mineral prospectivity mapping using clustering methods in kariz now 1:100,000 sheet, razavi khorasan, iran

The increasing demand for mineral resources necessitates the development of efficient exploration strategies, particularly through mineral prospectivity mapping (mpm). this study focuses on identifying potential areas for copper (cu) mineralization in the kariz now region of northeastern iran by employing clustering techniques. we applied three clustering methods including mean-shift, hierarchical, and birch to analyze a comprehensive dataset that includes geological, geochemical, geophysical, and remote sensing information. each method s effectiveness in predicting mineral anomalies was evaluated to undestand their relative performance. the findings indicate that birch clustering significantly outperformed the other methods in terms of precision and reliability. this work highlights the advantage of using clustering techniques in enhancing mpm, facilitating the discovery of mineralization potential through the integration of diverse data sources. the study ultimately encourages further exploration efforts and detailed geophysical surveys in the identified high-potential areas to validate the presence of mineral deposits.