| Abstract: | The precision of Aster data is higher than that of Landsat series of multispectral remote sensing data, which can more accurately reveal the distribution of altered minerals. It plays an important role in prospecting, but it is rarely used in areas with complex terrain and high vegetation coverage. Based on this purpose, this study used Aster remote sensing data, and took Gongchangling iron deposit as a case study. It combined the mineral spectrum theory and the basic geologic data of the study area, using the model of principal component analysis (PCA) and color synthesis to extract abnormal altered minerals. The results show that the distribution of identified anomalies is basically consistent with the existing geological data in this study area, which provides a reliable reference for the mineral resources ex-ploration and delineation of mining areas. |
