This report describes the preliminary re.wlts of surficial geological mapping during the 1992 field season in the Chilanko Forks (93Cil) and Chezacut 193CiX) map areas (Figure 4. IO-1 ). As part of the Canad;~ f3ritish Cofumhia Mineral Developme~~t Agreement, the British Columbia Geological Survey Rranch proposed to map the surlicial geology of these weiis to deriw drift exploration potential m...

Reflectance and emittance spectroscopy in the near-infra red and short-wave infra red offers a rapid, Inexpensive, non-destructive tool for determining the mineralogy of rock and soil samples. Hyperspectral remote sensing has the potential to provide the detailed physico-chemistry (mineralogy, chemistry, morphology) of the earth’s surface. This information is useful for mapping potential host r...

The spectral and spatial properties of the advanced spaceborne thermal emission and reflection radiometer (ASTER) data can be used in detailed lithological and hydrothermal alteration mapping related to copper and gold mineralization, particularly the shortwave infrared radiation subsystem where hydrothermal alteration minerals have diagnostic spectral absorption features. This paper reviews th...

Biofortification of foods, achieved by increasing the concentrations of minerals such as iron (Fe) and zinc (Zn), is a goal of plant scientists. Understanding genes that influence seed mineral concentration in a model plant such as Arabidopsis could help in the development of nutritionally enhanced crop cultivars. Quantitative trait locus (QTL) mapping for seed concentrations of calcium (Ca), c...

New “geoscience-tuned” remote sensing technologies are now available (e.g. satellite-borne multi-spectral ASTER and airborne HyMap imaging systems) or soon to be available (e.g. satellite hyperspectral Hyper-J and EnMap systems) for the resources (energy, minerals and soils) community. These imaging sensors have the potential to provide global information at high spatial resolution for baseline...

We briefly review the state-of-the-art machine learning (ML) algorithms for mineral exploration, which mainly include random forest (RF), convolutional neural network (CNN), and graph (GCN). In recent years, RF, a representative shallow algorithm, CNN, deep approach, have been proved to be powerful tools ML-based mapping exploration. future, GCN deserves more attention exploration because of it...

Hyperspectral imaging technology has been used for geological analysis for many years wherein mineral mapping is the dominant application for hyperspectral images (HSIs). The very high spectral resolution of HSIs enables the identification and the diagnosis of different minerals with detection accuracy far beyond that offered by multispectral images. However, HSIs are inevitably corrupted by no...

Hydrothermal processes in the Earth’s crust can result in ore deposits characterized by high concentrations of metals with fractal or multifractal properties. This paper shows that stream sediments in the neighborhoods of ore deposits also can have singular properties for ore-mineral and associated toxic trace elements. We propose a new local singularity mapping method for assembling element co...