Drones in Mine Surveying Works
Mining is one of the most hazardous and high-risk industries. However, in order to reduce risks and operational costs, a promising technology has emerged — unmanned aerial vehicles (UAVs), commonly known as drones or quadcopters. Their use helps automate processes, increase data accuracy, improve personnel safety, and enhance the economic efficiency of mining enterprises.
Traditional methods of mine surveying services are associated with increased risk and require significant time, especially in complex and hard-to-reach areas. With the use of drones, these processes become faster and more efficient. Drones accelerate mining operations, reduce costs, help control extraction processes, and monitor material storage. The obtained geospatial data is characterized by high quality and accuracy, meeting the requirements of the Rules for Performing Mine Surveying Works during the Development of Ore and Non-Ore Mineral Deposits and enabling the creation and maintenance of up-to-date mining and graphical documentation.
One of the key advantages of using drones in mine surveying is their ability to quickly and accurately collect geodetic data of the terrain. Equipped with onboard GPS receivers and altitude sensors, drones can perform detailed flights over the work area and record precise coordinates and elevations of each point.
As mine surveying equipment, drones of various types are used depending on their characteristics and application. These typically include:
Multirotor drones — highly maneuverable platforms capable of collecting detailed data from different angles and altitudes.
Fixed-wing drones — suitable for long-range operations and extended flight times, widely used for large-scale mapping and environmental monitoring.
Helicopter-type drones — provide increased in-air stability and can be equipped with heavy sensors and cameras.
Hybrid drones — combine the advantages of multirotor and fixed-wing systems, offering greater versatility in various conditions.
There are many drone models and brands on the market specifically designed for mine surveying applications. The specific models used may vary depending on the manufacturer, technical specifications, and operational conditions.
Commonly used in mine surveying practice:
DJI Phantom — widely used drones equipped with high-quality cameras and stabilization systems for accurate terrain imaging.
SenseFly eBee — fixed-wing drones developed for mapping and geodetic surveys, offering long flight times and high data accuracy.
Trimble UX5 — fixed-wing drones with high-precision GPS navigation and autonomous flight capabilities.
Microdrones mdMapper — a comprehensive solution combining a drone with specialized data collection and processing software.
Airobotics Optimus — autonomous drones capable of operating without an on-site operator and equipped with thermal cameras for detecting temperature anomalies.
WingtraOne — drones capable of high-resolution aerial surveys and equipped with global navigation satellite systems.
The choice of a specific drone model depends on project requirements, budget, and regulatory constraints. Nevertheless, all such systems provide broad opportunities for analyzing slope stability and terrain profiles to detect deformations and landslides. This helps prevent hazardous collapses, develop effective work plans, optimize equipment use, and ensure worker safety.
Drones are also effective for repeated or periodic surveys of mining sites. This allows rapid determination of extracted material volumes, measurement of earth embankments and excavation depths after completed works, forecasting of remaining material, and verification of surface stability in relevant areas.
Thanks to modern software, data processing takes only a few hours, significantly reducing the time required for routine reporting tasks. This is especially useful for monitoring the implementation of the Mining Operations Development Plan, accounting of reserves and mineral depletion. The use of drones reduces labor intensity and costs, enables frequent surveys as needed, minimizes human-factor influence on data processing, and facilitates a transition to paperless spatial data management and reporting.