文献类型：期刊文献

中文题名：Estimating leaf mercury content in Phragmites australis based on leaf hyperspectral reflectance

作者：Weiwei Liu[1,2,3] Mengjie Li[1,2,3] Manyin Zhang[1,2,3] DaanWang[1,2,3] Ziliang Guo[1,2,3] Songyuan Long[1,2,3] Si Yang[1,2,3] Henian Wang[1,2,3] Wei Li[1,2,4] Yukun Hu[1,2,3] Yuanyun Wei[1,2,3] Hongye Xiao[1,2,3]

第一作者：刘魏魏;Weiwei Liu

机构：[1]Institute of Wetland Research,Chinese Academy of Forestry,Beijing,China;[2]Beijing Key Laboratory of Wetland Services and Restoration,Beijing,China;[3]cHengshuihu National Wetland Ecosystem Research Station,Hengshui,Hebei,China;[4]Hanshiqiao National Wetland Ecosystem Research Station,Beijing,China

年份：2020

卷号：6

期号：1

起止页码：240-250

中文期刊名：生态系统健康与可持续性（英文）

外文期刊名：Ecosystem Health and Sustainability

收录：Scopus

基金：This work was supported by the Fundamental Research Funds of Central-level Nonprofit Research Institutes of China[CAFINT2014K05].

语种：英文

中文关键词：Mercury pollution;reed leaf;hyperspectrum;inversion model;nondestructive monitoring

分类号：F42

摘要：Introduction:Highmercury(Hg)concentrations affect the chlorophyll in leaves,therebymodifying leaf spectra.Hyperspectra is a promising technique for the rapid,nondestructive evaluation of leaf Hg content.In this study,we investigated Hg contents and reflective hyperspectra of reed leaves(Phragmites communis)in a gold mining(Jilin province,China).Spectral parameters sensitive to Hg content were identified through basic spectral transformations,continuous wavelet transformation(CWT),and spectral indices techniques.Leaf Hg inversion models were developed using stepwise multiple linear regression,partial least squares regression,and random forest algorithms.Outcomes:The results indicated that:1)leaf Hg content decreased with increasing distance from the mine:Jiapigou(JPG)>Erdaocha(EDC)>Laojingchang(LJC)>Erdaogou(EDG)>Lingqian(LQ)>Weishahe(WSH).2)Hg–sensitive wavelengths were primarily in the visible region;CWT increased the correlation between hyperspectral data and leaf Hg content,and improved the regression and accuracy of inversion;3)the continuumremoval–CWT–stepwise multiple linear regression was better for estimating low leaf Hg content;while the differential spectral index–partial least squares regression was better for estimating high leaf Hg content.Conclusion:These hyperspectral inversion methods could be used for rapid,nondestructive monitoring of wetland plants.