Spatiotemporal variation of vegetation cover in mining areas of Dexing City, China

Spatial and temporal distribution characteristics of dust concentration based on satellite in mining area

The spatial and temporal distribution patterns of dust concentration in the Pingshuo mining area and urban area were analyzed utilizing satellite data. The results indicate that the correlation coefficients of the average PM2.5 and PM10 concentration retrieved by satellite in Shuozhou City are 0.88 and 0.63, respectively, and the satellite inversion data demonstrate high reliability. The spatial distribution of dust concentration in the Pingshuo Mine area is elevated during winter and spring, with significant dust accumulation in winter. The pollution phenomenon in the Pingshuo mining area was pronounced from January to March, and the air quality deteriorated significantly. The correlation analysis of dust concentration between the city and the mining area reveals a marked spatial discontinuity at the boundary between the city and the mining area, indicating that the mining area is not the primary cause of the increase of dust concentration in the urban area, and changes in dust concentration within the mining area exert no significant impact on the urban area. The research results possess significant implications for dust control in both the mining and urban areas.

Spatiotemporal change characteristics of vegetation coverage in Shangwan Mine of China's Shendong Mining Area

The coal mining might cause the disturbance to the vegetation and the disturbance impacts might exist the differences for different areas, and few literatures compared and analyzed different disturbed areas based on the location of the mining face, and paid attention to the post mining self-healing effects of vegetation. Here, this paper selected the GaoFen multispectral images during 2017-2021 to study different areas of Shangwan Mine which includes the old mining area more than 5 years after mining, the new working face underground mined in 2018 and 2019, the natural growth control area and the open-pit mining affected area. The spatiotemporal changes of the surface fraction vegetation coverage (FVC) were analyzed in each area and the correlation between vegetation coverage and climatic factors was studied. The results showed that: (1) The overall vegetation coverage showed a moderate decrease trend in fluctuation from 2017 to 2021. The Open-pit mining affected areas showed the largest decline, reaching 68.3%. The FVC in the underground mining areas had a downward trend, but self-healing effect after mining was also observed. (2) The overall FVC in the study area was positively correlated with the number of precipitation days. (3) There were differences in the sensitivity to mining disturbance for different landform in the underground mining areas. (4) Although the FVC in the Old mining areas had recovered to the level of Natural growth control area, but the annual fluctuation was larger, which might mean lower ecological stability.

Image-based vegetation analysis of desertified area by using a combination of ImageJ and Photoshop software

Fractional vegetation cover (FVC) is a crucial indicator to estimate degradation and desertification for grasslands. However, traditional small-scale FVC analysis methods, such as visual estimation and point-sampling, are cumbersome and imprecise. Innovative methods like image-based FVC analysis methods, while accurate, face challenges such as complex analytical procedures and the necessary training for operations. Therefore, in this study, a combined application of ImageJ and Photoshop was employed to achieve a more effective analysis of FVC values in desertification areas. Our results showed that the FVC results obtained by combination of Photoshop and ImageJ were dependable and precise (R2 > 0.98), demonstrating equivalency to results obtained through either visual estimation or Photoshop-based methods. Furthermore, even in the face of background interference and varied shooting angles, the combination of ImageJ and Photoshop software was still able to maintain a low error rate when analyzing FVC values (average error rate =  - 2.6%). In conclusion, the imaged-based combined FVC analysis method employed in our research was an effective, precise, and efficient technique for analyzing small-scale FVC, promising substantial improvement over conventional methods.

SBAS-InSAR Based Deformation Monitoring of Tailings Dam: The Case Study of the Dexing Copper Mine No.4 Tailings Dam

The No.4 tailings pond of the Dexing Copper Mine is the second largest in Asia. The tailing pond is a dangerous source of man-made debris flow with high potential energy. In view of the lack of effective and low-cost global safety monitoring means in this region, in this paper, the time-series InSAR technology is innovatively introduced to monitor the deformation of tailings dam and significant key findings are obtained. First, the surface deformation information of the tailings pond and its surrounding areas was extracted by using SBAS-InSAR technology and Sentinel-1A data. Second, the cause of deformation is explored by analyzing the deformation rate, deformation accumulation, and three typical deformation rate profiles of the representative observation points on the dam body. Finally, the power function model is used to predict the typical deformation observation points. The results of this paper indicated that: (1) the surface deformation of the tailings dam can be categorized into two directions: the upper portion of the dam moving away from the satellite along the Line of Sight (LOS) at a rate of -40 mm/yr, whereas the bottom portion approaching the satellite along the LOS at a rate of 8 mm/yr; (2) the deformation of the dam body is mainly affected by the inventory deposits and the construction materials of the dam body; (3) according to the current trend, deformation of two typical observation points in the LOS direction will reach the cumulative deformation of 80 mm and -360 mm respectively. The research results can provide data support for safety management of No.4 tailings dam in the Dexing Copper Mine, and provide a method reference for monitoring other similar tailings dams.

Vegetation as an ecological indicator in assessing environmental restoration in mining areas

As global demand for natural resources escalates, the environmental impact stemming from resource extraction has risen to the forefront of contemporary discussions. This paper probed the potential of using vegetation cover as an ecological barometer to gauge the level of environmental damage and restoration in mining areas: a decline in vegetation cover may signify detrimental impacts from intense mining activities, while an increase may indicate effective local environmental stewardship. Therefore, this paper undertook an assessment and discussion of mining damage and environmental management at China's Ta'ershan Mining Area since 2007, calculating and visualizing FVC (Fractional Vegetation Cover) of the Ta'ershan Mining Area to track changes in vegetation cover between 2007 and 2021. Changes in vegetation cover in the Ta'ershan Mining Area could act as a reflection of both mining-induced damage and subsequent successful environmental management by local authorities, providing a practical way to evaluate ecological effects in resource development.