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This study focuses on the iron ore of Taxkorgan and Heiqia in the West Kunlun mountains as a case study, for the application of WorldView−2 and IKONOS remote sensing images as major data sources in the fabrication of a standard image map and in the adoption of image enhancement methods to extract information on the ore-controlling factors and mineralization, to interpret remote sensing for the mineral resources in these areas. ASTER, WorldView−2, and IKONOS data were applied for the extraction of alteration anomaly information. With an appropriate amount of field sampling and verification tests, this was used to establish a remote sensing geology prospecting model, that would provide the basis for future remote sensing of metallogenic belts in West Kunlun in the hope of discovering similar minerals. Survey results showed four additional iron ore mineralization belts could be delineated in the Taxkorgan area. A comparative analysis conducted for part of the field confirmation and the known mineral deposits indicated good reliability. In Heiqia, a siderite-haematite mineralization zone was observed with copperlead- zinc formation, 60-km in length and 200–500 m wide, which includes several mineralized bodies. The ore bodies, appear as stratoid, lenticular, or podiform morphologies and were located in the transition site from clastic to carbonate rocks of the D segment in the Wenquangou Group. The ore bodies generally occur within 40°–50° strike and 68°–81° dip, in accordance to the strata. The length of the single body varies from several hundred metres to more than 9500 m. Its exposed thickness on the surface ranges from 2–50 m, and the general thickness was approximately 15 m. The surface ore minerals were mainly haematite and limonite, with a small amount of siderite. Therefore, high-resolution remote sensing technology is suitable for iron ore geological and mineral remote sensing surveying. It is advantageous in both high-ground resolution of optical characteristics and a certain spectral recognition capability, and is effective not only for information extraction from a large area, but also for recognition of local mineralization outcrops. Therefore, high-resolution remote sensing technology is valuable for popularization.
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