Junting Guo’s research while affiliated with China University of Mining and Technology - Beijing and other places

The direct removal of surface vegetation during surface coal mining has a negative impact on the surrounding ecological environment. Effective vegetation restoration is essential to mitigate these impacts. Therefore, accurate monitoring and assessment of vegetation restoration following mining disturbance is critical for ecological protection in mining areas. This study employs the Detecting Breakpoints and Estimating Segments in Trend (DBEST) to map the historical patterns of vegetation disturbance and subsequent recovery at the Shendong coal base. This is the first large-scale application of DBEST for such purposes. To examine the spatio-temporal trends in post-mining vegetation restoration, the Years to Recovery (Y2R) and amount of NDVI recovery were calculated based on the Normalized Difference Vegetation Index (NDVI) time-series. The results show that the DBEST has an accuracy of 0.90 in detecting vegetation destruction and 0.78 in detecting restoration. These findings highlight the substantial potential of this algorithm for monitoring vegetation disturbance in mining areas. The total area of vegetation destruction within the Shendong coal base is 449.65 km ² , and the restoration area is 156.62 km ² . Between 1992 and 2017, 46.90% of the disturbed areas achieved 80% of the pre-mining vegetation level, exceeding the average restoration level in China. The average Y2R was 4.68 years. Furthermore, NDVI restoration showed an initial increase followed by a decline with longer Y2R values, suggesting that while early restoration efforts were more effective, long-term restoration efficiency decreased. This finding emphasizes the necessity of concentrating on the restoration process at each stage of the planning and implementation of revegetation projects, particularly regarding the difficulties associated with long-term restoration. This is crucial for the development of more comprehensive and sustainable strategies.

Analyzing the current trends and causes of carbon storage changes and accurately predicting future land use and carbon storage changes under different climate scenarios is crucial for regional land use decision-making and carbon management. This study focuses on Beijing as its study area and introduces a framework that combines the Markov model, the Patch-based Land Use Simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to assess carbon storage at the sub-district level. This framework allows for a systematic analysis of land use and carbon storage spatiotemporal evolution in Beijing from 2000 to 2020, including the influence of driving factors on carbon storage. Moreover, it enables the simulation and prediction of land use and carbon storage changes in Beijing from 2025 to 2040 under various scenarios. The results show the following: (1) From 2000 to 2020, the overall land use change in Beijing showed a trend of “Significant decrease in cropland area; Forest increase gradually; Shrub and grassland area increase first and then decrease; Decrease and then increase in water; Impervious expands in a large scale”. (2) From 2000 to 2020, the carbon storage in Beijing showed a “decrease-increase” fluctuation, with an overall decrease of 1.3 Tg. In future carbon storage prediction, the ecological protection scenario will contribute to achieving the goals of carbon peak and carbon neutrality. (3) Among the various driving factors, slope has the strongest impact on the overall carbon storage in Beijing, followed by Human Activity Intensity (HAI) and Nighttime Light Data (NTL). In the analysis of carbon storage in the built-up areas, it was found that HAI and DEM (Digital Elevation Model) have the strongest effect, followed by NTL and Fractional Vegetation Cover (FVC). The findings from this study offer valuable insights for the sustainable advancement of ecological conservation and urban development in Beijing.

Most coal resources are deposited in the form of inclined coal seams, and surface subsidence basin morphology induced by the mining of inclined coal seams is frequently skewed. The probability integral method with symmetrical distribution characteristics is widely used at present in surface subsidence prediction in coal mining in China. However, this method performs poorly when the inclined coal seam mining subsidence is predicted, and prediction accuracy decreases considerably with an increase in coal seam inclination. To solve this problem, this study first establishes three coordinate systems: a working surface rectangular coordinate system, a working face body-following coordinate system, and a surface rectangular coordinate system. Then, a random medium theory is applied to realize the superposition integral operation of the subsidence influence of unit mining in the working faces body-following coordinate system. Subsequently, the subsidence effect of a certain point on the surface is converted into the surface rectangular coordinate system. Finally, the inclined coal seam mining subsidence prediction model is constructed under the surface rectangular coordinate system. Results show that the surface subsidence caused by the mining of the inclined coal seam units conforms to the Weibull polar distribution law, and the effectiveness of the prediction model is verified through examples. The relative mean squared error of the prediction is less than 10%. The results of the study can provide theoretical and technical support for the subsidence prediction of similar mining areas.

The mining of underground coal resources often results in extensive damage to the ground surface, particularly in China, which has a large amount of coal resources. However, the laws of surface damage caused by the mining of deep and shallow underground coal resources are relatively different. This study analyzes the difference in surface damage induced by deep and shallow mining and its mechanism by field measurement and similar material simulation experiments. Surface damage is mainly manifested in the form of cracks, which can be categorized as permanent and dynamic cracks. Permanent cracks occur above the mining boundary of shallow and deep coal mines. Dynamic cracks (including dynamic stretching cracks and stepped cracks) only appear above the goaf in shallow mining. This disparity is due to the fact that strata movement in deep mining occurs in a “three zones” mode, with the failure height of strata increasing with the mining degree in an “S” shape. However, rock strata movement in shallow mining follows a “two zones” mode, with the failure height of rock strata increasing exponentially with the mining degree. Thus, the rock strata are prone to slide and become unstable in the form of benched rock beams, producing dynamic cracks, such as stepped cracks on the surface. This research improves the existing mining subsidence theory and provides technical support for relevant mines to take targeted treatment measures.

Understanding the synergistic effect between topography and vegetation in the underground coal mine is of great significance for the ecological restoration and sustainable development of mining areas. This paper took advantage of unmanned aerial vehicle (UAV) remote sensing to obtain high-precision topographic factors (i.e., digital elevation model (DEM), slope, and aspect) in the Shangwan Coal Mine. Then, a normalized difference vegetation index (NDVI) was calculated utilizing Landsat images from 2017 to 2021, and the NDVI with the same spatial resolution as the slope and aspect was acquired by down-sampling. Finally, the synergistic effect of topography and vegetation in the underground mining area was revealed by dividing the topography obtained using high-precision data into 21 types. The results show that: (1) the vegetation cover was dominated by “slightly low-VC”, “medium-VC”, and “slightly high-VC” in the study area, and there was a positive correlation between the slope and NDVI when the slope was more than 5°. (2) When the slope was slight, the aspect had less influence on the vegetation growth. When the slope was larger, the influence of the aspect increased in the study area. (3) “Rapidly steep–semi-sunny slope” was the most suitable combination for the vegetation growth in the study area. This paper revealed the relationship between the topography and vegetation. In addition, it provided a scientific and effective foundation for decision-making of ecological restoration in the underground coal mine.

In the practical processes of coal mines and tunnel, rectangular roadways are widely used in the underground environment. However, the stress distribution law of the rock mass around the rectangular roadways is relatively complicated that is influenced by different parameters, such as the in situ stress, geological structure, and properties of the surrounding rock mass. It is extremely significant to conduct systematic and in-depth research regarding the stress distribution and deformation failure mechanism of the rock mass around the rectangular roadways. Based on theoretical analysis, the stress distribution law of the surrounding rock of rectangular roadway under different rock mass strength grades is studied directly through rectangular roadway in this paper. This further reveals the distribution law of secondary stress field after excavation of rectangular roadway. A coal mine intends to excavate a roadway in rock mass, and then, the rectangular roadway is simulated by FLAC3D software. Then, the strain distribution and failure types of roadway surrounding rock under different rock mass properties are obtained. The results show that the failure of rectangular roadway is mainly shear failure and tensile failure. The roof and floor of roadway are mainly tensile failure, and the side of roadway is mainly shear failure. Moreover, the stress shifting and distribution of the rock mass around rectangular roadways is a complicated dynamic variation process. The damage degree of the floor and roof of the rectangular roadway is greater than that of the two sides of the roadway. Its variation is mainly related to the strength of surrounding rock mass.

Considering the spatio-temporal heterogeneity, this study resolved the coupling influence of a variety of driving factors on vegetation changes in mining areas and discovered the influencing characteristics of the respective driving factors, especially mining activities. First, the spatio-temporal characteristics of FVC (fractional vegetation cover) variation were analyzed in the Sheng-Li mining area. Second, the quantitative relationships among the natural factors (temperature, precipitation, and elevation), artificial factors (mining activities, urban activities), and FVC were constructed by GTWR (geographically and temporally weighted regression) to quantify the contribution of each factor to the change in FVC. Third, the influencing characteristics of the respective driving factors, especially mining activities, were analyzed and summarized. The results show that (1) the FVC change was mainly influenced by natural factors in the areas far from mines and towns and artificial factors in the areas close to mines and towns. (2) The contribution of mining activities to vegetation change (C-Mine) was spatially characterized by two features: (a) distance attenuation characteristics: C-Mine showed logarithmic decrement with distance; (b) directional heterogeneity: C-Mine varied significantly in different directions. In particular, there was a high C-Mine area located near multiple mining areas, and the range of this area shifted to include the mine with more production over time. Overall, unmixing the coupling influence from driving factors with spatio-temporal heterogeneity and achieving a quantitative description of the influencing characteristics in mining areas were the main contributions of this study. The quantification methods and results in this paper provide important support for decision-making on ecological protection and restoration in mining areas.

Studying the movement law and failure mechanism of overburden is important to underground safety production, aquifer protection, surface subsidence and ecological protection. A commonly used model, the arch structure model, for studying overburden movement is systematically reviewed in this paper. First, the arch structure in the mining field is divided into an unconsolidated layer arch, beam arch (hinged arch), and overburden arch according to arching medium. On this basis, the research progress and existing problems of these three arch structure models are discussed according to the research means, including theoretical modeling, numerical simulation, similar simulation, and field measurements. The application of the arch structure model focuses on the prediction and prevention of mining pressure and surface subsidence, and there are relatively few means to actively regulate overburden arch. Thus, three control methods of the arch structure in underground coal mining are proposed: the preset arch structure method before coal mining, process control arch methods during coal mining, and end reinforcement control arch methods after coal mining. Finally, the main research focus on the arch structure model in the future is discussed.