Geostructural Investigation of the Lugiin Gol Area Using Optical and Microwave Remote Sensing

This study aims to investigate the geostructural characteristics of the Lugiin Gol area through the integration of optical and microwave remote sensing (RS) data. To achieve this objective, a combination of image enhancement techniques was applied to multisource RS datasets to improve the discrimination of lithological units and geostructures. The results demonstrate that synthetic aperture radar (SAR) data are particularly effective for detecting structural features, such as faults and lineaments, whereas multispectral imagery provides valuable information for identifying lithological variability and alteration zones based on spectral reflectance characteristics. Image enhancement approaches, including false color composite (FCC) generation, contrast stretching, band ratioing, and spatial filtering, significantly improved the visual interpretation and delineation of geological features. In addition, advanced transformation techniques, namely principal component analysis (PCA) and minimum noise fraction (MNF), were employed to extract supplementary spatial and spectral information from the datasets. Among these methods, the MNF transformation demonstrated superior performance in noise reduction and the enhancement of geological patterns. The integrated analysis enabled clearer identification of geostructural features, lithological boundaries, and possible subsurface intrusions within the study area. Overall, the findings indicate that the integration of optical and microwave RS data, combined with advanced image processing techniques, provides a reliable and effective framework for comprehensive geostructural investigation, while also supporting environmental assessment, land-use planning, and informed decision-making in geologically complex regions.