Quantifying the chemical composition of weathering products of Hainan basalts with reflectance spectroscopy and its implications for Mars

With the development of the hyperspectral remote sensing technique, extensive chemical weathering profiles have been identified on Mars. These weathering sequences, formed through precipitation-driven leaching processes, can reflect the paleoenvironments and paleoclimates during pedogenic processes....

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Main Authors: Xing Wu, JiaCheng Liu, WeiChao Sun, Yang Liu, Joseph Michalski, Wei Tan, XiaoRong Qin, YongLiao Zou
Format: Article
Language:English
Published: Science Press 2024-11-01
Series:Earth and Planetary Physics
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Online Access:http://www.eppcgs.org/article/doi/10.26464/epp2024011?pageType=en
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author Xing Wu
JiaCheng Liu
WeiChao Sun
Yang Liu
Joseph Michalski
Wei Tan
XiaoRong Qin
YongLiao Zou
author_facet Xing Wu
JiaCheng Liu
WeiChao Sun
Yang Liu
Joseph Michalski
Wei Tan
XiaoRong Qin
YongLiao Zou
author_sort Xing Wu
collection DOAJ
description With the development of the hyperspectral remote sensing technique, extensive chemical weathering profiles have been identified on Mars. These weathering sequences, formed through precipitation-driven leaching processes, can reflect the paleoenvironments and paleoclimates during pedogenic processes. The specific composition and stratigraphic profiles mirror the mineralogical and chemical trends observed in weathered basalts on Hainan Island in south China. In this study, we investigated the laboratory reflectance spectra of a 53-m-long drilling core of a thick basaltic weathering profile collected from Hainan Island. We established a quantitative spectral model by combining the genetic algorithm and partial least squares regression (GA-PLSR) to predict the chemical properties (SiO2, Al2O3, Fe2O3) and index of laterization (IOL). The entire sample set was divided into a calibration set of 25 samples and a validation set of 12 samples. Specifically, the GA was used to select the spectral subsets for each composition, which were then input into the PLSR model to derive the chemical concentration. The coefficient of determination (R2) values on the validation set for SiO2, Al2O3, Fe2O3, and the IOL were greater than 0.9. In addition, the effects of various spectral preprocessing techniques on the model accuracy were evaluated. We found that the spectral derivative treatment boosted the prediction accuracy of the GA-PLSR model. The improvement achieved with the second derivative was more pronounced than when using the first derivative. The quantitative model developed in this work has the potential to estimate the contents of similar weathering basalt products, and thus infer the degree of alteration and provide insights into paleoclimatic conditions. Moreover, the informative bands selected by the GA can serve as a guideline for designing spectral channels for the next generation of spectrometers.
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spelling doaj-art-e9ed766ae5da47fca70f25adb9a2fe412025-08-20T02:13:55ZengScience PressEarth and Planetary Physics2096-39552024-11-018685486710.26464/epp2024011RA436-wuxing-FQuantifying the chemical composition of weathering products of Hainan basalts with reflectance spectroscopy and its implications for MarsXing Wu0JiaCheng Liu1WeiChao Sun2Yang Liu3Joseph Michalski4Wei Tan5XiaoRong Qin6YongLiao Zou7State Key Laboratory of Space Weather, National Space Science Center, Chinese Academy of Sciences, Beijing 100190, ChinaDepartment of Earth Sciences and Laboratory for Space Research, The University of Hong Kong, Hong Kong, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaState Key Laboratory of Space Weather, National Space Science Center, Chinese Academy of Sciences, Beijing 100190, ChinaDepartment of Earth Sciences and Laboratory for Space Research, The University of Hong Kong, Hong Kong, ChinaKey Laboratory of Mineralogy and Metallogeny, Guangdong Provincial Key Laboratory of Mineral Physics and Materials, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, ChinaKey Laboratory of Mineralogy and Metallogeny, Guangdong Provincial Key Laboratory of Mineral Physics and Materials, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, ChinaState Key Laboratory of Space Weather, National Space Science Center, Chinese Academy of Sciences, Beijing 100190, ChinaWith the development of the hyperspectral remote sensing technique, extensive chemical weathering profiles have been identified on Mars. These weathering sequences, formed through precipitation-driven leaching processes, can reflect the paleoenvironments and paleoclimates during pedogenic processes. The specific composition and stratigraphic profiles mirror the mineralogical and chemical trends observed in weathered basalts on Hainan Island in south China. In this study, we investigated the laboratory reflectance spectra of a 53-m-long drilling core of a thick basaltic weathering profile collected from Hainan Island. We established a quantitative spectral model by combining the genetic algorithm and partial least squares regression (GA-PLSR) to predict the chemical properties (SiO2, Al2O3, Fe2O3) and index of laterization (IOL). The entire sample set was divided into a calibration set of 25 samples and a validation set of 12 samples. Specifically, the GA was used to select the spectral subsets for each composition, which were then input into the PLSR model to derive the chemical concentration. The coefficient of determination (R2) values on the validation set for SiO2, Al2O3, Fe2O3, and the IOL were greater than 0.9. In addition, the effects of various spectral preprocessing techniques on the model accuracy were evaluated. We found that the spectral derivative treatment boosted the prediction accuracy of the GA-PLSR model. The improvement achieved with the second derivative was more pronounced than when using the first derivative. The quantitative model developed in this work has the potential to estimate the contents of similar weathering basalt products, and thus infer the degree of alteration and provide insights into paleoclimatic conditions. Moreover, the informative bands selected by the GA can serve as a guideline for designing spectral channels for the next generation of spectrometers.http://www.eppcgs.org/article/doi/10.26464/epp2024011?pageType=enreflectance spectroscopyweathered basaltsterrestrial analogquantitative retrievalmars
spellingShingle Xing Wu
JiaCheng Liu
WeiChao Sun
Yang Liu
Joseph Michalski
Wei Tan
XiaoRong Qin
YongLiao Zou
Quantifying the chemical composition of weathering products of Hainan basalts with reflectance spectroscopy and its implications for Mars
Earth and Planetary Physics
reflectance spectroscopy
weathered basalts
terrestrial analog
quantitative retrieval
mars
title Quantifying the chemical composition of weathering products of Hainan basalts with reflectance spectroscopy and its implications for Mars
title_full Quantifying the chemical composition of weathering products of Hainan basalts with reflectance spectroscopy and its implications for Mars
title_fullStr Quantifying the chemical composition of weathering products of Hainan basalts with reflectance spectroscopy and its implications for Mars
title_full_unstemmed Quantifying the chemical composition of weathering products of Hainan basalts with reflectance spectroscopy and its implications for Mars
title_short Quantifying the chemical composition of weathering products of Hainan basalts with reflectance spectroscopy and its implications for Mars
title_sort quantifying the chemical composition of weathering products of hainan basalts with reflectance spectroscopy and its implications for mars
topic reflectance spectroscopy
weathered basalts
terrestrial analog
quantitative retrieval
mars
url http://www.eppcgs.org/article/doi/10.26464/epp2024011?pageType=en
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