Retrieving zinc concentrations in topsoil with reflectance spectroscopy at Opencast Coal Mine sites

Abstract Heavy metals contaminations in mining areas aroused wide concerns globally. Efficient evaluation of its pollution status is a basis for further soil reclamation. Visible and near–infrared reflectance (Vis–NIR) spectroscopy has been diffusely used for retrieving heavy metals concentrations....

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Autores principales:	Bin Guo, Bo Zhang, Yi Su, Dingming Zhang, Yan Wang, Yi Bian, Liang Suo, Xianan Guo, Haorui Bai
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f5efc56732c54ea39aa24d707d711aee
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spelling	oai:doaj.org-article:f5efc56732c54ea39aa24d707d711aee2021-12-02T19:16:14ZRetrieving zinc concentrations in topsoil with reflectance spectroscopy at Opencast Coal Mine sites10.1038/s41598-021-99106-12045-2322https://doaj.org/article/f5efc56732c54ea39aa24d707d711aee2021-10-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-99106-1https://doaj.org/toc/2045-2322Abstract Heavy metals contaminations in mining areas aroused wide concerns globally. Efficient evaluation of its pollution status is a basis for further soil reclamation. Visible and near–infrared reflectance (Vis–NIR) spectroscopy has been diffusely used for retrieving heavy metals concentrations. However, the reliability and feasibility of calibrated models were still doubtful. The present study estimated zinc (Zn) concentrations via the random forest (RF) and partial least squares regression (PLSR) using ground in-situ Zn concentrations as well as soil spectral reflectance at an Opencast Coal Mine of Ordos, China in February 2020. The coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), and the ratio of performance to deviation (RPD) were selected to assess the robustness of the methods in estimating Zn contents. Moreover, the characteristic bands were chosen by Pearson correlation analysis and Boruta Algorithm. Finally, the comparison between RF and PLSR combined with eight spectral reflectance transformation methods was conducted for four concentration groups to determine the optimal model. The results indicated that: (1) Zn contents represented a skewed distribution (coefficient of variation (CV) = 33%); (2) the spectral reflectance tended to decrease with the increase of Zn contents during 580–1850 nm based on Savitzky–Golay smoothing (SG); (3) the continuous wavelet transform (CWT) demonstrated higher effectiveness than other spectral reflectance transformation methods in enhancing spectral responses, the R2 between Zn contents and the soil spectral reflectance achieved the highest (R2 = 0.71) by using CWT; (4) the RF combined with CWT exhibited the best performance than other methods in the current study (R2 = 0.97, RPD = 3.39, RMSE = 1.05 mg kg−1, MAE = 0.79 mg kg−1). The current study supplied a scientific scheme and theoretical support for predicting heavy metals concentrations via the Vis–NIR spectral method in possible contaminated areas such as coal mines and metallic mineral deposit areas.Bin GuoBo ZhangYi SuDingming ZhangYan WangYi BianLiang SuoXianan GuoHaorui BaiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-20 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Bin Guo Bo Zhang Yi Su Dingming Zhang Yan Wang Yi Bian Liang Suo Xianan Guo Haorui Bai Retrieving zinc concentrations in topsoil with reflectance spectroscopy at Opencast Coal Mine sites
description	Abstract Heavy metals contaminations in mining areas aroused wide concerns globally. Efficient evaluation of its pollution status is a basis for further soil reclamation. Visible and near–infrared reflectance (Vis–NIR) spectroscopy has been diffusely used for retrieving heavy metals concentrations. However, the reliability and feasibility of calibrated models were still doubtful. The present study estimated zinc (Zn) concentrations via the random forest (RF) and partial least squares regression (PLSR) using ground in-situ Zn concentrations as well as soil spectral reflectance at an Opencast Coal Mine of Ordos, China in February 2020. The coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), and the ratio of performance to deviation (RPD) were selected to assess the robustness of the methods in estimating Zn contents. Moreover, the characteristic bands were chosen by Pearson correlation analysis and Boruta Algorithm. Finally, the comparison between RF and PLSR combined with eight spectral reflectance transformation methods was conducted for four concentration groups to determine the optimal model. The results indicated that: (1) Zn contents represented a skewed distribution (coefficient of variation (CV) = 33%); (2) the spectral reflectance tended to decrease with the increase of Zn contents during 580–1850 nm based on Savitzky–Golay smoothing (SG); (3) the continuous wavelet transform (CWT) demonstrated higher effectiveness than other spectral reflectance transformation methods in enhancing spectral responses, the R2 between Zn contents and the soil spectral reflectance achieved the highest (R2 = 0.71) by using CWT; (4) the RF combined with CWT exhibited the best performance than other methods in the current study (R2 = 0.97, RPD = 3.39, RMSE = 1.05 mg kg−1, MAE = 0.79 mg kg−1). The current study supplied a scientific scheme and theoretical support for predicting heavy metals concentrations via the Vis–NIR spectral method in possible contaminated areas such as coal mines and metallic mineral deposit areas.
format	article
author	Bin Guo Bo Zhang Yi Su Dingming Zhang Yan Wang Yi Bian Liang Suo Xianan Guo Haorui Bai
author_facet	Bin Guo Bo Zhang Yi Su Dingming Zhang Yan Wang Yi Bian Liang Suo Xianan Guo Haorui Bai
author_sort	Bin Guo
title	Retrieving zinc concentrations in topsoil with reflectance spectroscopy at Opencast Coal Mine sites
title_short	Retrieving zinc concentrations in topsoil with reflectance spectroscopy at Opencast Coal Mine sites
title_full	Retrieving zinc concentrations in topsoil with reflectance spectroscopy at Opencast Coal Mine sites
title_fullStr	Retrieving zinc concentrations in topsoil with reflectance spectroscopy at Opencast Coal Mine sites
title_full_unstemmed	Retrieving zinc concentrations in topsoil with reflectance spectroscopy at Opencast Coal Mine sites
title_sort	retrieving zinc concentrations in topsoil with reflectance spectroscopy at opencast coal mine sites
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/f5efc56732c54ea39aa24d707d711aee
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Retrieving zinc concentrations in topsoil with reflectance spectroscopy at Opencast Coal Mine sites

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