Opencast iron mine and mine solid waste (OIM-MSW) are closely associated with a wide range of environmental issues, such as destroying soil structure, affecting air quality, and damaging biodiversity. Therefore, accurately grasping the distribution of OIM-MSW is of great significance to monitoring and managing environmental conditions. In order to reduce the impact of background features on the identification of OIM-MSW, we constructed an index based on medium spatial resolution satellite data, and proposed a semiautomatic method to determine the threshold value of the index. Experimental results indicated that: 1) The proposed index (OIM-MSWI) can effectively identify the OIM-MSW of which the OA (overall accuracy) and K (kappa coefficient) value are 0.98 and 0.75, respectively. 2) The index owns satisfying performance in identifying OIM-MSW in different months, and its recognition ability in plant growing season is better than that in the nonplant growing season. 3) Both Landsat 8 images and Sentinel 2 images have the potential to identify OIM-MSW via the proposed index, but the recognition accuracy of Landsat 8 images (OA = 0.98, K = 0.75) is slightly better than Sentinel 2 images (OA = 0.96, K = 0.64). (4) OIM-MSWI is effective in different climatic conditions, with OA and K of 0.98, 0.75 and 0.97, 0.63 in the cases of semiarid and humid zones, respectively. In conclusion, OIM-MSWI is a simple and effective index for identifying OIM-MSW, and can provide support for OIM-MSW monitoring and management.