Multi-scale Analysis of TSFs

The Geospatial Artificial Intelligence Analysis for Tailings Storage Facilities (GAIA-TSF) aims to design and develop the prototype of a system based on satellite earth observation and machine learning algorithms to achieve continuous multi-level/multi-scale characterisation and monitoring of Tailings Storage Facilities (TSFs).

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Why GAIA-TSF?

Tailings Storage Facilities play a critical role in the mining industry, but their management poses significant environmental and safety risks. Traditional monitoring methods can be reactive and resource-intensive. GAIA-TSF leverages advanced satellite technology and AI-driven models to offer a proactive, scalable, and efficient solution to detect anomalies and predict risks in real-time.

By relying global expertise from Spain, Portugal, Netherlands, Czech Republic, Zambia, and South Africa, GAIA-TSF is at the forefront of innovation, working collaboratively with mining authorities and industry leaders to address this pressing challenge.

Defining Key Monitoring Variables

GAIA TSF aims to establish a comprehensive set of Key Variables (KVs) for tracking anomalies and assessing risks associated with TSF operations. KVs are derived through an in-depth analysis of operational data provided by stakeholders in the mining industry. They serve as the foundation for designing a satellite data-based monitoring system, specifically tailored to meet the unique needs of these stakeholders.

Integrating Advanced Technologies

GAIA-TSF is dedicated to uniting the capabilities of Satellite Earth Observation (EO), geo-engineering data, and Machine Learning (ML). By harmonizing these disciplines, the project seeks to discover news synergy that enhances the precision, scalability, and effectiveness of TSF monitoring solutions. This integration will set new benchmarks for operational efficiency and risk mitigation.

Prototyping Next-Generation Applications

Our goal is to design and refine a state-of-the-art prototype system that merges satellite EO, in-situ measurements, and advanced ML models. This innovative system will enable automatic detection of anomalies, provide predictive risk analysis with clear explanations, and deliver continuous monitoring at multiple scales. By achieving these objectives, GAIA-TSF is transforming TSF monitoring into a proactive, technology-driven process that prioritizes safety, sustainability, and operational excellence.