和土壤湿度。研究证明基于GEE的方法可有效地同时实现大范围内中国不同生态系统林火驱动力研究。Focused on studying wildfire and driving forces across various ecosystems on a large scale,this paper presents a novel method utilizing the google earth engine(GEE)platform.Firstly,the fire information for resource management system database,Sentinel-2 images and driving factor information in four different Chinese ecosystems were accessed on online via GEE platform.Then,the differential normalized burn ratio was extracted from Sentinel-2 images to sieve fire spots.Three machine learning algorithms,namely random forest,support vector machine and augmented regression tree,were used to classify fire locations.Furthermore,we determined the optimal-performing classification algorithms for each ecosystem and assessed variable importance.The results showed that random forest performed best with accuracy exceeding 92%among the three machine methods and the fire drivers varied significantly among four different ecosystems.In Changzhi City of Shanxi Province,and the Great Xing′an Mountains of Inner Mongolia,population distribution and maximum temperature were identified as the most influential drivers,respectively.While for Liangshan Yi Autonomous Prefecture in Sichuan Province and Ganzhou City in Jiangxi Province,the palmer drought index and soil moisture emerged as the primary drivers.This study demonstrates the efficacy of the proposed GEE-based method in studying wildfire and driving forces across different ecosystems in large scale regions.

关 键 词：林火 驱动力 随机森林 支持向量机 增强回归树 谷歌地球引擎 

分 类 号：X87[环境科学与工程—环境工程] TP79[自动化与计算机技术—检测技术与自动化装置]