Akademik Veri Yönetim Sistemi
TURKISH JOURNAL OF EARTH SCIENCES, cilt.35, sa.3, ss.303-317, 2026 (SCI-Expanded)
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.