Hyperspectral estimation of mercury content of soil in Oasis city in arid zones of China

Mercury (Hg) is one of the most toxic heavy metals to the human body. Conventional methods for measuring Hg content in soil are time-consuming and expensive. In order to select a high-effective method for estimating soil Hg content based on hyperspectral remote sensing techniques, a total of 85 soil...

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Main Authors: Qing Zhong, Mamattursun Eziz, Mireguli Ainiwaer, Rukeya Sawut, Maorui Hou
Format: Article
Language:English
Published: Taylor & Francis Group 2024-01-01
Series:Geocarto International
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Online Access:https://www.tandfonline.com/doi/10.1080/10106049.2023.2299147
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author Qing Zhong
Mamattursun Eziz
Mireguli Ainiwaer
Rukeya Sawut
Maorui Hou
author_facet Qing Zhong
Mamattursun Eziz
Mireguli Ainiwaer
Rukeya Sawut
Maorui Hou
author_sort Qing Zhong
collection DOAJ
description Mercury (Hg) is one of the most toxic heavy metals to the human body. Conventional methods for measuring Hg content in soil are time-consuming and expensive. In order to select a high-effective method for estimating soil Hg content based on hyperspectral remote sensing techniques, a total of 85 soil samples were collected from the Urumqi city, northwest China, to obtain the Hg contents and related hyperspectral data. A total of 12 spectral transformation methods were used to the original spectral data for selecting significant wavebands. The partial least squares regression (PLSR), random forest regression (RFR) and support vector machine regression (SVMR) were used to establish hyperspectral inversion models for soil Hg content using selected significant wavebands. The results showed that the Hg content of soil was significantly higher than its corresponding background value, which obviously enriched in soil in the study area. The spectral transformation of the original wavebands can effectively reduce the interference of the background noise and can improve the correlations between the spectral data and the soil Hg content. The RFR model based on logarithmic first-order differential (LTFD–RFR) or on reciprocal logarithmic first-order differential (ATFD–RFR) had the best inversion effects, with the highest prediction ability (R2 = 0.856, RMSE = 0.002 and MAE = 0.072). The LTFD–RFR or ATFD–RFR methods can be used as a means of inversion of Hg content of soil in oasis cities. The novel contribution of this work is to construct hyperspectral inversion model which can accurately estimate the Hg content of urban soils in arid zones. Results of this study can provide a technical support for hyperspectral estimation of soil Hg content.
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spelling doaj-art-035018242e3e42e3b42e368a15d5dfa72025-08-20T02:38:26ZengTaylor & Francis GroupGeocarto International1010-60491752-07622024-01-0139110.1080/10106049.2023.2299147Hyperspectral estimation of mercury content of soil in Oasis city in arid zones of ChinaQing Zhong0Mamattursun Eziz1Mireguli Ainiwaer2Rukeya Sawut3Maorui Hou4College of Geographical Science and Tourism, Xinjiang Normal University, Urumqi, PR ChinaCollege of Geographical Science and Tourism, Xinjiang Normal University, Urumqi, PR ChinaCollege of Geographical Science and Tourism, Xinjiang Normal University, Urumqi, PR ChinaCollege of Geographical Science and Tourism, Xinjiang Normal University, Urumqi, PR ChinaCollege of Computer Science and Technology, Tiangong University, Tianjin, PR ChinaMercury (Hg) is one of the most toxic heavy metals to the human body. Conventional methods for measuring Hg content in soil are time-consuming and expensive. In order to select a high-effective method for estimating soil Hg content based on hyperspectral remote sensing techniques, a total of 85 soil samples were collected from the Urumqi city, northwest China, to obtain the Hg contents and related hyperspectral data. A total of 12 spectral transformation methods were used to the original spectral data for selecting significant wavebands. The partial least squares regression (PLSR), random forest regression (RFR) and support vector machine regression (SVMR) were used to establish hyperspectral inversion models for soil Hg content using selected significant wavebands. The results showed that the Hg content of soil was significantly higher than its corresponding background value, which obviously enriched in soil in the study area. The spectral transformation of the original wavebands can effectively reduce the interference of the background noise and can improve the correlations between the spectral data and the soil Hg content. The RFR model based on logarithmic first-order differential (LTFD–RFR) or on reciprocal logarithmic first-order differential (ATFD–RFR) had the best inversion effects, with the highest prediction ability (R2 = 0.856, RMSE = 0.002 and MAE = 0.072). The LTFD–RFR or ATFD–RFR methods can be used as a means of inversion of Hg content of soil in oasis cities. The novel contribution of this work is to construct hyperspectral inversion model which can accurately estimate the Hg content of urban soils in arid zones. Results of this study can provide a technical support for hyperspectral estimation of soil Hg content.https://www.tandfonline.com/doi/10.1080/10106049.2023.2299147Soil mercury contentspectral analysishyperspectral estimationRFRSVMR
spellingShingle Qing Zhong
Mamattursun Eziz
Mireguli Ainiwaer
Rukeya Sawut
Maorui Hou
Hyperspectral estimation of mercury content of soil in Oasis city in arid zones of China
Geocarto International
Soil mercury content
spectral analysis
hyperspectral estimation
RFR
SVMR
title Hyperspectral estimation of mercury content of soil in Oasis city in arid zones of China
title_full Hyperspectral estimation of mercury content of soil in Oasis city in arid zones of China
title_fullStr Hyperspectral estimation of mercury content of soil in Oasis city in arid zones of China
title_full_unstemmed Hyperspectral estimation of mercury content of soil in Oasis city in arid zones of China
title_short Hyperspectral estimation of mercury content of soil in Oasis city in arid zones of China
title_sort hyperspectral estimation of mercury content of soil in oasis city in arid zones of china
topic Soil mercury content
spectral analysis
hyperspectral estimation
RFR
SVMR
url https://www.tandfonline.com/doi/10.1080/10106049.2023.2299147
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