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12 pages, 924 KB

Open AccessArticle

Quantitative Assessment of Pit Lake Rehabilitation Using Virtual Reality Imagery and Machine Learning Validation

by Emmanouil A. Varouchakis, Evangelos Machairas, Ioulia Koroptsenko, Stylianos Tampouris, Christos Stenos and Michail Galetakis

Geosciences 2026, 16(4), 149; https://doi.org/10.3390/geosciences16040149 - 7 Apr 2026

Viewed by 54

Abstract

The growing demand for Critical Raw Materials (CRMs) requires mining practices that align with sustainability and environmental, social, and governance (ESG) principles, while mining training increasingly benefits from advanced digital tools. Virtual Reality (VR) can provide high-resolution site representations that support both interactive learning and data-oriented analysis without operational risk. This study presents a VR-based framework for the quantitative assessment of pit lake rehabilitation using Virtual Excursions (VEs) developed from panoramic imagery and supported by machine-learning correction. High-resolution 360° panoramic images were used to extract geometric characteristics of a rehabilitated pit lake at the LARCO GMMSA Euboea mine site, Greece, including surface area, shoreline length, mean diameter, and maximum diameter. These image-derived estimates were validated against ground-truth data from field surveys and mine-closure documentation. To reduce systematic deviations associated with panoramic image measurements, a supervised multiple linear regression model was applied as a correction step. Validation based on Root Mean Square Error (RMSE) and the coefficient of determination (

R^{2}

) showed substantial improvement of the corrected estimates relative to the uncorrected image-based measurements. The results demonstrate that panoramic VR imagery can support site-specific quantitative environmental assessment in addition to its educational value. Although the present findings are limited to a single pit lake case study, the proposed workflow provides a structured basis for integrating immersive visualization, image-based measurement, and regression-based correction in post-mining rehabilitation assessment. Full article

(This article belongs to the Topic From Earth to Innovation: Modern Trends in Mining, Geoinformation, and Geoscientific Applications)

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1 pages, 126 KB

Open AccessCorrection

Correction: Fuławka et al. Frequency-Dependent Slope Stability Under Earthquake Loading: A Parametric Study with Hybrid FEM–LEM. Geosciences 2025, 15, 460

by Krzysztof Fuławka, Bogumiła Pałac-Walko and Lech Stolecki

Geosciences 2026, 16(3), 115; https://doi.org/10.3390/geosciences16030115 - 12 Mar 2026

Viewed by 158

Abstract

There was an error in the original publication [...] Full article

(This article belongs to the Topic From Earth to Innovation: Modern Trends in Mining, Geoinformation, and Geoscientific Applications)

24 pages, 13566 KB

Open AccessArticle

Comparative Evaluation of Empirical and Numerical Approaches for Ground Support Design: A Case Study from the Gilar Underground Mine

by Suleyman Ismayilov, Krzysztof Fuławka, Karolina Adach-Pawelus and Anar Valiyev

Geosciences 2026, 16(1), 19; https://doi.org/10.3390/geosciences16010019 - 30 Dec 2025

Cited by 1 | Viewed by 936

Abstract

The stability of underground excavations is a critical factor in the safety and efficiency of mining operations, particularly in structurally complex and geomechanically variable rock mass. This study presents a comparative evaluation of empirical and numerical methods for the design of tunnel support systems in the Gilar underground mine, located in the Gedabek Contract Area of Azerbaijan. To validate and optimize the empirical Q-system-based support designs, Finite Element Method (FEM) simulations were conducted using RS2 software. These simulations enabled the modeling of stress distribution, deformation, and support–rock interaction under in situ conditions. Critical sections along the main ramp were analyzed in detail to determine safety factors during excavation and post-support installation. The study reveals that, although the Q-system provides a practical and time-efficient method for support selection, it may underestimate the reinforcement required in highly fractured or low-strength zones. Numerical modeling proved to be essential in identifying zones with low strength factors and in optimizing support configurations by adjusting rockbolt spacing and shotcrete thickness. The hybrid approach adopted in this study—empirical classification followed by numerical verification and optimization—demonstrated significant improvements in long-term tunnel stability. This research highlights the importance of integrating empirical and numerical approaches for robust ground support design in underground mining. The proposed methodology not only enhances the accuracy of support recommendations but also provides a more reliable basis for decision-making in complex geological settings. The results are particularly relevant for deep and geologically active mines requiring long-term stability of access tunnels. Full article

(This article belongs to the Topic From Earth to Innovation: Modern Trends in Mining, Geoinformation, and Geoscientific Applications)

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22 pages, 3716 KB

Open AccessArticle

Frequency-Dependent Slope Stability Under Earthquake Loading: A Parametric Study with Hybrid FEM–LEM

by Krzysztof Fuławka, Bogumiła Pałac-Walko and Lech Stolecki

Geosciences 2025, 15(12), 460; https://doi.org/10.3390/geosciences15120460 - 3 Dec 2025

Cited by 1 | Viewed by 592 | Correction

Abstract

The correct assessment of slope stability under seismic loading requires not only the magnitude of ground acceleration to be considered but also its frequency content. In this study, a hybrid finite element/limit equilibrium (FEM–LEM) approach is used to quantify how the dominant frequency of harmonic ground motion affects the dynamic factor of safety, FSdyn, of a large homogeneous slope. Dynamic stresses are computed in QUAKE/W and transferred to SLOPE/W, where a FS calculation is performed at each time step to obtain FS_dyn(t). A design-of-experiment framework is applied to explore combinations of peak ground acceleration and dominant frequency. The results show that FS_dyn is much more sensitive to dominant frequency than to acceleration amplitude within the analyzed ranges, with the strongest reduction in stability occurring with the low input frequencies. Comparison with conventional pseudo-static analysis demonstrates that pseudo-static factors of safety can significantly overestimate stability at low dominant frequencies, and frequency thresholds are identified above which pseudo-static results become closer to the hybrid solution for the studied configuration. Although the model is intentionally simplified (homogeneous, drained conditions and single-frequency excitation), the findings highlight that dominant frequency is a decisive control parameter and should not be neglected in the seismic assessment of large earth structures. Full article

(This article belongs to the Topic From Earth to Innovation: Modern Trends in Mining, Geoinformation, and Geoscientific Applications)

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25 pages, 9230 KB

Open AccessArticle

Analysis of the Statistical Relationship Between Vertical Ground Displacements and Selected Explanatory Factors: A Case Study of the Underground Gas Storage Area, Kosakowo, Poland

by Anna Buczyńska, Aleksandra Kaczmarek, Dariusz Głąbicki and Jan Blachowski

Remote Sens. 2025, 17(23), 3912; https://doi.org/10.3390/rs17233912 - 2 Dec 2025

Viewed by 627

Abstract

Underground gas storage (UGS) facilities may cause ground displacements as a result of the cavern convergence or regular gas injection (alternate ground uplift and subsidence). The occurrence and scale of displacements are strongly dependent on the storage time and cavern capacity. At an early stage of facility operation, displacements can be difficult to detect in the presence of wetlands. The main objective of this study was to describe the global and local relationships between vertical ground displacements observed over a small and relatively new Kosakowo UGS facility (Poland) from 2014 to 2024 (dependent variable) and selected topographic, hydrological, and mining factors (independent variables). The dependent variable was determined through SBAS-InSAR analysis of Sentinel-1 SAR data, while the independent variables were developed using passive Sentinel-2 imagery and open geospatial data. The global relationships between variables were described using Ordinary Least Squares (OLS) and Generalized Linear Regression (GLR) models, while the Geographically Weighted Regression (GWR) model was utilized to analyze local relations. The results obtained indicate that ground displacements were characterized by seasonal fluctuations between 4 mm and 10 mm. The factors that had, both globally and locally, the strongest influence were soil moisture, vegetation water content, and the flora condition, indicating that the environmental hydrogeology had the greatest impact on the phenomenon under study. None of the considered models identified underground gas storage as a significant contributing factor to the observed ground displacements. The results confirm that the presence of wetlands can be a significant obstacle to an accurate description of the impact of gas storage on the ground movements, especially in UGS areas at an early stage of operation. Full article

(This article belongs to the Topic From Earth to Innovation: Modern Trends in Mining, Geoinformation, and Geoscientific Applications)

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25 pages, 49354 KB

Open AccessArticle

Displacement Time Series Forecasting Using Sentinel-1 SBAS-InSAR Results in a Mining Subsidence Case Study—Evaluation of Machine Learning and Deep Learning Methods

by Dariusz Głąbicki

Remote Sens. 2025, 17(23), 3905; https://doi.org/10.3390/rs17233905 - 2 Dec 2025

Viewed by 1416

Abstract

With an abundance of data provided by satellite-based measurements, such as Synthetic Aperture Radar Interferometry (InSAR) or the Global Navigation Satellite System (GNSS), an interest has grown in training highly complex data-driven models for geophysical applications, including displacement modeling. These methods, including machine learning (ML) and deep learning (DL) algorithms, represent a new approach to forecasting ground surface displacements. Yet, the effectiveness of such methods, including their generalization capabilities and performance on non-linear data, remains underexplored. This paper examines the performance of various data-driven algorithms, including regression models and deep neural networks, in predicting mining-induced subsidence. Ground surface displacement data obtained from the Small Baseline Subset (SBAS) InSAR were used as time series samples for training and validation. ML and DL models were evaluated over varying forecast horizons. The results show that data-driven approaches can effectively model InSAR-derived ground subsidence in mining areas. Deep learning models outperform other ML-based models, indicating that increased model complexity can lead to better forecasting accuracy. Nevertheless, it is shown that careful examination of performance metrics and forecast errors in the spatial domain is essential for appropriate model evaluation. The findings demonstrate that combining SBAS-InSAR measurements with data-driven modeling offers a promising direction for developing automated systems for monitoring and forecasting mining-induced ground deformation. Full article

(This article belongs to the Topic From Earth to Innovation: Modern Trends in Mining, Geoinformation, and Geoscientific Applications)

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23 pages, 1917 KB

Open AccessArticle

Complexity of Water-Covered Land Use by the Extractive Industry in Terms of Legal, Economic and Environmental Protection Aspects in Poland and Malaysia

by Michał W. Dudek, Nurul Hana Adi Maimun and Ezdihar Hamzah

Water 2025, 17(23), 3418; https://doi.org/10.3390/w17233418 - 1 Dec 2025

Viewed by 950

Abstract

Our research aims to provide a comparative analysis of water governance components by presenting the complexity of water-covered land use by the extractive industry in terms of legal, economic, and environmental protection aspects in Poland and Malaysia, along with the corresponding regulations and their implications. This paper discusses the legal forms of land ownership and use, as well as the currently applied principles for calculating fees for using state-owned water covered land that contains mineral deposits. We also present a comparison of selected technologies for the extraction of sand and gravel aggregates under water with their environmental impact. This research highlights the need for specialized valuation frameworks tailored to the geological and regulatory landscape of Poland and Malaysia. We suggest that the market value of land located above a mineral deposit, calculated individually for each deposit-property, should serve as the basis for calculating the lease fee. This discussion should encompass not only the principles and methodology involved in estimating the magnitudes of lease rents on mining industry and its profitability, but also the identification and criteria for assessing the risks associated with ongoing or planned mining ventures and concerns about the protection of river ecosystems. Our research contributes in providing data to stakeholders on extractive industry that operates within flowing and standing inland waters. The key finding of our research is that, in our opinion, the water governance frameworks in Poland and Malaysia are inadequate for protecting public finances and for internalizing the environmental externalities inherent in the economics of mining. Full article

(This article belongs to the Topic From Earth to Innovation: Modern Trends in Mining, Geoinformation, and Geoscientific Applications)

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22 pages, 1749 KB

Open AccessArticle

Pułtusk H5 Chondrite—A Compilation of Chemical, Physical, and Thermophysical Data

by Katarzyna Łuszczek and Radosław A. Wach

Geosciences 2025, 15(11), 438; https://doi.org/10.3390/geosciences15110438 - 18 Nov 2025

Cited by 1 | Viewed by 887

Abstract

The Pułtusk meteorite, classified as an H5 ordinary chondrite, is one of the best documented Polish falls, yet some important data on its physical and thermophysical properties remain limited. This study provides new measurements and derived parameters of its physical and thermophysical properties that complement existing datasets for the Pułtusk meteorite and H chondrites in two important ways. Firstly, they cover a temperature range previously not explored. Secondly, using techniques generally applied in geology to validate the novel techniques developed recently, bulk and grain densities, porosity, and specific heat capacity were determined using the Archimedean method and differential scanning calorimetry, supported by bulk chemical analyses performed by ICP-MS and ICP-ES. The chemical composition of Pułtusk closely matches that of average H chondrites, though Fe and Ni contents are about 15–20% lower, likely due to weathering effects. Measured bulk density, grain density, and porosity are 3.30 g/cm³, 3.41 g/cm³, and 3.22%, respectively. The specific heat capacity increases from 564 to 1147 J/(kg·K) between 223 and 773 K, with 699 J/(kg·K) at 300 K. Derived thermophysical parameters include thermal conductivity, thermal diffusivity, and thermal inertia at 200 K, 300 K, and low pressure, and in ambient air. These results are consistent with previous data for H chondrites and confirm Pułtusk as a representative sample of this group. The new dataset can enhance the accuracy of models describing the Yarkovsky effect, meteoroid atmospheric entry, and the thermal evolution of ordinary chondrite parent bodies. Full article

(This article belongs to the Topic From Earth to Innovation: Modern Trends in Mining, Geoinformation, and Geoscientific Applications)

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Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Geosciences geosciences	2.1	5.1	2011	23.6 Days	CHF 1800
Minerals minerals	2.2	4.4	2011	17.7 Days	CHF 2400
Mining mining	-	4.0	2021	22.7 Days	CHF 1200
Remote Sensing remotesensing	4.1	8.6	2009	24.3 Days	CHF 2700
Water water	3.0	6.0	2009	18.9 Days	CHF 2600

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