Project
Integrated Hyperspectral Imaging System for Non-Invasive Mineral–Mechanical
Diagnostics, Critical Mineral Exploration, and Infrastructure Resilience
Founder Institution
NSERC Research Tools and Instruments Grant. Co-PI: Jeff Boisvert, Michael Hendry, Renato Macchiotta, Yitong Li
Program 1: Non-Invasive Mineral–Mechanical Diagnostics and Real-time Data-Driven Decision
Making for Subsurface Energy, Mining and Transportation System; Program 2: Critical Minerals Mapping and Exploration; Program 3: Wildland Fire, Climate Hazard, and Post-Disaster Assessment
More Details
The University of Alberta hosts one of Canada’s leading research environments for subsurface geomechanics research through the GeoInnovation Environments and two CFI-JELF projects, including Temperature-control Structure-Property Characterization (TSPC) system (CFI-JELF #45115) and Integrated Quadruped Robotic Sensing System (IQRSS) (CFI-JELF #44363). These platforms enable integrated and multidisciplinary research activities that enable breakthroughs in subsurface energy diversification (fossil fuel, carbon storage, geothermal and nuclear energy), minerals exploration and extraction, and infrastructure monitoring at both lab and field scale. However, a critical capability is absent across existing facilities: non-invasive mineralogical, chemical, moisture content and species imaging and identification. Without hyperspectral imaging (HSI), neither laboratory nor field research at UAlberta can spatially characterize oxidation, hydration, or weathering processes that govern mechanical degradation in geomaterials and infrastructures. The need for hyperspectral capability is urgent and driven by national research priorities in critical minerals development, carbon and energy (hydrogen) storage, geothermal systems, and climate-resilient infrastructure. Hyperspectral imaging provides full-field, non-contact mineral and alteration mapping, enabling correlations between mineral chemistry and mechanical response and serving as an essential requirement for predictive geomechanical models, critical minerals mapping, and AI-driven hazard assessment. These instruments capture essential diagnostic features of iron oxidation, hydration fronts, and surface weathering, which are proven precursors to mechanical instability in rocks, tailings, and engineered infrastructure.