Remote Sensing Solutions for Mapping Mining Environments

Dear Colleagues,

The Raw Material (RM) and mining industrial sectors rely on various systems of infrastructures for efficient and productive operations such as plants, buildings, gas and water pipes, sewages, tailing dams, underground tunnels, transportations, etc. Such systems, normally located in harsh environments, need periodic inspection, maintenance and monitoring to maximize efficiency and minimize costs and risks. Mining infrastructures and installations are rarely renewed due to high costs involved or to ensure production continuity.

In the last years, the RM industrial sector is slowly adopting innovative techniques to improve productivity from existing assets and infrastructure, leveraging on continuous innovations in remote sensing methods, robotics, data processing methods and Artificial Intelligence. However, this digitalization process is not yet successfully and fully deployed in the mining field. More effective remote sensing solutions can be envisaged in order to innovate the RM sector and improve process efficiency.

This Special Issue, which stems from the EIT-RM project AMICOS – Autonomous Monitoring and Control System for Mining Plants (https://amicos.fbk.eu/), welcomes but is not limited to contributions in the following topics:

• Remote sensing in mining areas;
• Tailing dams and open pit mines monitoring;
• Underground 3D mapping;
• Simultaneous localization and mapping (SLAM);
• UAV/UGV and robotics data in the mining field;
• Data fusion;
• Multi-temporal data processing;
• Decision Support Systems;
• BIM in the mining sector;
• Spatial data analysis, modeling and visualisation;
• Spatial analyses;
• Case studies in mining.

You may choose our Joint Special Issue in Sensors.

Prof. Dr. Radosław Zimroz
Dr. Fabio Remondino
Dr. Denis Guilhot
Dr. Vittorio Cannas
Guest Editors

Manuscript Submission Information

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