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• Identify the vegetation patterns of a landslide after 5 years natural restoration in the Loess Plateau mining area. • Analyze differences in plant diversity and similarity between the bottom, middle and top of the landslide. • Design an experiment to test the vitality of soil seed bank in the landslide. • Discuss the effect of changes in topography on revegetation. Landslides represent the most intense type of geological disaster in the gully region of the Loess Plateau and have caused great damage to surface vegetation. Natural restoration is considered as an effective method for revegetation, however, vegetation patterns on landslides after natural restoration and its related factors remain poorly understood. The present study investigated vegetation patterns on a landslide after 5 years of natural restoration, which located in Hezhai coal mining area, Shanxi Province, China, to understand the natural restoration of vegetation after landslides. The species composition on the bottom, middle and top of the landslide, as well as the species importance value, plant diversity and similarity were ascertained and compared with the that on undisturbed site. Furthermore, the soil seed bank in another landslide which just experienced 0.5-year natural restoration was also investigated, and a seed bank germination experiment was performed based on the collected seed samples from the landslide to test their vitalities. Results showed that 20 species of vegetation were found on all three parts of the landslide, which all belonged to herbaceous plants and shrubs. Eleusine indica was dominant in both the bottom and middle of the landslide, while the top was dominated by Potentilla sischanensis. From the bottom to the top of landslide, the Margalef Index was 3.26, 3.91, and 2.17 respectively; the Shannon–Wiener Index was 2.56, 2.60, and 2.13 respectively; the Pielou Index was 0.55, 0.56, and 0.46, respectively. Species similarity revealed a close relationship between species compositions on restored landslide and undisturbed area. A total of 13 species of seeds were found in the soil seed bank, which were also similar to the aboveground plants on disturbed site and the landslide after 5-year natural restoration, and the seed was also proved vital in the seed bank experiment. These results indicated that vegetation on landslides could recovery naturally, and natural restoration was more effective on the bottom and middle of the landslide, which revealed that changes in topography could affect revegetation. The seed bank in the soil was considered as a main factor affecting natural restoration. This research provides useful insight into the natural restoration of vegetation after landslides, and provides a reference for the selection of ecological restoration strategies. [ABSTRACT FROM AUTHOR]

Understanding the changes in a land use/land cover (LULC) is important for environmental assessment and land management. However, tracking the dynamic of LULC has proved difficult, especially in large-scale underground mining areas with extensive LULC heterogeneity and a history of multiple disturbances. Additional research related to the methods in this field is still needed. In this study, we tracked the LULC change in the Nanjiao mining area, Shanxi Province, China between 1987 and 2017 via random forest classifier and continuous Landsat imagery, where years of underground mining and reforestation projects have occurred. We applied a Savitzky–Golay filter and a normalized difference vegetation index (NDVI)-based approach to detect the temporal and spatial change, respectively. The accuracy assessment shows that the random forest classifier has a good performance in this heterogeneous area, with an accuracy ranging from 81.92% to 86.6%, which is also higher than that via support vector machine (SVM), neural network (NN), and maximum likelihood (ML) algorithm. LULC classification results reveal that cultivated forest in the mining area increased significantly after 2004, while the spatial extent of natural forest, buildings, and farmland decreased significantly after 2007. The areas where vegetation was significantly reduced were mainly because of the transformation from natural forest and shrubs into grasslands and bare lands, respectively, whereas the areas with an obvious increase in NDVI were mainly because of the conversion from grasslands and buildings into cultivated forest, especially when villages were abandoned after mining subsidence. A partial correlation analysis demonstrated that the extent of LULC change was significantly related to coal production and reforestation, which indicated the effects of underground mining and reforestation projects on LULC changes. This study suggests that continuous Landsat classification via random forest classifier could be effective in monitoring the long-term dynamics of LULC changes, and provide crucial information and data for the understanding of the driving forces of LULC change, environmental impact assessment, and ecological protection planning in large-scale mining areas. [ABSTRACT FROM AUTHOR]