Abstract—Exploitation of mine resources has great damage to the earth surface and has impact on the regional ecological environment, which led to serious land collapse, soil degradation, vegetation damage and so on. Land cover distribution and change can directly reflect the ecological status of mining region. Therefore, this paper presented a framework to obtain more detailed classification results and monitor land cover change of mining city using multi-temporal high spatial resolution remote sensing images. The presented method had two major steps. First, the multi-temporal remote sensing images were classified by object-oriented semi-automatic classification method. Second, the spatial distribution and change of land cover were analyzed based on multi-temporal classification results. The Liaoning Anshan Iron Ore of Northeast China was selected as the study area. Two temporal high spatial resolution remote sensing images spanning ten years were collected, including ALOS, SPOT-2 and Landsat-7. The experimental results showed that multi-temporal high spatial resolution remote sensing images can be effectively used to monitor the land cove change of mining city. The land cover of Anshan had great changes over the ten years. The mining, building and bare land area increased. The arable land and grassland area decreased, and the forest land area remained stable. From the change of land cover distribution and types, the ecological quality of Liaoning Anshan was declined with mining and urbanization.