Glaciers are extremely sensitive to climate change. And glacier changes have great impacts on the regional climate, ecology, water resources and so on. Remote sensing images are often used to study glacial changes. For plateau mountainous areas, the images usually have a larger area of the mountain shadows. Shadows cause loss or distraction of the information reflected by the ground target, making remote sensing image difficult to understand. Therefore, the identification of glaciers in the mountain shadow area based on remote sensing images becomes a technical difficulty. In this study, a large mountain glacier on the Qinghai-Tibet Plateau was chosen as experimental subject. Based on Landsat 8 OLI data, this study first analyzed the reflection characteristics of different bands for glacier and non-glacier in shadow area. The results showed that due to the fact that direct light is blocked and target objects in a shadow area are mainly irradiated by the scattered light, the blue band which has shorter wavelength and higher intensity of the scattered light is preferred band for glacier identification in shaded area. For longer wavelength band, the reflectance of ground target in the entire shadow region is very low, and it is difficult to distinguish between glaciers or non-glacial regions. On this basis, a shaded glacier information enhanced index is proposed. Compared with the conventional glacier information extraction methods, the proposed method can give a result to identify the segmentation threshold more clearly in the histogram; and get the best result both in accuracy of the extracted boundary and the total area. For large-scale glacier extractionin the plateau mountainous area, it is recommended to use the proposed method which can be helpful in improving the overall work efficiency.