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.

Waste pickers (WPs) play an indispensable role by helping to control municipal solid waste (MSW). However, they constitute the entry-level workforce of the waste recycling industry and receive little attention from the general public. In China, approximately 4 million WPs make their living by collecting MSW recyclable materials. To assess the role of WPs, an extensive social survey including urban management decision-makers, recycling industrial circle insiders, WPs, as well as common citizen respondents has been conducted in the city of Nanjing, China. The results confirmed that 70–80% of recyclable MSW materials were collected by WPs in the informal sector, which are an integral component of the waste recycling system. In Nanjing, the recyclable material collected annually by WPs is about 505,000 tons, which creates annual economic value of about 78.6–84.7 million USD. However, WPs account for only 6.8–7.3% of the entire industrial chain of the recycling economy. In Nanjing, WPs are able to save an annual MSW disposal cost of about 17.6–22.0 million USD. The resource recovery rate is also increased by 1.9–8.0%. The survey results support the experience of establishing a community-based semi-official picker organizational framework, accompanied by relevant laws, regulations, and preferential policies that would improve the resource recovery rate and pickers’ living and working conditions in order to achieve more effective and hazard-free MSW resource utilization. It is anticipated that the results of this research will be instrumental for the improvement of the MSW recycling system and WP management in other cities in China and other developing countries.