Estimation of Soil Nickel Using Visible and Near-Infrared Spectroscopy Based on Spectral Classification
Soil heavy metal pollution is an increasingly severe environmental problem. Efficient investigation of soil contamination with heavy metals is the premise of soil remediation. Visible and near-infrared reflectance spectroscopy (VNIRS) has been widely used in the assessment of soil contaminant elements due to its rapidity and convenience. The relation between spectrally active soil characteristics (organic matter, iron oxide and clay minerals) and heavy metals is the mechanism of reflectance spectroscopy for assessment of soil heavy metals. With different spectrally active soil characteristics, soil reflectance spectra exhibit distinctive curve forms. In consideration of various soil reflectance curve forms, spectral clustering was applied to explore the potential of classification in soil nickel (Ni) estimation. In this study, 74 soil samples were collected from Hunan Province, China and their reflectance spectra were employed to estimate Ni concentration by partial least square regression (PLSR). Savitzky-Golay (SG) smoothing method was used to reduce the noise caused by spectral measurement, and the spectra were clustered into two groups, group 1 and group 2, by k-means method based on squared Euclidean distance. Root mean square error of prediction (RMSEP), coefficient of determination (R2 ) and residual prediction deviation (RPD) were adopted to evaluate the prediction accuracy. The result shows that the accuracy in group 1 was improved by clustering with R2 increased from 0.32 to 0.59, RPD increased from 1.21 to 1.56, while the prediction accuracy in group 2 was decreased with RPD dropped from 1.21 to 0.76. Preliminary analysis shows that the decrement for soil samples in group 2 was caused by the weak absorption feature of clay minerals. Future research may focus on the effect of soil constituents on absorption of Ni on soil. The result indicates the significance of considering soil reflectance curve forms in soil Nickel estimation using VNIRS.
Authors: Weichao Sun | Xia Zhang | Honglei Lin
Keywords: Soil nickel, VNIRS, Spectral classification, PLSR
Soil spectra for the estimation of soil nickel using visible and near-infrared spectroscopy based on spectral classification were measured by a portable spectrometer PSR+™ which covered a spectral range of 350-2500 nm. Spectral Evolution is a leading manufacturer of field-portable UV-Vis-NIR remote sensing spectroradiometers and spectrometers for applications including geological remote sensing, ground-truthing, spectral remote sensing, environmental and climate research, crop and soil research, vegetative studies, forestry and canopy studies, radiometric calibration transfer, upwelling and downwelling measurement and more. Our UV-Vis-NIR spectrometers and spectroradiometers provide the best combination of high resolution and high sensitivity resulting in the most precise field portable instruments available on the market.
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