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Turkish Journal of Earth Sciences

Abstract

Accurate lithological mapping requires selecting the appropriate remote sensing data and classification methods. This study evaluates the performance of four satellite datasets—Landsat 8 OLI, Sentinel-2A, ASTER, and Hyperion EO-1—using three spectral classification techniques: Matched Filtering (MF), Spectral Angle Mapper (SAM), and Spectral Information Divergence (SID). The study area is located between the Zara and Koyulhisar districts in eastern Türkiye and comprises diverse lithological units. A total of 49 rock samples collected in the field were used for validation. The results indicate that MF consistently outperformed the other methods, achieving the highest accuracy with Landsat 8 (Kappa = 94.2%). ASTER data demonstrated strong capability in distinguishing lithologies with subtle spectral differences, particularly due to its SWIR bands. Meanwhile, Sentinel-2A provided improved spatial delineation. Despite its high spectral resolution, Hyperion showed limited performance in separating spectrally similar units. Misclassification was primarily associated with lithologies that had similar mineralogical compositions and terrain-related effects. The results demonstrate the efficacy of MF in conjunction with multispectral data for lithological mapping and underscore the significance of selecting suitable data–method combinations in geologically complex regions.​

Author ORCID Identifier

ÖNDER GÜRSOY: 0000-0002-1531-135X

EMRE ÖZELKAN: 0000-0002-2031-1610

RUTKAY ATUN: 0000-0001-9959-2058

AYŞE ÇALIŞKAN: 0000-0001-7724-6664

AHMET EFE: 0000-0002-5989-4753

DOI

10.55730/1300-0985.2020

Keywords

Remote sensing, spectral classification, lithology, ASTER, Hyperion, Landsat

First Page

303

Last Page

317

Publisher

The Scientific and Technological Research Council of Türkiye (TÜBİTAK)

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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