文献类型：期刊文献

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

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

第一作者：刘魏魏;Liu, Weiwei

通信作者：Zhang, MY[1]|[a00051fe3588fbc8d8c88]张曼胤;

机构：[1]Chinese Acad Forestry, Inst Wetland Res, 1 Dongxiaofu, Beijing 100091, Peoples R China;[2]Beijing Key Lab Wetland Serv & Restorat, Beijing, Peoples R China;[3]Hengshuihu Natl Wetland Ecosyst Res Stn, Hengshui, Hebei, Peoples R China;[4]Hanshiqiao Natl Wetland Ecosyst Res Stn, Beijing, Peoples R China

年份：2020

卷号：6

期号：1

外文期刊名：ECOSYSTEM HEALTH AND SUSTAINABILITY

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000519069100001)】；

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

语种：英文

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

摘要：Introduction: High mercury (Hg) concentrations affect the chlorophyll in leaves, thereby modifying 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 continuum removal-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.