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

TitleQuantifying the chemical composition of weathering products of Hainan basalts with reflectance spectroscopy and its implications for Mars
Authors
KeywordsMars
quantitative retrieval
reflectance spectroscopy
terrestrial analog
weathered basalts
Issue Date1-Nov-2024
PublisherScience Press
Citation
Earth and Planetary Physics, 2024, v. 8, n. 6, p. 854-867 How to Cite?
Abstract

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.


Persistent Identifierhttp://hdl.handle.net/10722/359174
ISSN
2023 Impact Factor: 2.5
2023 SCImago Journal Rankings: 0.674

 

DC FieldValueLanguage
dc.contributor.authorWu, Xing-
dc.contributor.authorLiu, Jia Cheng-
dc.contributor.authorSun, Wei Chao-
dc.contributor.authorLiu, Yang-
dc.contributor.authorMichalski, Joseph-
dc.contributor.authorTan, Wei-
dc.contributor.authorQin, Xiao Rong-
dc.contributor.authorZou, Yong Liao-
dc.date.accessioned2025-08-23T00:30:25Z-
dc.date.available2025-08-23T00:30:25Z-
dc.date.issued2024-11-01-
dc.identifier.citationEarth and Planetary Physics, 2024, v. 8, n. 6, p. 854-867-
dc.identifier.issn2096-3955-
dc.identifier.urihttp://hdl.handle.net/10722/359174-
dc.description.abstract<p>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.</p>-
dc.languageeng-
dc.publisherScience Press-
dc.relation.ispartofEarth and Planetary Physics-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectMars-
dc.subjectquantitative retrieval-
dc.subjectreflectance spectroscopy-
dc.subjectterrestrial analog-
dc.subjectweathered basalts-
dc.titleQuantifying the chemical composition of weathering products of Hainan basalts with reflectance spectroscopy and its implications for Mars-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.26464/epp2024011-
dc.identifier.scopuseid_2-s2.0-85209246445-
dc.identifier.volume8-
dc.identifier.issue6-
dc.identifier.spage854-
dc.identifier.epage867-
dc.identifier.issnl2096-3955-

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