<b>Rapid Lithological Mapping Using Multi-Source Remote Sensing Data Fusion and Automatic Sample Generation Strategy</b> حسب Tao Zhang (21914624)

"…Using various machine learning algorithms, we evaluated the classification capabilities of heterogeneous predictive factors, feature optimization algorithms, and object-based algorithms. Results indicate that: (1) Combining optical and radar data improves prediction accuracy, with terrain data further enhancing mapping capabilities; (2) Terrain factors contribute most to classification, but SWIR and TIR bands of optical data are critical for lithological identification; (3) The feature optimization algorithm reduces feature redundancy and efficiency issues from multi-source data, achieving 96.51% accuracy with the optimal feature model, an improvement of 0.1%-2.02% over original features; (4) Object-based algorithms show significant potential in mapping areas with large rock outcrops. …"