Hyperspectral Mapping of Alunite Mineral in Chh.Sambhajinagar District: Using Remote Sensing, Field Spectroscopy, and GIS Techniques for Accurate Identification District

This study focuses on the identification and mapping of Alunite mineral deposits in Chhatrapati Sambhajinagar using hyperspectral remote sensing and geospatial techniques. Hyperspectral data enables detailed analysis of spectral signatures, particularly in the SWIR region, where Alunite shows distinct absorption features. Preprocessing steps such as atmospheric and radiometric corrections ensure accurate data quality. The Spectral Angle Mapper (SAM) algorithm is used to compare image spectra with USGS spectral library data, allowing precise mineral classification. The results are visualized through false-color composite maps, highlighting Alunite-rich zones within the study area. GIS integration further enhances spatial interpretation by linking mineral distribution with geological and environmental factors. This approach provides a reliable, efficient, and cost-effective method for mineral exploration, resource assessment, and environmental monitoring.