Lithological classification using SDGSAT-1 TIS data and three-dimensional spectral feature space model

Thermal infrared (TIR) remote sensing is pivotal in lithological classification due to its diagnostic ability for silicate minerals; however, its application has been partially constrained by limited data availability and insufficient methodological development. In this study, the objective is to ex...

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Main Authors: Qunjia Zhang, Zhenhua Guo, Lei Liu, Jiacheng Mei, Le Wang
Format: Article
Language:English
Published: Taylor & Francis Group 2025-08-01
Series:International Journal of Digital Earth
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Online Access:https://www.tandfonline.com/doi/10.1080/17538947.2025.2467983
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author Qunjia Zhang
Zhenhua Guo
Lei Liu
Jiacheng Mei
Le Wang
author_facet Qunjia Zhang
Zhenhua Guo
Lei Liu
Jiacheng Mei
Le Wang
author_sort Qunjia Zhang
collection DOAJ
description Thermal infrared (TIR) remote sensing is pivotal in lithological classification due to its diagnostic ability for silicate minerals; however, its application has been partially constrained by limited data availability and insufficient methodological development. In this study, the objective is to explore the feasibility of the newly available SDGSAT-1 TIS data in lithological classification and to devise a novel method suitable for the SDGSAT-1 TIS data. Based on radiative transfer and statistical analysis, the Mafic-ultramafic rock Index (MI) and Quartz-bearing rock Index (QI) were deduced and computed using the scatter plots of various bands. Band ratios were formulated based on the spectral characteristics. The 3D spectral feature space was constructed using these derived features to establish classification rules. In the Tianshan-Beishan Cu-Ni metallogenic belt of northwest China, ASTER TIR data were compared with SDGSAT-1 TIS data to assess the performance of derived features, classification effectiveness, and generalizability. The mapping results were validated through field surveys and geological maps. The proposed method could effectively map lithology, particularly mafic-ultramafic intrusions, and SDGSAT-1 TIS excels at identifying veins and small outcrops. This study has expanded the data options for lithological classification and proposed a new method, providing technical support for geological surveys.
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institution Kabale University
issn 1753-8947
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publishDate 2025-08-01
publisher Taylor & Francis Group
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series International Journal of Digital Earth
spelling doaj-art-6725260526c1449ea583b1dfdbbef0d52025-08-25T11:28:43ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552025-08-0118110.1080/17538947.2025.2467983Lithological classification using SDGSAT-1 TIS data and three-dimensional spectral feature space modelQunjia Zhang0Zhenhua Guo1Lei Liu2Jiacheng Mei3Le Wang4School of Earth Science and Resources, Chang’an University, Xi’an, People’s Republic of ChinaFaculty of Geographical Science, Beijing Normal University, Beijing, People’s Republic of ChinaSchool of Earth Science and Resources, Chang’an University, Xi’an, People’s Republic of ChinaSchool of Earth Science and Resources, Chang’an University, Xi’an, People’s Republic of ChinaSchool of Earth Science and Resources, Chang’an University, Xi’an, People’s Republic of ChinaThermal infrared (TIR) remote sensing is pivotal in lithological classification due to its diagnostic ability for silicate minerals; however, its application has been partially constrained by limited data availability and insufficient methodological development. In this study, the objective is to explore the feasibility of the newly available SDGSAT-1 TIS data in lithological classification and to devise a novel method suitable for the SDGSAT-1 TIS data. Based on radiative transfer and statistical analysis, the Mafic-ultramafic rock Index (MI) and Quartz-bearing rock Index (QI) were deduced and computed using the scatter plots of various bands. Band ratios were formulated based on the spectral characteristics. The 3D spectral feature space was constructed using these derived features to establish classification rules. In the Tianshan-Beishan Cu-Ni metallogenic belt of northwest China, ASTER TIR data were compared with SDGSAT-1 TIS data to assess the performance of derived features, classification effectiveness, and generalizability. The mapping results were validated through field surveys and geological maps. The proposed method could effectively map lithology, particularly mafic-ultramafic intrusions, and SDGSAT-1 TIS excels at identifying veins and small outcrops. This study has expanded the data options for lithological classification and proposed a new method, providing technical support for geological surveys.https://www.tandfonline.com/doi/10.1080/17538947.2025.2467983SDGSAT-1ASTERlithological classificationfeature spacespectral indices
spellingShingle Qunjia Zhang
Zhenhua Guo
Lei Liu
Jiacheng Mei
Le Wang
Lithological classification using SDGSAT-1 TIS data and three-dimensional spectral feature space model
International Journal of Digital Earth
SDGSAT-1
ASTER
lithological classification
feature space
spectral indices
title Lithological classification using SDGSAT-1 TIS data and three-dimensional spectral feature space model
title_full Lithological classification using SDGSAT-1 TIS data and three-dimensional spectral feature space model
title_fullStr Lithological classification using SDGSAT-1 TIS data and three-dimensional spectral feature space model
title_full_unstemmed Lithological classification using SDGSAT-1 TIS data and three-dimensional spectral feature space model
title_short Lithological classification using SDGSAT-1 TIS data and three-dimensional spectral feature space model
title_sort lithological classification using sdgsat 1 tis data and three dimensional spectral feature space model
topic SDGSAT-1
ASTER
lithological classification
feature space
spectral indices
url https://www.tandfonline.com/doi/10.1080/17538947.2025.2467983
work_keys_str_mv AT qunjiazhang lithologicalclassificationusingsdgsat1tisdataandthreedimensionalspectralfeaturespacemodel
AT zhenhuaguo lithologicalclassificationusingsdgsat1tisdataandthreedimensionalspectralfeaturespacemodel
AT leiliu lithologicalclassificationusingsdgsat1tisdataandthreedimensionalspectralfeaturespacemodel
AT jiachengmei lithologicalclassificationusingsdgsat1tisdataandthreedimensionalspectralfeaturespacemodel
AT lewang lithologicalclassificationusingsdgsat1tisdataandthreedimensionalspectralfeaturespacemodel