Estimating the heavy metal concentrations in topsoil in the Daxigou mining area, China, using multispectral satellite imagery

Abstract A precise estimation of the heavy metal concentrations in soils using multispectral remote sensing technology is challenging. Herein, Landsat8 imagery, a digital elevation model, and geochemical data derived from soil samples are integrated to improve the accuracy of estimating the Cu, Pb,...

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Autores principales:	Yun Yang, Qinfang Cui, Peng Jia, Jinbao Liu, Han Bai
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/10a8cf83636d4c6bbfc1d291d4a532c8
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spelling	oai:doaj.org-article:10a8cf83636d4c6bbfc1d291d4a532c82021-12-02T18:24:53ZEstimating the heavy metal concentrations in topsoil in the Daxigou mining area, China, using multispectral satellite imagery10.1038/s41598-021-91103-82045-2322https://doaj.org/article/10a8cf83636d4c6bbfc1d291d4a532c82021-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-91103-8https://doaj.org/toc/2045-2322Abstract A precise estimation of the heavy metal concentrations in soils using multispectral remote sensing technology is challenging. Herein, Landsat8 imagery, a digital elevation model, and geochemical data derived from soil samples are integrated to improve the accuracy of estimating the Cu, Pb, and As concentrations in topsoil, using the Daxigou mining area in Shaanxi Province, China, as a case study. The relationships between the three heavy metals and soil environmental factors were investigated. The optimal combination of factors associated with the elevated concentrations of each heavy metal was determined combining correlation analysis with collinearity tests. A back propagation network optimised using a genetic algorithm was trained with 80% of the data for samples and subsequently employed to estimate the heavy metal concentrations in the area. The validation results show that the RMSE of the proposed model is lower than those of the existing linear model and rule-based M5 model tree. From the spatial distribution map of the three metals concentrations using the proposed method, there are findings that high concentrations of the heavy metals studied occur in the mining area, across the slag storage area, on the sides of the road used for transporting ore materials, and along the base of slopes in the area. These findings are consistent with the survey results in the field. The validation and findings validate the effectiveness of the proposed method.Yun YangQinfang CuiPeng JiaJinbao LiuHan BaiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yun Yang Qinfang Cui Peng Jia Jinbao Liu Han Bai Estimating the heavy metal concentrations in topsoil in the Daxigou mining area, China, using multispectral satellite imagery
description	Abstract A precise estimation of the heavy metal concentrations in soils using multispectral remote sensing technology is challenging. Herein, Landsat8 imagery, a digital elevation model, and geochemical data derived from soil samples are integrated to improve the accuracy of estimating the Cu, Pb, and As concentrations in topsoil, using the Daxigou mining area in Shaanxi Province, China, as a case study. The relationships between the three heavy metals and soil environmental factors were investigated. The optimal combination of factors associated with the elevated concentrations of each heavy metal was determined combining correlation analysis with collinearity tests. A back propagation network optimised using a genetic algorithm was trained with 80% of the data for samples and subsequently employed to estimate the heavy metal concentrations in the area. The validation results show that the RMSE of the proposed model is lower than those of the existing linear model and rule-based M5 model tree. From the spatial distribution map of the three metals concentrations using the proposed method, there are findings that high concentrations of the heavy metals studied occur in the mining area, across the slag storage area, on the sides of the road used for transporting ore materials, and along the base of slopes in the area. These findings are consistent with the survey results in the field. The validation and findings validate the effectiveness of the proposed method.
format	article
author	Yun Yang Qinfang Cui Peng Jia Jinbao Liu Han Bai
author_facet	Yun Yang Qinfang Cui Peng Jia Jinbao Liu Han Bai
author_sort	Yun Yang
title	Estimating the heavy metal concentrations in topsoil in the Daxigou mining area, China, using multispectral satellite imagery
title_short	Estimating the heavy metal concentrations in topsoil in the Daxigou mining area, China, using multispectral satellite imagery
title_full	Estimating the heavy metal concentrations in topsoil in the Daxigou mining area, China, using multispectral satellite imagery
title_fullStr	Estimating the heavy metal concentrations in topsoil in the Daxigou mining area, China, using multispectral satellite imagery
title_full_unstemmed	Estimating the heavy metal concentrations in topsoil in the Daxigou mining area, China, using multispectral satellite imagery
title_sort	estimating the heavy metal concentrations in topsoil in the daxigou mining area, china, using multispectral satellite imagery
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/10a8cf83636d4c6bbfc1d291d4a532c8
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Estimating the heavy metal concentrations in topsoil in the Daxigou mining area, China, using multispectral satellite imagery

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