Surface Clay and Mineral Exploration Using Hyperspectral Imaging: Advanced Techniques for Geospatial Analysis
Keywords: Mineral Mapping, Minimum Noise Fraction, Spectral Analyst, Spectral Angle Mapper
Abstract. This research investigates the application of hyperspectral imaging (HSI) for surface clay and mineral exploration, specifically targeting kaolin, hematite, saponite, and illite in the Udaipur region of Rajasthan, India an area known for its complex and diverse mineralogy. Traditional approaches such as geological mapping, geochemical assays, and field surveys, while fundamental, often prove inefficient in terms of time and resources, especially in the challenging topography of the Aravalli Range. HSI, leveraging data from the Hyperion sensor, offers a fine-resolution remote sensing method capable of discriminating minerals through their unique spectral reflectance profiles. The study employs advanced HSI processing techniques, including Minimum Noise Fraction (MNF) transformation for noise reduction and feature space optimization, and Pixel Purity Index (PPI) for endmember extraction, followed by mineral classification using Spectral Angle Mapper (SAM). A detailed pre-processing workflow is implemented, involving atmospheric correction, radiometric calibration, and the generation of endmember spectra based on USGS mineral spectra of key minerals. SAM is used to classify mineralogical components by computing the spectral angle between the pixel spectra and the known spectral profiles. Results demonstrate that this integrated approach—combining HSI with MNF, PPI, and SAM algorithms significantly enhances the accuracy and precision of clay and mineral detection, specifically identifying clay kaolinite, illite, saponite, and hematite, along with their spatial distribution within the study area. This methodology offers a scalable, cost-effective, and highly reliable solution for mineral exploration, particularly for identifying surface clay minerals and other mineral resources in geologically complex regions such as Udaipur. The study's findings not only enhance the understanding of mineral resources in the Udaipur region but also highlight the potential of HSI in climate change research. By providing precise data on mineral distribution and soil composition, HSI can be a valuable tool for creating adaptive land-use strategies, supporting sustainable agriculture, and mitigating the impacts of climate change, ultimately contributing to more resilient ecosystems and informed decision-making in geospatial research and sustainable development.