Under the ecological restoration project, the vegetation in the mining area shows a significant improvement trend. Exploring the causal relationship among the implementation of ecological restoration projects in mining areas, vegetation restoration, and the improvement of ecosystem service functions is of great significance for the current green development of coal mines. Therefore, in this study, we used the kernel Normalized Vegetation Index (kNDVI) to measure how vegetation growth has changed since ecological restoration projects began. Changes in four major ecosystem service functions, including soil conservation, net primary productivity (NPP), water yield, and habitat quality, were assessed before and after the restoration projects. The relationship between kNDVI and ecosystem services was further discussed by using the constraint line method. The results show the following: (1) Under the implementation of ecological restoration projects from 1994 to 2022, the annual vegetation growth rate in the mining area has progressively risen each year at a rate of 0.0046/a. Spatially speaking, 90.44% of the mining area had a substantial upward trend, indicating clear evidence of vegetation restoration. (2) Under the scientific ecological restoration of the mining areas, the total ecosystem service index increased from 0.41 in 1994 to 0.49 in 2022. The functions of ecosystem services have been enhanced to differing extents. (3) KNDVI’s constraint effect on the four ecosystem services changed dramatically before and after the ecological restoration effort. After the ecological restoration project, kNDVI’s constraint on ecosystem services decreased. (4) After restoration, the threshold value of kNDVI for maximizing the benefits of the four ecosystem services ranges from 0.1 to 0.2, and the constraint on the total ecosystem services reaches the threshold value of 0.225. This study employs more comprehensive data to examine the intricate relationship between environmental change and service function, which is crucial for the scientific management of ecological processes and facilitates the sustainable green development of mining areas.

The Shendong Mining Area, being the largest coal base in the world, has significant challenges in the intensive development and utilization of coal resources, as well as the impact of a dry climate, which can have serious negative effects on the growth of flora in the region. Investigating the spatial and temporal patterns of how meteorological drought affects vegetation in the Shendong Mining Area at various time scales can offer a scientific foundation for promoting sustainable development and ecological restoration in the region. This study utilizes the Standardized Precipitation Evapotranspiration Index (SPEI) and Normalized Difference Vegetation Index (NDVI) data from 1986 to 2020 in the Shendong Mining Area. It employs Slope trend analysis, a Mann–Kendall test, a Geographic Detector, and other methods to examine the spatiotemporal distribution characteristics of meteorological drought at various time scales. Additionally, the study investigates the influence of these drought patterns on vegetation growth in the Shendong Mining Area. Across the mining area, there was a general decrease in the monthly average SPEI on an annual basis. However, on a seasonal, semi-annual, and annual basis, there was a gradual increase in the annual average SPEI, with a higher rate of increase in the southern region compared to the northern region. When considering the spatial variation trend in different seasons, both positive and negative trends were observed in winter and summer. The negative trend was mainly observed in the western part of the mining area, while the positive trend was observed in the eastern part. In spring, the mining area generally experienced drought, while in autumn, it generally experienced more precipitation. The mining area exhibits a prevailing distribution of vegetation, with a greater extent in the southeast and a lesser extent in the northwest. The vegetation coverage near the mine is insufficient, resulting in a low NDVI value, which makes the area prone to drought. Over the past few years, the mining area has experienced a significant increase in vegetation coverage, indicating successful ecological restoration efforts. Various forms of land use exhibit distinct responses to drought, with forests displaying the most positive correlation and barren land displaying the strongest negative correlation. Various types of landforms exhibit varying responses to drought. Loess ridge and hill landforms demonstrate the most pronounced positive association with monthly-scale SPEI values, whereas alluvial and floodplain landforms display the poorest positive correlation with yearly scale SPEI values. The general findings of this research can be summarized as follows: (1) The mining area exhibits a general pattern of increased humidity, with the pace of humidity increase having intensified in recent times. Seasonal variations exhibit consistent cyclic patterns. (2) There are distinct regional disparities in NDVI values, with a notable peak in the southeast and a decline in the northwest. The majority of the mining area exhibits a positive trend in vegetation recovery. (3) Regional meteorological drought is a significant element that influences changes in vegetation coverage in the Shendong Mining Area. Nevertheless, it displays complexity and is more obviously impacted by other factors at a small scale. (4) It should be noted that forests and barren land exert a more significant influence on SPEI values, despite their relatively lesser spatial coverage. The predominant land use type in most locations is grasslands; however, they have a relatively minor influence on SPEI. (5) A shorter time period, higher elevation, and steeper slope gradient all contribute to a larger correlation with drought.

Vegetation indices are important representatives of plant growth. Climate change and human activities seriously affect vegetation. This study focuses on the Huojitu mining area in the Shendong region, utilizing the kNDVI index calculated via the Google Earth Engine (GEE) cloud platform. The Mann–Kendall mutation test and linear regression analysis were employed to examine the spatiotemporal changes in vegetation growth over a 25-year period from 1999 to 2023. Through correlation analysis, geographic detector models, and land use map fusion, combined with climate, topography, soil, mining, and land use data, this study investigates the influencing factors of vegetation growth evolution. The key findings are as follows: (1) kNDVI is more suitable for analyzing vegetation growth in this study compared to NDVI. (2) Over the past 25 years, vegetation growth has exhibited an overall fluctuating upward trend, with an annual growth rate of 0.0041/a. The annual average kNDVI value in the mining area is 0.121. Specifically, kNDVI initially increased gradually, then rapidly increased, and subsequently declined rapidly. (3) Vegetation growth in the study area has significantly improved, with areas of improved vegetation accounting for 89.08% of the total mining area, while degraded areas account for 11.02%. (4) Precipitation and air temperature are the primary natural factors influencing vegetation growth fluctuations in the mining area, with precipitation being the dominant factor (r = 0.81, p < 0.01). The spatial heterogeneity of vegetation growth is influenced by land use, topography, soil nutrients, and mining activities, with land use having the greatest impact (q = 0.43). Major land use changes contribute 46.45% to vegetation improvement and 13.43% to vegetation degradation. The findings of this study provide a scientific basis for ecological planning and the development of the Huojitu mining area.

Underground coal mining in coal-grain overlapped areas leads to land subsidence and deformation above the goaf, damaging cultivated land. Understanding the influencing process of coal mining on cultivated land and crops is important for carrying out timely land reclamation and stabilizing crop yield. Research has been carried out by using crop growth parameters to evaluate the damaging degree of cultivated land when the mining subsidence is stable, but few studies focus on the influence of land damage on crop growth when the subsidence is unstable during coal mining. Therefore, this study tracked the three growth stages of winter wheat by using UAV multispectral imagery to explore the dynamic influence of underground mining on winter wheat aboveground biomass (AGB). Firstly, a winter-wheat-AGB estimation model (R² = 0.89, RMSE = 2.18 t/ha) was developed by using vegetation indexes (VIs), textures, and terrain data extracted from UAV imagery. Secondly, based on the winter-wheat-AGB estimation model, the winter wheat AGB was successfully estimated and mapped at different growth stages. The AGB of winter wheat in the coal mining-affected area was approximately 5.59 t/ha at the reviving stage, 8.2 t/ha at the jointing stage, and 15.6 t/ha at the flowering stage. Finally, combined with the progress of coal mining, the dynamic changing process of crops during underground mining can be inferred by analyzing the spatiotemporal variation in winter wheat AGB. Results showed that, in the dip direction, winter wheat AGB at the flowering stage was the highest at the compression zone, followed by the inner stretch zone, outer stretch zone, and neutral zone. The distance from the waterlogged area and the existence of cracks were found to be the important moderating variables affecting the crop growth status in the mining subsidence area. In the strike direction, there were significant differences in the wheat AGB-affected area as the mining proceeded. Even areas where AGB had previously significantly increased gradually transitioned to significant decreases with the end of mining. The research explores the dynamic changes in winter wheat AGB and land damage status during coal mining. It provides a rapid and non-destructive land-damage-monitoring method to protect cultivated land in mining areas.

Elucidating the response mechanism of vegetation change trends is of great value for environmental resource management, especially in coal mining areas where climate fluctuations and human activities are intense. Taking the Shendong mining area as an example, based on the Google Earth Engine cloud platform, this study used the kernel Normalized Vegetation Index (kNDVI) to study the spatiotemporal change characteristics of vegetation cover during 1994–2022. Then, it carried out an attribution analysis through the partial derivative analysis method to explore the driving mechanism behind vegetation greening. The results showed that (1) the growth rate of vegetation cover change from 1994 to 2022 was 0.0052/a. The area with an upward trend of kNDVI accounted for 94.11% of the total area of the study area. The greening effect was obvious, and the kNDVI change would continue to rise. (2) Under the scenario of regional climate warming and humidifying, kNDVI responds slightly differently to different climatic factors, and kNDVI is positively correlated with temperature and precipitation in 85.20% of the mining area. The average contribution of precipitation, temperature, and human activities to kNDVI change in the Shendong mining area were 0.00094/a, 0.00066/a, and 0.0036/a, respectively. The relative contribution rates of human activities and climate change were 69.23% and 30.77%, respectively. Thus, human activities are the main driving factor for the changing of vegetation cover in this mining area, and climate change is the secondary driving factor. (3) The dynamic change in land use presents an increase in forest area under the ecological restoration project. The results of this study can provide a scientific basis for the future ecological construction of the Shendong mining area and help in the realization of regional green sustainable development goals.

Arid and semi-arid regions are highly sensitive and vulnerable to climate change and human activities. Clarifying their spatial distribution is of great significance for understanding regional drought dynamics. This research examines the Shendong mining region, employing time series data of vegetation growth anomalies derived from total primary productivity data to delineate ecological drought. The SPI dataset, representing meteorological drought, is utilized to identify drought frequency, duration, and intensity for both types of droughts based on the run theory. The drought characteristics of different land use patterns are analyzed, and the center of gravity of meteorological and ecological droughts in the study area are calculated. The results show the following: (1) The frequency, duration, and intensity of meteorological drought in the Shendong mining area are 0.74 times per year, 9.2 months, and 0.91, respectively. The frequency, duration, and intensity of ecological drought are 0.33 times per year, 18.2 months, and 0.09, respectively. (2) The intensity of meteorological and ecological droughts is generally consistent across different land use types. The frequency of meteorological drought is minimal for croplands and high-coverage grasslands. The duration of meteorological drought is shortest for high-coverage grasslands. High- and medium-to-high-coverage grasslands and cultivated lands have lower ecological drought frequencies. Low- and medium-to-low-coverage grasslands have relatively shorter ecological drought durations. (3) In regions where land use alterations are evident, the frequency and duration of meteorological drought in areas where cropland has been converted to grassland are relatively low. The frequency, duration, and intensity of ecological drought for croplands converted to grasslands and grasslands converted to croplands are similar. (4) The average incidence of meteorological drought transitioning into ecological drought in the study area is roughly 55%, with areas of stable land use demonstrating a more robust correlation between meteorological and ecological drought in croplands. In the converted areas, the correlation between meteorological drought and ecological drought is higher for croplands converted to grasslands. (5) The transition frequency from meteorological drought to ecological drought exceeds 60% in mining areas. Compared to other mining areas, the meteorological drought intensity near Jitu well and Daliuta well is notably higher. The research findings reveal the spatial distribution attributes and transition dynamics of meteorological and ecological droughts in the Shendong coal mining region, providing reference for the implementation of ecological restoration projects and protection measures in the area.