Ecosystem Services Value (ESV) are the various beneficial functions and products that natural ecosystems provide to humans, and are important indicators for evaluating ecosystem conditions and human well-being. Opencast mining is one of the human activities that severely damage the surface environment, but its long-term impact on ecosystem services lacks systematic assessment. This study takes the Ordos opencast mining area as an example, and calculates the value of ESV from 1990 to 2020 based on the Google Earth Engine platform. Mann-Kendall Tau-b with Sen’s Method (Sen + mk test) and Joinpoint regression model were used to analyzes its spatiotemporal variation characteristics. Further revealed the impacts of opencast mining on ESV as well as the trend of ESV changes. The results show that: (1) The dynamic ESV levels in the study area fluctuated considerably from 1990 to 2020 with an overall decreasing trend of 89.45%. (2) Among nine types ecosystem services, most of them were significantly different (p < 0.001) between mining areas and control areas, with biodiversity protection (BP), climate regulation (CR), gas regulation (GR), soil formation and retention (SFR), water supply (WS) and waste treatment (WT) showed a significant decrease between 1990 and 2020. (3) In the past 30 years, the ESV of the study area showed an overall improvement trend, where the improved area accounted for 48.45% of the total area of the study area. However, the degraded area also accounted for 21.28, and 17.19% of the area belonged to severe degradation. With 67% of the significantly degraded areas distributed within mining concessions. (4) The trend of ESV changes in the mining impact areas and the control area showed significant differences. The ESV of the control area increased continuously, with an average annual percentage change (AAPC) of 0.7(95%CI:0.50 ~ 0.9, P < 0.001) from 1990 to 2020; while the ESV of the mining impact areas first stabilized and then decreased significantly, with an AAPC of − 0.2(95%CI:− 0.3 ~ − 0.1,P < 0.001) from 1990 to 2020. This study provides scientific support for formulating ecosystem management, restoration plans, and payment for ecosystem service policies, which is conducive to achieving regional sustainable development and improving human well-being.

The overlapped areas of cropland and coal resources play a fundamental role in promoting economic and social progress. However, intensive mining operations in high water-level areas have brought significant spatial–temporal heterogeneity and ecological problems. From the dual dimensions of the ecosystem service value (ESV) and ecological risk (ER), it is of great significance to explore the influence characteristics of underground mining on the landscape, such as above-ground cultivated land, which is valuable to achieving regional governance and coordinated development. In this study, taking Peixian as the research area, a multiple-dimensional correlation framework was constructed based on the revised ESV and ER, integrating the grey relational degree, spatial–temporal heterogeneity, disequilibrium, and inconsistency index to explore the ESV and ER assessment and correlation characteristics from 2010 to 2020. The results show that (1) the ESV showed a high agglomerated distribution pattern in the east, with a net decrease of 13.61%. (2) The ER decreased by 78.18 and was concentrated in the western and southern regions, with overall contiguous and local agglomeration characteristics. This indicates that the ecological security of the region has improved. (3) The comprehensive grey correlation between the cultural service value and the ecological risk index was the highest. Furthermore, the spatial–temporal heterogeneity of the ESV and ER weakened, and the disequilibrium rose and then fell, indicating that the ecosystem gradually tended to be stable. The study is crucial for overlapped cropland and coal resource areas to maintain stability and sustainable development. The multivariate correlation framework provides practical value for ecosystem management and risk control.

Remotely sensed spectral diversity is a promising method for investigating biodiversity. However, studies designed to assess the effectiveness of tracking changes in diversity using historical satellite imagery are lacking. This study employs open-access multispectral Landsat imagery and the BiodivMapR package to estimate the multi-temporal alpha diversity in drylands affected by mining. Multi-temporal parameters of alpha diversity were identified, such as vegetation indices, buffer zone size, and the number of clusters. Variations in alpha diversity were compared for various plant communities over time. The results showed that this method could effectively assess the alpha diversity of vegetation (R², 0.68). The optimal parameters used to maximize the accuracy of alpha diversity were NDVI threshold, 0.01; size of buffer zones, 120 m × 120 m; number of clusters, 100. The root mean square error of the alpha diversity of herbs was lowest (0.26), while those of shrub and tree communities were higher (0.34–0.41). During the period 1990–2020, the study area showed an overall trend of increasing diversity, with surface mining causing a significant decrease in diversity when compared with underground mining. This illustrates that the quick development of remote sensing and image processing techniques offers new opportunities for monitoring diversity in both single and multiple time phases. Researchers should consider the plant community types involved and select locally suitable parameters. In the future, the generation of long-time series and finer resolution maps of diversity should be studied further in the aspects of spatial, functional, taxonomic, and phylogenetic diversity.