基于GF-5高光谱数据的白云岩找矿应用研究OA

Based on domestic GF-5 hyperspectral remote sensing data,a study on dolomite identification and prospecting prediction was carried out in the Weiya-Tianhu area of the eastern Tianshan Mountains in Xinjiang.Taking advantage of the well-exposed bedrock in the region,preprocessing steps such as radiometric calibration and atmospheric correction were applied.SWIR bands were selected for dimensionality reduction,and dolomite information was accurately extracted using a combination of optimal spectral selection and an integrated spectral shape-absorption position collaborative matching algorithm.Comparative analysis with mining areas such as Hengshan and southwestern Weiya showed that high-confidence identification zones highly coincide with the distribution of known ore bodies,while low-confidence zones correspond to marginal low-grade dolomite,verifying the reliability of the extraction results.Based on the analysis of metallogenic horizons and remote sensing identification results,a favorable prospecting area of 6.8 km2 was delineated.This study preliminarily confirms the effectiveness of GF-5 data in direct dolomite prospecting in shallow coverage areas and provides a reference for the application of hyperspectral remote sensing in non-metallic mineral exploration.