Harnessing imaging spectroscopy for multivariate rock sorting in the mine environment

The proposed research focuses on imaging spectroscopy of geological materials encountered at mineral deposits. Imaging spectroscopy (also known as hyperspectral imaging) in the geosciences traditionally utilizes airborne or spaceborne platforms but ground-based studies at outcrop and smaller scales are becoming more common. This technique collects reflectance data as images, and allows quick analysis of specific mineralogical properties that are visually undetectable (e.g., phyllosilicate mineralogy). We will investigate mineralogical and geochemical variability and spectral characteristics of various ore and non-ore lithologies from three mineral deposits. Results will improve the understanding of spectroscopy from these ore deposits and will also provide information exploitable by the mining industry. In particular, this research will directly guide how to integrate imaging spectroscopy into multivariate rock sorting methodologies developed by MineSense Technologies. Mineralogical information available through imaging spectroscopy complements the companys existing sensor suite, and can potentially improve decision making for ore acceptance or waste rejection.

Faculty Supervisor:

Lee Groat

Student:

David Turner

Partner:

MineSense Technologies

Discipline:

Geography / Geology / Earth science

Sector:

Mining and quarrying

University:

Program: