In the heart of Türkiye, a groundbreaking study is reshaping how we monitor and manage open-pit mines, offering a glimpse into a future where technology and geospatial analysis converge to enhance safety and efficiency. Led by Abdurahman Yasin Yiğit from the Department of Geomatics Engineering at Mersin University, this research leverages the power of unmanned aerial vehicles (UAVs) and advanced photogrammetry to transform the way we assess surface changes and stability in mining operations.
The study, published in the journal *Drones* (translated from Turkish), focuses on an active marble quarry in Dinar, Türkiye. By combining high-resolution images captured in 2024 and 2025 with dense point clouds generated through Structure from Motion (SfM) methods, Yiğit and his team have developed a sophisticated approach to quantify surface changes and identify potential risk areas. “The integration of UAV photogrammetric data with geospatial analysis allows us to detect even the slightest morphological transformations, which is crucial for ensuring site safety and slope stability,” Yiğit explains.
One of the key findings of the study is the significant volumetric changes observed in the quarry. The researchers noted a volumetric increase of 7,744.04 cubic meters in the dump zones, accompanied by an excavation loss of 8,359.72 cubic meters, resulting in a net difference of approximately 615.68 cubic meters. These changes were meticulously quantified using Iterative Closest Point (ICP) registration and Multiscale Model-to-Model Cloud Comparison (M3C2) analysis, with an impressive root mean square error (RMSE) of just 2.09 centimeters.
The study also introduced a holistic approach to evaluating surface risk factors by analyzing various morphometric criteria. Parameters such as surface variation, roughness, verticality, planarity, and linearity were used to identify zones of increased instability. Yiğit emphasizes the importance of these measures: “By understanding the surface characteristics, we can better predict potential failure zones and take proactive measures to mitigate risks.”
The integration of point cloud modeling derived from UAVs with GIS-based spatial analysis has revealed that morphological anomalies are spatially correlated with possible failure zones. This correlation is a game-changer for the mining industry, as it allows for more accurate risk assessment and better-informed decision-making. “This research not only enhances our understanding of surface changes but also provides a robust framework for monitoring and managing open-pit mines,” Yiğit adds.
The implications of this research extend beyond the mining sector, with significant commercial impacts for the energy industry. As the demand for raw materials continues to grow, the need for efficient and safe mining practices becomes increasingly critical. By adopting the methods outlined in this study, energy companies can optimize their operations, reduce risks, and ensure the sustainability of their mining activities.
Looking ahead, this research paves the way for future developments in the field of geospatial analysis and UAV technology. As Yiğit and his team continue to refine their methods, we can expect to see even more sophisticated approaches to monitoring and managing mining operations. The integration of advanced technologies with geospatial analysis is not just a step forward; it’s a leap towards a safer, more efficient, and sustainable future for the mining and energy sectors.
In the words of Yiğit, “The future of mining lies in our ability to harness the power of technology and data to make informed decisions and ensure the safety of our operations.” With this research, we are one step closer to realizing that vision.