Exploring field vegetation reflectance as an indicator of soil contamination in river floodplains

被引:151
作者
Kooistra, L
Salas, EAL
Clevers, JGPW
Wehrens, R
Leuven, RSEW
Nienhuis, PH
Buydens, LMC
机构
[1] Univ Nijmegen, Dept Environm Studies, NL-3525 ED Nijmegen, Netherlands
[2] Univ Nijmegen, Analyt Chem Lab, NL-6525 ED Nijmegen, Netherlands
[3] Univ Wageningen & Res Ctr, Lab Geoinformat Sci & Remote Sensing, NL-6708 PB Wageningen, Netherlands
关键词
heavy metals; vegetation reflectance; remote sensing; multivariate statistics; river sediment;
D O I
10.1016/S0269-7491(03)00266-5
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study investigated the relation between vegetation reflectance and elevated concentrations of the metals Ni, Cd, Cu, Zn and Pb in river floodplain soils. High-resolution vegetation reflectance spectra in the visible to near-infrared (400-1350 nm) were obtained using a field radiometer. The relations were evaluated using simple linear regression in combination with two spectral vegetation indices: the Difference Vegetation Index (DVI) and the Red-Edge Position (REP). In addition, a multivariate regression approach using partial least squares (PLS) regression was adopted. The three methods achieved comparable results. The best R-2 values for the relation between metals concentrations and vegetation reflectance were obtained for grass vegetation and ranged from 0.50 to 0.73. Herbaceous species displayed a larger deviation from the established relationships, resulting in lower R-2 values and larger cross-validation errors. The results corroborate the potential of hyperspectral remote sensing to contribute to the survey of elevated metal concentrations in floodplain soils under grassland using the spectral response of the vegetation as an indicator. Additional constraints will, however, have to be taken into account, as results are resolution- and location-dependent. (C) 2003 Elsevier Ltd. All rights reserved.
引用
收藏
页码:281 / 290
页数:10
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