Hyperspectral imaging in geoscience
Hyperspectral imaging is a powerful method for remote analysis of an object’s composition. In geoscience applications, mapping material content and distribution can give important insights that can be difficult to obtain from traditional sampling or conventional photographs. In outcrop geology, mapping mineral and rock types can be a vital first step towards understanding petrophysical properties (e.g. porosity and permeability) of an exposed section. Where physical sampling can be expensive and time-consuming, especially in inaccessible and remote field areas, hyperspectral imaging is an efficient way to quantitatively map materials remotely. Using non-visible parts of the electromagnetic spectrum, sampled with extremely high spectral resolution, allows material differences to be identified that may be very difficult to see on conventional photographs or in the field.
Hyperspectral imaging field setup.
The VOG Group has pioneered the use of spectral imaging in geology, with experience built up over the last decade. Our expertise includes the scanning of near-vertical cliff sections (such as geological outcrops and mine faces), tunnels, buildings facades, as well as spectral analysis of drill cores and samples. The method is increasingly valuable for a broadening range of applications within our project portfolio, including CO2 sequestration, characterising clay materials in subterranean storage sites for hazardous waste, mapping economically-viable materials in historic mine waste, geohazards, cultural heritage and in the natural world.
Hyperspectral imaging of carbonate quarry in Cantabria, Spain, showing mapped material classes (limestone, dolomite types, calcite etc) overlaid on photorealistic 3D model using in-house LIME software (see Buckley et al., 2013).
A fundamental part of the VOG Group’s work has been the tight coupling of the spectral mapping results with geometric methods, such as lidar and photogrammetry. In-house software allows registration of the two data types and visualisation of multi-layered textured models. Linking the two allows material distributions to be obtained in 3D space, which makes it possible to measure and perform quantitative analysis, as well as develop novel visual products to communicate end results.
Overlay of hyperspectral results on photorealistic lidar model. Left: mapped rock types; right: vector class representing carbonate nodules projected into 3D space for area calculation. Height of cliff is c. 10 m. Image based on Kurz et al. (2013).
Using portable imaging equipment, hyperspectral methods offer added value both in the field and in the laboratory, by allowing non-contact and high resolution identification and description of material.
Map of iron content in cross section through historic mine waste material, for potential recycling of economically-viable ore. Image based on Denk et al. (2015), collaboration with the Department of Geography and Geoscience, Martin Luther University Halle-Wittenberg, funded through the Research Council of Norway and DAAD.