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With the exploitation of rare earth elements (REE) in southern China, desertification has become a serious ecological problem in this region. To accurately understand the desertification process in mining areas and formulate targeted ecological restoration programs, taking the Lingbei mining area in Ganzhou City, Jiangxi Province as the study area, we explored desertification information extraction methods, desertification dynamics monitoring, and desertification drivers in REE mining areas using multisource data from 1986 to 2021. The results show that from the method of extracting desertification information, Random Forest is the prominent (83.33%), followed by Albedo–NDVI (Normalized Difference Vegetation Index) space (74.44%), and thirdly Linear Spectral Mixture Model (65.56%). From 1986 to 2021, the desertification land area in Lingbei mining areas first increased and then decreased, showing a reverse trend, but it has not recovered to the pre‐mining level. The government's ecological reclamation measures are the key factors for the restoration of desertification land. There are still 17.81 km2 areas that have not been restored, of which 2.16 km2 are at the level of severe desertification. Moderate desertification and light desertification have not been completely curbed, which needs continuous attention. Vegetation coverage has the highest explanatory power to the distribution of land desertification in mining areas, followed by land use classification, indicating that human activities have a great influence on the spatial differentiation of land desertification in mining areas, and it is necessary to pay attention to regional balanced and sustainable development in the future. [ABSTRACT FROM AUTHOR]

Quantitative evaluation of ecological restoration effectiveness is critical to provide operational feedback for mine restoration and to implement adaptive management. Existing practice are limited by a focus on single elements and sub-project scales. This paper proposed an ecological restoration evaluation framework with 8 dimensions and 24 indicators from macro perspective, taking a mineral concentration area (MCA) in southeastern Hubei as a case study. LandTrendr and random forest algorithms were used to extract and classify different ecological disturbances around the mine sites from micro perspective. The ecological restoration process and disturbances were revealed at different scales. The findings demonstrated that the total ecological restoration area increased by 10.092% from 2010 to 2019, showing an improving trend, but it has not recovered to the ecological level of 2000. The ecologically degraded areas were shifting to the urban areas with concentrated population and around the water, from area diffusion to strip extension. Ecological disturbances changes in mining areas shows there was a trend towards slower ecological restoration of mine sites after 2019. Disturbances due to construction development occurred in areas surrounding closed mining areas, especially in Huangshi National Mine Park and Tonglvshan Copper Mine. Notably, natural restoration occurred in mine-forest compound area without any ecological restoration measures. While the findings demonstrate the effectiveness of ecological engineering, there are still some limitations in the mine ecological restoration process. In response, we suggest an international framework for ecological restoration in mining areas to solve the cognitive gaps in ecological engineering, improve the management of the whole process of ecological restoration, and optimize the ecological restoration effect in mining areas. [Display omitted] • An ecological restoration assessment framework at macro perspective was proposed. • Different disturbance and recovery types in 3-km buffer were analyzed. • The ecological disturbance and restoration characteristics were analyzed in different typical mining areas. [ABSTRACT FROM AUTHOR]