摘要
互花米草(Spartina alterniflora)作为滨海湿地的主要入侵植被,对滨海湿地生态系统结构和功能造成了严重影响,因此,及时、准确地监测互花米草的生长状况,可为滨海湿地生态系统的恢复提供依据。本研究基于Sentinel-2多光谱卫星影像,提取原始波段、植被指数和生物物理参数3类特征变量,利用多元逐步回归的方法构建互花米草的地上生物量最优估算模型,并对生物量进行空间制图。结果表明,在所构建的模型中,基于结合3类特征变量的逐步回归模型的估算精度最高,其决定系数R2为0.879,均方根误差RMSE为255.5 g/m^(2),平均相对误差MRE为10.63%。互花米草地上生物量的空间分布,呈靠近陆地一侧生物量低、靠近海洋一侧生物量高的特点。综上所述,利用Sentinel-2数据对互花米草地上生物量高精度反演是可行和有效的。
Spartina alterniflora,as a major invasive vegetation in coastal wetlands,has a serious impact on the ecosystem structure and function of coastal wetland.Therefore,timely and accurate monitoring of the growth status of S.alterniflora can provide a basis for the restoration of coastal wetland ecosystems.Based on Sentinel-2 multispectral satellite images,this study extracted three types of characteristic variables:original bands,vegetation index,and biophysical parameters,and constructed an optimal biomass estimation model for S.alterniflora by using multiple stepwise regression methods,and then performed spatial mapping of biomass.The results showed that among the constructed models,the estimation accuracy of the stepwise regression model based on combining three types of characteristic variables had the highest estimation accuracy,with a determination coefficient of 0.879,a root mean square error of 255.5 g/m^(2) and a mean relative error of 10.63%.The spatial distribution of aboveground biomass on S.alterniflora was characterized by low biomass near land and high biomass near the ocean side. In summary, it is feasible and effective to use Sentinel-2 data to invert theaboveground biomass on the S. alterniflora with high accuracy.
作者
李敏
陈利
李静泰
闫丹丹
刘垚
吴翠玲
栾兆擎
LI Min;CHEN Li;LI Jingtai;YAN Dandan;LIU Yao;WU Cuiling;LUAN Zhaoqing(Co-Innovation Center for Sustainable Forestry in Southern China,Nanjing Forestry University,Nanjing 210037,China;College of Ecology and the Environment,Nanjing Forestry University,Nanjing 210037,China;College of Horticulture and Plant Protection,Henan University of Science and Technology,Luoyang 471000,China)
出处
《海洋环境科学》
CAS
CSCD
北大核心
2024年第3期386-397,共12页
Marine Environmental Science
基金
国家自然科学基金项目(41871097)。
