About
Remote sensing techniques serve a critical role in the identification, exploration and prediction of beryllium. Australia's national science agency, CSIRO, developed continental-scale mineral maps in 1999 using data from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. These maps were groundbreaking at the time but are now considered too coarse in many situations to be highly accurate for mineral prospecting. More recent examples applied to beryllium include:
Dr. Bryony Richards, a senior research scientist with the Energy & Geoscience Institute (EGI) at the University of Utah, is developing a satellite-based exploration framework to map hydrothermal alteration associated with beryllium mineralization at Spor Mountain, Utah, the world's largest known bertrandite (Be) resource. Because the ore mineral itself lacks strong spectral signatures, Richards integrates multispectral data from NASA and JAXA platforms, including Sentinel-2, Landsat-8/9, and ASTER, with advances in computing to detect alteration-proxy minerals such as Al-OH clays, silica fronts, iron oxides, and fluorine-enriched lithologies.
By combining satellite imagery, synthetic aperture radar (SAR) structural analysis, and field validation, her work delineates fracture-controlled fluid pathways and alteration domains across areas exceeding 100 km². In addition, Richards is advancing hyperspectral imaging analysis to acquire higher-resolution data closer to the ground, enabling refinement of mineral targets and supporting scalable, domestic critical mineral resource assessment.
Li et al. (2025) and Gao et al. (2025) successfully mapped beryllium deposits in the central Altyn region in Xinjiang, China by integrating remote sensing data with geological datasets that were validated by field observations in areas with harsh natural conditions. Remote sensing image enhancement techniques including Principal Component Analysis (PCA), Independent Component Analysis (ICA), and…
The talk
Credits and licence
- Institution
- CERN
- Speaker
- Josef Sobieraj
- Year
- 2026
- Language
- English
- Source
- CERN
- Licence
- CERN, as CERN states it. CERN's terms
- Attribution
- © CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
- Who can watch
- CERN gives no rating. Invisible Network shows it to Teens profiles and older, judged from what the source says about it. How courses are placed