Open-pit mining is a common method for extracting coal, but considerable resources are often left unrecovered at the bottom of end-slopes, leading to a permanent waste of resources. This research presents a sustainable approach of multi-layer highwall mining at different levels to address the issue of abundant resources left unrecovered at the bottom of the end-slope in thick-seam open-pit mines. The interlayer between the upper and lower entries is simplified into a beam structure model, the bending moment distribution characteristics of the beam under a load of highwall miner are analyzed, and a method for calculating the thickness range of the interlayer is proposed. The web pillar width and interlayer thickness, obtained theoretically, are verified through a numerical simulation, and the results of mining a single layer are compared to those of mining multiple layers. The results show that the web pillar width and interlayer thickness derived from the numerical simulation are basically the same as those of the theoretical analysis. Compared with single layer mining, the vertical stress on the web pillar in the lowest panel is reduced by 14.83~18.25%, and the safety factor of the web pillar is increased to 0.27. The web pillars and interlayers at different elevations are stable during multi-layer highwall mining. These findings support the feasibility of multi-layer highwall mining for resource recovery, which is conducive to sustainable mining.

In the process of mining and transportation, the temporary non-hardened mine-road structure is mainly a mixture of soil and stone, which very easily produces dust hazards via crushing and wind transportation. Geopolymers can be used in the road’s soil and stone mixture so that the road reaches certain strength requirements in line with the short-term use of the mine. However, in alpine open-pit coal mines, which are subject to the influence of weather changes, freezing and thawing phenomena will affect the long-term use of the road and its normal and safe operation. An open-pit coal mine in Xinjiang, China, was chosen as the research object of alpine open-pit coal mines. Using the method of indoor testing, different freeze–thaw freezing temperatures, different numbers of cycles, changes in the mechanical properties of the mine-road materials, and microscopic changes were studied. From the experimental results, it was determined that with a reduction in the freeze–thaw freezing temperature, the specimen strength declines after stabilizing, and with an increase in the number of freeze–thaw cycles, the specimen strength exhibits a linear decline. The specimen’s internal structure gradually changed from dense to loose; the fracture mode changed from toughness fractures to crystal fractures after the removal of the maximum load reduction. The uniaxial compressive strength was reduced to 61%; the tensile strength was reduced to 49%. The fracture zone of the specimen was analyzed using energy spectra, and the main elements changed from O (57.19%), Si (17.07%), and Al (12.19%) without freezing and thawing to O (49.76%), Si (15.70%) and Ca (11.09%) after freezing and thawing.

Damage deterioration of rocks in cold regions under seasonal changes and daily cycles of freezing and thawing generate a series of engineering geological problems. These problems will seriously affect the safe and efficient production of open-pit mines. In this paper, a freeze–thaw cycle test and uniaxial compression test considering the natural conditions of the slope were carried out. Mechanical properties and damage mechanisms of open-pit mine mudstone under freeze–thaw conditions were investigated based on nuclear magnetic resonance (NMR) technology. The test results show that the microscopic internal pore structure of mudstone was changed under the superimposed effect of freeze–thaw damage and hydration damage. The internal pore size of mudstone increased with the number of freeze–thaw cycles, while the average pore size of the natural mudstone test increased more. Macroscopically, the compressive strength and modulus of elasticity of mudstone varied linearly with the number of freezing cycles, and the compressive strength and modulus of elasticity showed a decreasing trend. The strain-softening characteristics of mudstone samples were significant for more freeze–thaw cycles. The study explains the microscopic causes of mudstone deterioration in open-pit mines in cold regions and offers guidance for solving engineering disasters caused by mudstone deterioration.

Plant species classification in semi-arid mining areas is of great significance in assessing the environmental impacts and ecological restoration effects of coal mining. However, in semi-arid mining areas characterized by mixed arbor–shrub–herb vegetation, the complex vegetation distribution patterns and spectral features render single-sensor approaches inadequate for achieving fine classification of plant species in such environments. How to effectively fuse hyperspectral images (HSI) data with light detection and ranging (LiDAR) to achieve better accuracy in classifying vegetation in semi-arid mining areas is worth exploring. There is a lack of precise evaluation regarding how these two data collection approaches impact the accuracy of fine-scale plant species classification in semi-arid mining environments. This study established two experimental scenarios involving the synchronous and asynchronous acquisition of HSI and LiDAR data. The results demonstrate that integrating LiDAR data, whether synchronously or asynchronously acquired, significantly enhances classification accuracy compared to using HSI data alone. The overall classification accuracy for target vegetation increased from 71.7% to 84.7% (synchronous) and 80.2% (asynchronous), respectively. In addition, the synchronous acquisition mode achieved a 4.5% higher overall accuracy than asynchronous acquisition, with particularly pronounced improvements observed in classifying vegetation with smaller canopies (Medicago sativa L.: 17.4%, Pinus sylvestris var. mongholica Litv.: 11.7%, and Artemisia ordosica Krasch.: 7.5%). This study can provide important references for ensuring classification accuracy and error analysis of land cover based on HSI-LiDAR fusion in similar scenarios.