基于Sentinel-2B的油松冠层可燃物含水率反演研究  

Research on Inversion of Combustible Moisture Content in the Pinus Tabulaeformis Canopy Based on Sentinel-2B

作　　者：刘鸿升 欧阳文欣 魏英杰 谢亦秋 李建军[2] LIU Hongsheng;OUYANG Wenxin;WEI Yingjie;XIE Yiqiu;LI Jianjun(Hunan Provincial Forestry Affairs Center,Changsha 410004,China;College of Computer and Information Engineering,Central South University of Forestry and Technology,Changsha 410004,China;Institute of Forest Resource Information Techniques,Chinese Academy of Forestry,Beijing 100091,China)

机构地区：[1]湖南省林业事务中心,长沙410004 [2]中南林业科技大学计算机与信息工程学院,长沙410004 [3]中国林业科学研究院资源信息研究所,北京100091

出　　处：《林业资源管理》2023年第4期141-149,共9页Forest Resources Management

基　　金：国家重点研发计划课题“森林立地质量评价和全周期多功能经营决策平台”(2022YFD2200505)。

摘　　要：森林火灾的发生与植被冠层可燃物含水率的大小有着密切联系。利用高精度、大尺度、高效率的遥感影像反演获取植被冠层可燃物含水率对于有效防治森林火灾具有重要意义。油松由于其自身理化性质成为引发森林火灾的主要树种之一,以张家口崇礼区的油松为研究对象,基于Sentinel-2B遥感影像和油松含水率实测数据,建立了多个油松冠层可燃物含水率反演模型:一元线性回归模型、一元非线性回归模型和多元非线性回归模型,并利用决定系数(R 2)和均方根误差(RMSE)进行模型精度评价。结果表明,非线性模型总体上要优于线性模型;通过多个自变量因子建立的多元非线性模型能够更好地反映油松冠层可燃物含水率情况,模型反演精度更高,可以为植被冠层可燃物含水率反演模型方法选择提供一定的理论依据。The occurrence of forest fires is closely related to the moisture content of vegetation canopy combustibles.Using high-precision,large-scale,and high-efficiency remote sensing image inversion to obtain the moisture content of vegetation canopy combustibles is of great significance for effective prevention and control of forest fires.Pinus tabulaeformis is one of the main tree species causing forest fires due to its physical and chemical properties.This study takes Pinus tabulaeformis in Chongli District,Zhangjiakou as the research object.Based on Sentinel 2B remote sensing images and measured moisture content dataof Pinus tabulaeformis,multiple linear regression models,nonlinear regression models and multiple nonlinear regression models were established for the moisture content of Pinus tabulaeformis canopy combustibles.Using the coefficient of determination(R 2)and root mean square error(RMSE)to evaluate model accuracy.The results indicated that the nonlinear model was generally superior to the linear model;The multivariate nonlinear model established through multiple independent variable factors better reflected the moisture content of Pinus tabulaeformis canopy combustibles,and the model had higher inversion accuracy,which provided a certain theoretical basis for the selection of vegetation canopy fuel moisture inversion model methods.

关 键 词：Sentinel-2B 油松 冠层可燃物含水率 线性回归 多元非线性回归 

分 类 号：S762[农业科学—森林保护学] S771.8[农业科学—林学]