Special Issue "Hyperspectral Imaging for Mineral Mapping"

A special issue of Minerals (ISSN 2075-163X).

Deadline for manuscript submissions: closed (1 October 2019).

Special Issue Editor

Dr. Véronique Carrere
E-Mail Website
Guest Editor
Laboratoire de Planétologie et Géodynamique de Nantes, University of Nantes, 2 rue de la Houssinière, BP92208 44322 NANTES Cedex 3, France
Interests: field and imaging spectroscopy: extraction of physical parameters, quantitative research, application to environmental geology
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Special Issue Information

Dear Colleagues,

Imaging spectroscopy (also called hyperspectral imaging or “HIS”) is one of the most powerful non-destructive remote sensing tools to obtain accurate mineralogical information about inaccessible targets—information which is often not available by other techniques. Identification of minerals and other geologic materials using visible to near infrared (VNIR), shortwave infrared (SWIR), and now longwave infrared (LWIR) spectroscopy is well established. Laboratory spectral studies have shown that spectral parameters such as absorption band shape, minimum position, depths, widths, areas, absolute reflectance, and combinations of these various parameters can be used to extract compositional information as well as quantify, or at least severely constrain, important physical and chemical properties such as major, and in some cases minor, element chemistry, endmember abundances, moisture content, grain size, etc.

Hyperspectral data in the VNIR-SWIR, extensively used in planetary exploration, have been available for over 30 years, and analysis of these for geologic applications is considered mature. With a number of planned Earth observation hyperspectral missions such as PRISMA (2018, Italy) and EnMAP (2020, Germany), after the Hyperion precursor, this non-destructive technology will be available for widespread monitoring and mapping of the complex Earth surface, in particular by extracting chemical and physical parameters. The aim of this special issue is to focus on recent advances in the understanding and the quantitative interpretation of mineral/rock spectral signatures in the VNIR, SWIR and LWIR spectral ranges in terms of chemical composition and physical properties, the understanding of intimate/areal mixtures as well as radiative transfer modeling.

Dr. Véronique Carrere
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Minerals is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • spectroscopy
  • hyperspectral remote sensing
  • spectral signature
  • mineral mapping
  • planetary surface composition and physical properties
  • VNIR-SWIR-MWIR-LWIR spectral range
  • absorption features
  • reflectance
  • emissivity
  • radiative transfer modeling
  • spectral deconvolution
  • mixture analysis

Published Papers (3 papers)

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Research

Open AccessFeature PaperArticle
Mineral Mapping and Vein Detection in Hyperspectral Drill-Core Scans: Application to Porphyry-Type Mineralization
Minerals 2019, 9(2), 122; https://doi.org/10.3390/min9020122 - 19 Feb 2019
Cited by 2
Abstract
The rapid mapping and characterization of specific porphyry vein types in geological samples represent a challenge for the mineral exploration and mining industry. In this paper, a methodology to integrate mineralogical and structural data extracted from hyperspectral drill-core scans is proposed. The workflow [...] Read more.
The rapid mapping and characterization of specific porphyry vein types in geological samples represent a challenge for the mineral exploration and mining industry. In this paper, a methodology to integrate mineralogical and structural data extracted from hyperspectral drill-core scans is proposed. The workflow allows for the identification of vein types based on minerals having significant absorption features in the short-wave infrared. The method not only targets alteration halos of known compositions but also allows for the identification of any vein-like structure. The results consist of vein distribution maps, quantified vein abundances, and their azimuths. Three drill-cores from the Bolcana porphyry system hosting veins of variable density, composition, orientation, and thickness are analysed for this purpose. The results are validated using high-resolution scanning electron microscopy-based mineral mapping techniques. We demonstrate that the use of hyperspectral scanning allows for faster, non-invasive and more efficient drill-core mapping, providing a useful tool for complementing core-logging performed by on-site geologists. Full article
(This article belongs to the Special Issue Hyperspectral Imaging for Mineral Mapping)
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Open AccessArticle
Rock Sample Surface Preparation Influences Thermal Infrared Spectra
Minerals 2018, 8(11), 475; https://doi.org/10.3390/min8110475 - 23 Oct 2018
Abstract
High-resolution laboratory-based thermal infrared spectroscopy is an up-and-coming tool in the field of geological remote sensing. Its spatial resolution allows for detailed analyses at centimeter to sub-millimeter scales. However, this increase in resolution creates challenges with sample characteristics, such as grain size, surface [...] Read more.
High-resolution laboratory-based thermal infrared spectroscopy is an up-and-coming tool in the field of geological remote sensing. Its spatial resolution allows for detailed analyses at centimeter to sub-millimeter scales. However, this increase in resolution creates challenges with sample characteristics, such as grain size, surface roughness, and porosity, which can influence the spectral signature. This research explores the effect of rock sample surface preparation on the thermal infrared spectral signatures. We applied three surface preparation methods (split, saw, and polish) to determine how the resulting differences in surface roughness affects both the spectral shape as well as the spectral contrast. The selected samples are a pure quartz sandstone, a quartz sandstone containing a small percentage of kaolinite, and an intermediate-grained gabbro. To avoid instrument or measurement type biases we conducted measurements on three TIR instruments, resulting in directional hemispherical reflectance spectra, emissivity spectra and bi-directional reflectance images. Surface imaging and analyses were performed with scanning electron microscopy and profilometer measurements. We demonstrate that surface preparation affects the TIR spectral signatures influencing both the spectral contrast, as well as the spectral shape. The results show that polished surfaces predominantly display a high spectral contrast while the sawed and split surfaces display up to 25% lower reflectance values. Furthermore, the sawed and split surfaces display spectral signature shape differences at specific wavelengths, which we link to mineral transmission features, surface orientation effects, and multiple reflections in fine-grained minerals. Hence, the influence of rock surface preparation should be taken in consideration to avoid an inaccurate geological interpretation. Full article
(This article belongs to the Special Issue Hyperspectral Imaging for Mineral Mapping)
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Open AccessArticle
Mapping Surface Quartz Content in Sand Dunes Covered by Biological Soil Crusts Using Airborne Hyperspectral Images in the Longwave Infrared Region
Minerals 2018, 8(8), 318; https://doi.org/10.3390/min8080318 - 26 Jul 2018
Cited by 1
Abstract
Biological soil crusts (BSCs), composed of cyanobacteria, algae, mosses, lichens, and fungi, are important ecosystem engineers that stabilize the quartz-rich dunes in the Nitzana study area near the Israel–Egypt border. The longwave infrared (LWIR) region of the electromagnetic spectrum is very useful for [...] Read more.
Biological soil crusts (BSCs), composed of cyanobacteria, algae, mosses, lichens, and fungi, are important ecosystem engineers that stabilize the quartz-rich dunes in the Nitzana study area near the Israel–Egypt border. The longwave infrared (LWIR) region of the electromagnetic spectrum is very useful for quartz identification since quartz reflectance in the visible, near infrared, and shortwave infrared (VIS-NIR-SWIR, 0.4–2.5 µm) spectral regions lacks identifying features, whereas in the LWIR region, the quartz emissivity spectrum presents a strong doublet feature. This emissivity feature can be used as a diagnostic tool for BSCs development in desert environments, because BSCs attenuate the quartz feature as a function of their successional development. A pair of day and night airborne hyperspectral images were acquired using the Specim AisaOWL LWIR sensor (7.7–12 µm) and processed using an innovative algorithm to reduce the atmospheric interference in this spectral domain. The resulting day and night apparent emissivity products were used to produce a surface quartz content map of the study area. The significant reduction in atmospheric interference resulted in a high correlation (R2 = 0.88) between quartz content in field samples determined by X-ray powder diffraction analysis and emissivity estimations from the airborne images. This, in turn, served as the ground truth to our quartz content map of the surface, and by proxy to the BSC. Full article
(This article belongs to the Special Issue Hyperspectral Imaging for Mineral Mapping)
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