Surface Mining Research Articles

Automatically identifying the vegetation destruction and restoration of various open-pit mines utilizing remotely sensed images: Auto-VDR

The spatio-temporal pattern of vegetation disturbance by open-pit mining activities such as the disturbance area and magnitude are important for coordinated development of surface mining and environmental protection. This paper proposes an automatic method (Auto-VDR) for identifying vegetation destruction and restoration of various open-pit mines. The proposed method consists of three steps: construction of the sample dataset, identification of disturbance types, and extraction of disturbance time and magnitude. First, a sample dataset with three types was constructed according to the interannual trends of Normalized Difference Vegetation Index (NDVI) in mining areas: “Restoration after destruction (RAD)”, “Destruction without restoration (DWR)” and “No destruction (ND)”. Second, in order to accommodate to various open-pit mines with different background conditions (original vegetation cover prior to mining, loss rate and magnitude of vegetation due to mining, etc.), the “Shape-based distance” was used to match the NDVI curves of each pixel to the three disturbance types. Third, the disturbance time and magnitude in the destroyed regions were extracted based on the vegetated/bare ground threshold (α). The Shendong coal base in China was selected as the study area consisting of 133 open-pit coal mines. Annual NDVI was generated using Landsat time-series data. The maps of vegetation destruction and restoration caused by surface mining during 1990–2021 were drawn with accuracies of 0.82 and 0.87, respectively. The identification accuracy of the Auto-VDR is higher than Landsat-based detection of Trends in Disturbance and Recovery (LandTrendr) and Continuous Change Detection and Classification (CCDC). The results show that from 1990 to 2021, a total of 400.08 km2 of vegetation has been destroyed, accounting for 35.93% of the study area. Furthermore, restoration activities mainly began in 2010, lagging mining activities by approximately three years. The accumulated area of restoration was 177.91 km2 and accounts for 15.98% of the study area. The vegetation destruction at the Shendong coal base has gone through four stages, with 2008, 2015 and 2018 as splits, corresponding to the developing stage of the China coal industry. In particular, the area of vegetation destruction per year reached the maximum of 61.16 km2 in 2008, which was 1.38 times the total area mined over the past 17 years. There were 14% of the 133 open-pit mines in Shendong coal base with a restoration rate of 0.8 and 59% of the mines with a restoration rate of 0.5. This method has been demonstrated to be able to extract vegetation destruction and restoration processes accurately and rapidly for various open-pit mines at a scale of coal base, which provides an important reference for supervising the impact of mining on the environment and assessing the effectiveness of ecological restoration.

Conceptual Framework for Hazards Management in the Surface Mining Industry—Application of Structural Equation Modeling

This paper presents a conceptual framework with the application of the structural equation modeling (SEM) method for improving safety in the surface mining industry. The focus of the study is to address the essential components of occupational safety and assess them to develop significant linkages because they are often addressed individually. In this study, the risk (accident causation) factors were examined for continuous improvement based on the risk management process and the application of engineering, education, and enforcement. Data collected from mine employees were utilized to evaluate the framework using SEM. The final structure model showed good fit indices, including chi-square to a degree of freedom (x2/df) equal to 2.545, root mean square error of approximation (RMSEA) of 0.034 with a probability of 1.0, and a valid framework path. All the factors had a significant positive effect on workplace conditions and workers’ commitment, except machinery, which had a positive non-significant effect on workplace conditions. The effects of the mediated factors of worker commitment and workplace conditions on the number of accidents were β = −0.76 and β = −0.145, respectively, and the effects on job satisfaction were β = 0.31 and β = 0.433. The research concluded that any risk factor reduction can improve safety in the mining industry; however, the correlation of all factors’ effects magnifies the influence of a single factor. Furthermore, the conceptual framework is recommended for identifying the factors that need modification in order to manage hazards and improve safety in the workplace.

Distribution Law of Mine Ground Pressure via a Microseismic Sensor System

The particularity of the occurrence conditions of the ore body in Xianglushan Tungsten Mine determines the mining form of the ore body and the particularity of the ground pressure distribution after mining. A large number of mined-out areas, supporting pillars, and natural and human factors have formed a comprehensive disaster environment. This can lead to frequent disasters, great harm, serious economic losses, and the necessity of severe environmental protection operations in the mine. This study aims to establish a microseismic monitoring system according to the actual needs of the site and to reveal the law of ground pressure manifestation by analyzing the distribution characteristics of microseismic events; to analyze the occurrence stability of the goaf; further verify it laterally; and finally, demonstrate the feasibility and effectiveness of the microseismic monitoring sensor system. In view of the current ground pressure problem in Xiangxuoshan tungsten mine, the stress change characteristics during dynamic mining and filling were obtained through comparative analysis of different perspectives such as surface change, energy release, and mining loudness, and key areas were identified to improve the reliability of underground ground pressure monitoring. The results show that the process of deposit destabilization caused by ore body mining can be further analyzed by microseismic monitoring, and the combination of surface settlement, mining intensity, and energy release can verify the accuracy of stress distribution and ground pressure transfer. In turn, the general reliability of underground ground pressure hazard warning is empirically improved.

A review of state-of-the-art techniques for the determination of the optimum cut-off grade of a metalliferous deposit with a bibliometric mapping in a surface mine planning context

In terms of the global share, 95% of the non-metallic minerals, 90% of the metallic minerals, and about 60% of coal are being mined out through surface mining methods. In a mining operation, the grade-tonnage distribution of the deposit necessitates that not all of the material inside the open pit can be treated. Given this variability, it is critical to identify ore and waste elements correctly. The global population is expected to increase from 8 billion in 2022 to more than 9.7 billion in 2050. World metal consumption increases at around 3.2% per year, driving trade and economic diversification. Therefore, to guarantee a continuous supply of the minerals from the metalliferous surface mining industry in terms of techno-economic concerns, cut-off grade (COG) optimization is the key. The economic requirement aims towards the maximization of the return on investment, while techno-economic sustainability aims towards the maximization of resource recovery. Optimization of COG for surface mine design has come a long way in the last 60 years, primarily using analytical models based on the traditional methodology. In the past five years, non-conventional evolutionary algorithms have been extensively used. However, the analytical methods can be credited with the maximum amount of work, yet none can provide optimal outputs. This review article presents techniques, advancements, limitations, difficulties, bibliographic analysis, and potential future research paths in COG optimization for surface mine planning.

Coal, Cages, Crisis: The Rise of the Prison Economy in Central Appalachia by Judah Schept

Reviewed by: Coal, Cages, Crisis: The Rise of the Prison Economy in Central Appalachia by Judah Schept Justin Randolph Coal, Cages, Crisis: The Rise of the Prison Economy in Central Appalachia. By Judah Schept. (New York: New York University Press, 2022. Pp. [vi], 321. Paper, $32.00, ISBN 978-1-4798-5897-2; cloth, $99.00, ISBN 978-1-4798-8892-4.) On page one of Coal, Cages, Crisis: The Rise of the Prison Economy in Central Appalachia, its author is nearly arrested. Judah Schept’s offense was attempting to photograph a Kentucky prison. Police spoiled that photo opportunity, but others proved successful. One of the book’s photos, also featured on this edition’s cover, a landscape captioned “The Interface,” depicts the road between a strip mine’s coal seam and the razor wire of a prison (p. 125). Interfaces offer a conceptual symbol for Schept’s inquiry. He explores the juncture between past and present with an eye to paths around the prison. “The rise of cages in the coalfields,” he argues, “reflects a new strategy for an old project: the state’s ongoing need to manufacture and maintain capitalist social order and social relations” (p. 5). Through this interdisciplinary study of the rural prison boom, Schept provides an invaluable state of the field in carceral and Appalachian studies, using the lens of racial capitalism to interpret the region’s complex identity. He also gives an innovative model for the use of blended oral and archival historical methods to study deep historical processes that manifest in the recent past. To be sure, the book’s multiscalar and multitemporal presentation will dissatisfy those strict historicists expecting engagement with a circumscribed archive. But Coal, Cages, Crisis opens important pathways for historians of the southern prison and those southerners who have judged the prison an unnatural feature of the landscape. The book has three parts. In Part 1, “Extraction and Disposal,” Schept reflects on Appalachia’s construction as a space of great value and worthlessness. Chapter 1 showcases the book’s reliance on autoethnography, placing the authorial self in the narrative and interactions with oral history informants, to explore mountaintop removal (MTR). Longtime residents reveal [End Page 397] that rural planners used MTR sites for garbage incineration before they were used for prisons. Chapter 2 reflects on the region’s legal and political history, rooting Appalachia’s prison boom in the War on Poverty as well as the regulatory revolution of the 1970s, which empowered mining companies to normalize MTR. Part 2, “Profit and Order,” places Appalachia’s deeper history of resource extraction and anticapitalist militancy in a continuum with the region’s experience of mass incarceration. Chapter 3 focuses on the afterlife of convict leasing through the case of Tennessee’s Brushy Mountain State Penitentiary— now an ecotourist hot spot with moonshine tastings. Chapter 4, similarly, considers the longue durée of Wheelwright, Kentucky, a company town whose economy transitioned from coal to private prisons. Both chapters rely heavily on secondary historical literature and archival research situated alongside theoreticians of capitalist crisis, including Karl Marx, Antonio Gramsci, Stuart Hall, and the abolitionist geographer Ruth Wilson Gilmore, to complicate simple narratives of one industry replacing another. Part 3 tracks one community’s debate over a new federal prison in Letcher County, Kentucky, between 2013 and 2019. Chapters 5 and 6 expound on Schept’s idea of “carceral social reproduction,” the elite reorganization of Appalachian society—everything from workforce development to social benefits like road construction and elementary education—around prison expansion (p. 152). Chapter 7, coauthored with the activist-scholar Sylvia Ryerson, narrates the 2019 defeat of this newest prison by a complex coalition of anti-prison forces. This reviewer hopes for books that build on Schept’s image of the prison by exploring those just outside the frame of photos like “The Interface.” How might incarcerated people behind the concertina wire directly inform this history? How do the police lurking behind the photographer plug into a political economy like Kentucky’s, where “the state prison population has grown” since the passage of a 2011 bill meant to decarcerate (p. 13)? Schept has given us a model and program for collaborative...

An Analysis of Blasthole Condition towards Toxic Fumes Generation from Blasting Activities in Surface Mine

One impact of blasting activities is the release of toxic fumes capable of disturbing living creatures around the blasting zone. Fumes are affected by several factors, including blasthole conditions. Measurement for this research was performed in a coal mine called PT. Kaltim Prima Coal in Kalimantan, Indonesia, to investigate the impact mentioned above through a quantitative method, which was performed directly in the field. The results show that the formed CO gas level ranged between 60.34 - 360.29 ppm, while the formed NO2 gas level ranged between 0.3 - 3.16 ppm, with average temperature and relative humidity of the blastholes at 31°C and 77.01%, respectively. Based on these results, the temperature and relative humidity conditions in the blastholes have a linear effect on the formation of toxic fumes by 84%. Considering the average wind speed at the measurement sites was 2.14 m/s, the trend of decreasing toxic fumes, time variables, and threshold limit values of exposure for humans of up to 15-minutes, it can be concluded that the safe time for workers to return to the site is less than 1 minute.

Mineralogy and enrichment of critical elements (Li and Nb-Ta-Zr-Hf-Ga) in the Pennsylvanian coals from the Antaibao Surface Mine, Shanxi Province, China: derivation of pyroclastics and sediment-source regions

As a critical element, lithium plays an important role in a wide range of modern industries and in particular, battery storage and new energy technologies. Lithium in coal has attracted much attention in recent years because some coals are highly enriched in this element and consequently their corresponding coal combustion products may provide anm alternative source for this element. Previous studies showed that highly enriched Li in coals is generally associated with chlorite group minerals and in most cases attributed to the action of hydrothermal solutions. This paper provides mineralogical and geochemical data on the No. 9 Coal, the major minable coal from the Antaibao Surface Mine, Ningwu Coalfield, Shanxi Province, northern China, and focuses on the modes of occurrence and source of Li in this coal. The No. 9 Coal is a medium ash, medium sulfur, high volatile bituminous coal. The mineralogy of the No. 9 Coal is dominated by kaolinite, calcite, and pyrite, with minor amounts of anatase, rutile, goyazite, quartz, illite, boehmite, and bassanite, and traces of orthoclase, zircon and galena. The studied coal samples are characterized by high contents of Al2O3 (39.80% on average) in comparison with average Chinese coals, and high concentrations of Li, Ga, Se, Zr, Nb, Ta and Th compared with world hard coals. In addition to Li and Al, the critical elements Nb, Ta, Zr, Hf, and Ga in this coal also have a potential economic significance. The geochemical indicators (high Al2O3/TiO2, low Nb/Yb ratios and the specific rare earth element distribution patterns) and the mineral compositions (e.g., very low content of boehmite) indicate that the mineral matter in most coal benches and host rocks is dominantly derived from the Precambrian calc-alkaline granites of the Yinshan and northern Trans North China Orogens, and possibly from the bauxite of the Benxi Formation. Additionally, the geochemical and mineralogical characteristics of the intra-seam partings and some coal benches (quartz-free, kaolinite-dominated mineralogy, high Al2O3/TiO2 and Nb/Yb values) indicate that they were derived from an alkaline intermediate-felsic volcanic source. The highly enriched Li in the studied samples mainly occurs in kaolinite and is attributed to the input of material from sediment-source regions, rather than hydrothermal fluids. In addition, interaction of terrestrial and marine waters may have promoted the Li enrichment process in the partings.

Estimating Coal Mine Dump Stability from Its Natural Oscillations (Based on Seismic Monitoring at the Kolyvan Anthracite Deposit, Novosibirsk Region)

Abstract —Based on the analysis of the 2017–2021 recordings from the Kharino seismic station (the Altai-Sayan seismic stations network) and the 2002–2019 satellite imagery, the trigger of the July 18, 2020 earth-slide at Elbashinsky waste rock dump of the Kolyvan Anthracite Deposit (Novosibirsk region) has been established. The study of natural oscillations of the mine waste dump allowed estimating its stability and thus contributing to environmental and industrial safety in surface mining of solid minerals.

Development of Surface Mining 4.0 in Terms of Technological Shock in Energy Transition: A Review

The expansion of end-to-end Industry 4.0 technologies in various industries has caused a technological shock in the mineral resource sector, wherein itsdigital maturity is lower than in the manufacturing sector. As a result of the shock, the productivity and profitability of raw materials extraction has begun to lag behind the industries of its deep processing, which, in the conditions of volatile raw materials markets, can provoke sectoral crises. The diffusion of Industry 4.0 technologies in the mining sector (Mining 4.0) can prevent a technological shock if they are implemented in all segments, including quarrying (Surface Mining 4.0). The Surface Mining 4.0 technological platform would connect the advanced achievements of the Fourth Industrial Revolution (end-to-end digital artificial intelligence technologies, cyber-physical systems and unmanned production with traditional geotechnology) without canceling them, but instead bringing them to a new level of productivity, resource consumption, and environmental friendliness. In the future, the development of Surface Mining 4.0 will provide a response to the technological shock associated with the acceleration of the digital modernization of the mining sector and the increase in labor productivity, which are reducing the operating costs of raw materials extraction. In this regard, the given review is an attempt to analyze the surface mining digital transformation over the course of the diffusion of Industry 4.0 technologies covered in scientific publications. The authors tried to show the core and frontiers of Surface Mining 4.0 development to determine the production, economic, and social effect of replacing humans with digital and cyber-physical systems in the processes of mineral extraction. Particular attention was paid to the review of research on the role of Surface Mining 4.0 in achieving sustainable development goals.

Application of an Optimized PSO-BP Neural Network to the Assessment and Prediction of Underground Coal Mine Safety Risk Factors

Coal has played an important role in the economies of many countries worldwide, which has resulted in increased surface and underground mining in countries with large coal reserves, such as China and the United States. However, coal mining is subject to frequent accidents and predictable risks that have, in some instances, led to the loss of lives, disabilities, equipment damage, etc. The assessment of risk factors in underground mines is therefore considered a commendable initiative. Therefore, this research aimed to develop an efficient model for assessing and predicting safety risk factors in underground mines using existing data from the Xiaonan coal mine. A model for evaluating safety risks in underground coal mines was developed based on the optimized particle swarm optimization-backpropagation (PSO-BP) neural network. The results showed that the PSO-BP neural network model for safety risk assessment in underground coal mines was the most reliable and effective, with MSE, MAPE, and R2 values of 2.0 × 10−4, 4.3, and 0.92, respectively. Therefore, the study proposed the neural network model PSO-BP for underground coal mine safety risk assessment. The results of this study can be adopted by decision-makers for evaluating and predicting risk factors in underground coal mines.

Prediction of ground vibration due to mine blasting in a surface lead–zinc mine using machine learning ensemble techniques

Ground vibration due to blasting is identified as a challenging issue in mining and civil activities. Peak particle velocity (PPV) is one of the blasting undesirable consequences, which is resulted during emission of vibration in blasted bench. This study focuses on the PPV prediction in the surface mines. In this regard, two ensemble systems, i.e., the ensemble of artificial neural networks and the ensemble of extreme gradient boosting (EXGBoosts) were developed for PPV prediction in one of the largest lead–zinc open-pit mines in the Middle East. For ensemble modeling, several ANN and XGBoost base models were separately designed with different architectures. Then, the validation indices such as coefficient determination (R2), root mean square error (RMSE), mean absolute error (MAE), the variance accounted for (VAF), and Accuracy were used to evaluate the performance of the base models. The five top base models with high accuracy were selected to construct an ensemble model for each of the methods, i.e., ANNs and XGBoosts. To combine the outputs of the top base models and achieve a single result stacked generalization technique, was employed. Findings showed ensemble models increase the accuracy of PPV predicting in comparison with the best individual models. The EXGBoosts was superior method for predicting of the PPV, which obtained values of R2, RMSE, MAE, VAF, and Accuracy corresponding to the EXGBoosts were (0.990, 0.391, 0.257, 99.013(%), 98.216), and (0.968, 0.295, 0.427, 96.674(%), 96.059), for training and testing datasets, respectively. However, the sensitivity analysis indicated that the spacing (r = 0.917) and number of blast-holes (r = 0.839) had the highest and lowest impact on the PPV intensity, respectively.

Aircraft and satellite observations reveal historical gap between top-down and bottom-up CO2 emissions from Canadian oil sands.

Measurement-based estimates of greenhouse gas (GHG) emissions from complex industrial operations are challenging to obtain, but serve as an important, independent check on inventory-reported emissions. Such top-down estimates, while important for oil and gas (O&G) emissions globally, are particularly relevant for Canadian oil sands (OS) operations, which represent the largest O&G contributor to national GHG emissions. We present a multifaceted top-down approach for estimating CO2 emissions that combines aircraft-measured CO2/NOx emission ratios (ERs) with inventory and satellite-derived NOx emissions from Ozone Monitoring Instrument (OMI) and TROPOspheric Ozone Monitoring Instrument (TROPOMI) and apply it to the Athabasca Oil Sands Region (AOSR) in Alberta, Canada. Historical CO2 emissions were reconstructed for the surface mining region, and average top-down estimates were found to be >65% higher than facility-reported, bottom-up estimates from 2005 to 2020. Higher top-down vs. bottom-up emissions estimates were also consistently obtained for individual surface mining and in situ extraction facilities, which represent a growing category of energy-intensive OS operations. Although the magnitudes of the measured discrepancies vary between facilities, they combine such that the observed reporting gap for total AOSR emissions is ≥(31 ± 8) Mt for each of the last 3 years (2018-2020). This potential underestimation is large and broadly highlights the importance of continued review and refinement of bottom-up estimation methodologies and inventories. The ER method herein offers a powerful approach for upscaling measured facility-level or regional fossil fuel CO2 emissions by taking advantage of satellite remote sensing observations.

Determining the Safe Distance for Mining Equipment Operation When Forming an Internal Dump in a Deep Open Pit

In the surface mining of mineral deposits, land resources suitable for agricultural purposes are inappropriately spent in large volumes. When mining deep open pits, overburden rocks are mainly transported to the surface. The optimal solution for reducing the area of disturbed lands is the placement of overburden rocks in internal dumps in the open pit. This is especially suitable when mining a mineral deposit with several open pits where at least one of them is depleted. Therefore, it is important to assess the feasibility of building an internal dump, based on the stability parameters of its slopes and the safe distance for placing mining equipment within its boundaries, which was the focus of this research. Numerical modeling with Slide 5.0 software was used to determine the stability of the dump slope inside the open pit and the safe distance from the upper slope edge for placing mining equipment. This reflected the geomechanical situation occurring within the boundaries of the dump formed in the open-pit field with a high degree of reliability. It was determined that the maximum standard safety factor values of the open-pit slopes are within the limits when the overburden rocks border on the hard bedrock (Ks.s.f ≥ 1.2). Under the condition where the dump slope bordered on sedimentations represented by clays, loams, and sands with a strength of 2–3 on the Mohs scale, the safety factor decreased by 22%. It was determined that the minimum safe distance from the outer contour of the dragline base to the upper edge of a single-tier dump was 15.5 m with a safety factor of 1.21. The maximum safe distance values in the range of 73.5–93 m were concentrated within the boundaries of sections 5–9, with a safety factor from 1.18 to 1.28. When the dragline was located within the boundaries of section 7, the dump construction works should be conducted only if the dump exist for up to 3 years. Based on the identified parameters, on the example of using the ESH-11/70 walking dragline, a technological scheme of its operation was developed with the allocation of safe boundaries for its placement when forming an internal dump. The results obtained are useful for the development of projects for the reclamation of depleted open pits.

Sorption and desorption of naphthenic acids on reclamation materials: Mechanisms and selectivity of naphthenic acids from oil sands process water

This study investigated the application of materials peat-mineral mix (PT) and Pleistocene fluvial sands from different location (PF-1 and PF-2) obtained from surface mining of oil sands as sorbents of naphthenic acids (NAs) from oil sands process water (OSPW). To understand the sorption properties and mechanisms of NAs in the materials, sorption and desorption studies were performed using decanoic acid (DA) and 5-phenylvaleric acid (PVA). Additionally, the removal efficiency was evaluated using real OSPW to understand the effect of NA structure on sorption. Equilibrium of DA and PVA was reached at 2 days for PT, and 3 and 6 days for PF materials, respectively. Langmuir isotherm best fitted the equilibrium data. Maximum sorption capacities for DA and PVA were, respectively, 16.8 × 103 and 104 mg/kg for PT, 142.9 and 81.3 mg/kg for PF-1, and 600 and 476.2 mg/kg for PF-2. Hydrophobic interactions, hydrogen bonding, and π−π interaction were the main sorption mechanisms. Desorption of model compounds from post-sorption materials was not observed for 14 days. The removal of NAs from real OSPW ranged from 20 to 54%. PT is the most promising sorbent of NAs from OSPW because it partially removed NAs with a wide range of molecular weights and structures at very low dosage. Sorption of NAs was affected by the total organic carbon of the materials, emphasizing the hydrophobic interaction as an important sorption mechanism. The results suggest that some mobility of NAs is expected to take place if the reclamation materials come in contact with OSPW, which might occur in an oil sands reclamation landscape.

Economics of in-space industry and competitiveness of lunar-derived rocket propellant

Economic parameters are identified for an in-space industry where the capital is made on one planet, it is transported to and teleoperated on a second planet, and the product is transported off the second planet for consumption. This framework is used to model the long-run cost of lunar propellant production to help answer whether it is commercially competitive against propellant launched from Earth. The prior techno-economic analyses (TEAs) of lunar propellant production had disagreed over this. The “gear ratio on cost” for capital transport, G, and the production mass ratio of the capital, φ, are identified as the most important factors determining competitiveness. The prior TEAs are examined for how they handled these two metrics. This identifies crucial mistakes in some of the TEAs: choosing transportation architectures with high G, and neglecting to make choices for the capital that could achieve adequate φ. The tent sublimation technology has a value of φ that is an order of magnitude better than the threshold for competitiveness even in low Earth orbit (LEO). The strip mining technology is closer to the threshold, but technological improvements plus several years of operating experience will improve its competitiveness, according to the model. Objections from members of the aerospace community are discussed, especially the question whether the technology can attain adequate reliability in the lunar environment. The results suggest that lunar propellant production will be commercially viable and that it should lower the cost of doing everything else in space.

Mine Pit Wall Geological Mapping Using UAV-Based RGB Imaging and Unsupervised Learning

In surface mining operations, geological pit wall mapping is important since it provides significant information on the surficial geological features throughout the pit wall faces, thereby improving geological certainty and operational planning. Conventional pit wall geological mapping techniques generally rely on close visual observations and laboratory testing results, which can be both time- and labour-intensive and can expose the technical staff to different safety hazards on the ground. In this work, a case study was conducted by investigating the use of drone-acquired RGB images for pit wall mapping. High spatial resolution RGB image data were collected using a commercially available unmanned aerial vehicle (UAV) at two gold mines in Nevada, USA. Cluster maps were produced using unsupervised learning algorithms, including the implementation of convolutional autoencoders, to explore the use of unlabelled image data for pit wall geological mapping purposes. While the results are promising for simple geological settings, they deviate from human-labelled ground truth maps in more complex geological conditions. This indicates the need to further optimize and explore the algorithms to increase robustness for more complex geological cases.

V-Type Firing Pattern in Blasting: Evidence to Substantiate the Improved Fragmentation

Firing sequence of blastholes in blasting is an inherent part of the blast design for various reasons that range from the spatial requirements to the control of throw during blasting in surface mines. Despite several such patterns in vogue, role of firing sequences in defining the size of fragmented block sizes is not properly understood. The V-type firing pattern is believed to improve blast fragmentation because of the collision of moving fragments during the blasting process, thus resulting in further breakage. There are practically negligible studies that substantiate this assertion. The role of V-type firing pattern has been explored in this paper with simple logic and some field data. It is observed that the V-type firing pattern produces better fragmentation and controls the throw during blasting. A comparison with diagonal firing pattern, in controlled experiments, makes it evident that V-type firing pattern can be used to advantage for fragmentation improvement.

Incorporating Environmental Impacts into Short-Term Mine Planning: A Literature Survey

This paper aims to address the significant financial, environmental, and social risks posed by climate change to the mining industry, which is responsible for approximately 8% of global greenhouse gas emissions. With 70% of mining projects for the six largest mining companies located in water-stressed regions, the industry is facing increasing pressure to reduce its impact. Our study investigates the applicability of multi-objective optimization to integrate environmental impact considerations into short-term planning for mining operations. To achieve this, we have reviewed similar studies in various industries and developed an integrated planning framework that incorporates environmental considerations into production planning for surface mines. Our framework has the potential to be utilized in both short- and long-term planning horizons, promoting sustainable mining practices. Through this research, we aim to provide mining engineers with a more comprehensive and effective approach to minimize the environmental impacts of their operations while maintaining efficient production.

Assessment of the Capability of Landsat and BiodivMapR to Track the Change of Alpha Diversity in Dryland Disturbed by Mining

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.

A scientometrics view on sustainable development in surface mining: Everything from the beginning

In summary, the study on sustainable development in the late 20th century aimed to balance economic, social, and environmental factors in open-pit mining. The study found that while mining has negative ecological impacts, it also has positive economic and social benefits. The study analyzed 77 articles and found a growing trend in scientific interest in sustainable development research from 1985 to 2022. This suggests that there has been a growing trend in using qualitative research methods in studies related to sustainable development in the mining industry in the past ten years. This is likely due to a shift in focus toward finding ways to improve the positive impacts and mitigate the negative impacts of this development in light of technology advancements and changes in environmental and social regulations. This highlights the importance of using a comprehensive approach that considers all aspects of sustainable development in studying small-scale mining. Given the significance of small-scale mining to the economies of many mining communities, it is crucial to develop clear regulations and guidelines that align with the principles of sustainable development. This will help ensure that the industry operates responsibly and sustainably. This statement emphasizes the importance of updating research methods to reflect the latest technological advancements and the interdisciplinary nature of sustainable development. As technology and other fields of study continue to advance and intersect with the issue of sustainable development in the mining industry, it is essential to incorporate these new advancements and perspectives into future studies. This will help ensure that research in this area remains relevant and comprehensive.