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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Bibliographic Details
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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Summary: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.
ISSN:1753-8947
1753-8955