The northern Chifeng region of Inner Mongolia contains abundant lead-zinc, silver, tin, tungsten, copper, lithium, beryllium, niobium,tantalum, molybdenum, and iron resources, making it significant in the nonferrous metal-rare metal-silver metallogenic belt of the southern GreatXing'an Range. Previous studies have conducted extensive geological, geophysical, geochemical, remote sensing, and mineral resource surveys in thesouthern Great Xing'an Range, particularly in the Chifeng area. However, there is still a lack of effective prospecting methods for shallow overburdenareas. Considering the metallogenic geological background and spatial distribution patterns of deposits in this region, this study employed multi-sourceremote sensing technology to extract mineralization alteration in Hexigten Banner and Linxi County, northern Chifeng. Multispectral data (Landsat-8,ASTER) were used to extract alteration of different mineral types through principal component analysis. For GF-5 data, the mixed-tuned matchedfiltering technique was applied to extract mineralization alteration. The results from the three remote sensing methods were then integrated forcomprehensive analysis to delineate prospective metallogenic targets. We also conducted field verification, further advancing the application of remote sensing in geological and mineral resource exploration. Based on Landsat-8 and ASTER multispectral data, iron-stained and hydroxyl-bearing (Mg-OH, Al-OH) mineral information was extracted. Three alteration minerals of muscovite, epidote, and kaolinite were identified based on the GF-5 data.Field verification confirmed that the remote sensing extraction results corresponded well with actual alteration anomalies, and tin-copper-silver-leadzincmineralization was discovered within the delineated target areas. This study, by combining extraction and overlay results from different data sourcesand validating them through field surveys, demonstrates the accuracy of the remote sensing methods used for mineralization alteration extraction. Theintegration of multispectral and hyperspectral remote sensing data facilitates subsequent alteration zoning analysis and more precise metallogenicprediction, thereby better serving mineral resource exploration and related fields.

multi-source remote sensing data, alteration information extraction, principal component analysis, hybrid tuned matched filtering,Chifeng area, Inner Mongolia