Enhancing Geological Insights: The Evolution of Mineral Exploration Using OLI and ASTER Sensors

The advancement of mineral exploration has been significantly influenced by technological innovations, particularly through the integration of remote sensing techniques. This paper examines the transformative role of the Operational Land Imager (OLI) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensors in enhancing geological insights and mineral resource identification. OLI, aboard the Landsat-۸ satellite, and ASTER, on the Terra satellite, provide high-resolution multispectral imagery that facilitates detailed geological mapping, lithological identification, and detection of hydrothermal alteration zones. The unique capabilities of these sensors allow for the effective discrimination of various mineral groups and alteration patterns, which are critical for successful mineral exploration. The study highlights the application of advanced data processing techniques, such as Principal Component Analysis (PCA), Spectral Angle Mapping (SAM), and Linear Spectral Unmixing (LSU), which enhance the analysis of remote sensing data. These methodologies enable the identification of subtle mineralogical changes and the mapping of alteration halos around mineral deposits, thereby improving target generation and exploration accuracy. Furthermore, the integration of OLI and ASTER data with geophysical and geochemical information supports a more comprehensive understanding of geological features, ultimately leading to more efficient and sustainable exploration practices. As global demand for mineral resources continues to rise, the need for innovative and environmentally responsible exploration techniques becomes increasingly critical. The findings presented in this paper underscore the effectiveness of remote sensing technologies in identifying mineralization potential across diverse geological settings, while also promoting sustainable resource management. The ongoing evolution of these technologies, coupled with advancements in data processing and machine learning, promises to further enhance the capabilities of mineral exploration, paving the way for a more sustainable future in resource extraction.

کلیدواژه ها:

OLI ، ASTER ، Remote Sensing (RS) ، Mineral Exploration ، Principal Component Analysis (PCA)