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  • 1
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    A solar optical hyperspectral library of rare-earth-bearing minerals, rare-earth oxide powders, copper-bearing minerals and Apliki mine surface samples (2021)
    Copernicus
    Details
    Publication Date: 2021-03-09
    Description: Mineral resource exploration and mining is an essential part of today's high-tech industry. Elements such as rare-earth elements (REEs) and copper are, therefore, in high demand. Modern exploration techniques from multiple platforms (e.g., spaceborne and airborne), to detect and map the spectral characteristics of the materials of interest, require spectral libraries as an essential reference. They include field and laboratory spectral information in combination with geochemical analyses for validation. Here, we present a collection of REE- and copper-related hyperspectral spectra with associated geochemical information. The libraries contain reflectance spectra from rare-earth element oxides, REE-bearing minerals, copper-bearing minerals and mine surface samples from the Apliki copper–gold–pyrite mine in the Republic of Cyprus. The samples were measured with the HySpex imaging spectrometers in the visible and near infrared (VNIR) and shortwave infrared (SWIR) range (400–2500 nm). The geochemical validation of each sample is provided with the reflectance spectra. The spectral libraries are openly available to assist future mineral mapping campaigns and laboratory spectroscopic analyses. The spectral libraries and corresponding geochemistry are published via GFZ Data Services with the following DOIs: https://doi.org/10.5880/GFZ.1.4.2019.004 (13 REE-bearing minerals and 16 oxide powders, Koerting et al., 2019a), https://doi.org/10.5880/GFZ.1.4.2019.003 (20 copper-bearing minerals, Koellner et al., 2019), and https://doi.org/10.5880/GFZ.1.4.2019.005 (37 copper-bearing surface material samples from the Apliki copper–gold–pyrite mine in Cyprus, Koerting et al., 2019b). All spectral libraries are united and comparable by the internally consistent method of hyperspectral data acquisition in the laboratory.
    Print ISSN: 1866-3508
    Electronic ISSN: 1866-3516
    Topics: Geosciences
    Published by Copernicus
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  • 2
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    Hyperspectral and Lidar Data Applied to the Urban Land Cover Machine Learning and Neural-Network-Based Classification: A Review (2021)
    Molecular Diversity Preservation International
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    Publication Date: 2021-08-26
    Description: Rapid technological advances in airborne hyperspectral and lidar systems paved the way for using machine learning algorithms to map urban environments. Both hyperspectral and lidar systems can discriminate among many significant urban structures and materials properties, which are not recognizable by applying conventional RGB cameras. In most recent years, the fusion of hyperspectral and lidar sensors has overcome challenges related to the limits of active and passive remote sensing systems, providing promising results in urban land cover classification. This paper presents principles and key features for airborne hyperspectral imaging, lidar, and the fusion of those, as well as applications of these for urban land cover classification. In addition, machine learning and deep learning classification algorithms suitable for classifying individual urban classes such as buildings, vegetation, and roads have been reviewed, focusing on extracted features critical for classification of urban surfaces, transferability, dimensionality, and computational expense.
    Electronic ISSN: 2072-4292
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Published by Molecular Diversity Preservation International
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  • 3
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    Hyperspectral imaging data of the northern mine face and of laboratory samples of the copper-gold-pyrite mine Apliki, Nicosia District, Republic of Cyprus (2021)
    GFZ Data Services
    Details
    Publication Date: 2021-09-20
    Description: Abstract
    Description: The data set contains VNIR and SWIR raw and reference hyperspectral imaging data of the Apliki mine open cut and of samples from the surface of the mine measured in the laboratory. It is con-nected to the published spectral library and chemical analyses of 37 different surface materials from the copper-gold-pyrite mine Apliki in the Republic of Cyprus (Koerting et al., 2019). The field outcrop scan was acquired in March 2018 in cooperation with the Geological Survey Department of the Republic of Cyprus (GSD) and the German Research Centre for Geosciences (GFZ). The laboratory sample scan presented in this document is a collection of hyperspectral scans compiled in one large dataset. The hyperspectral data in the field and the lab were acquired with the HySpex sys-tem in a range of 414 – 2498 nm. The field data is shared as one VNIR and one SWIR radiance and reflectance data cube each. The laboratory data is shared as one full VNIR-SWIR (414 – 2450nm) reflectance data cube that was processed and corrected for the detector jump, data spikes and the last 8 SWIR bands were clipped due to a low signal to noise ratio (SNR). The data and the samples originate from fieldwork in the Republic of Cyprus and laboratory work at the GFZ Potsdam. A detailed description of the data acquisition and processing can be found in Koerting (2021).
    Keywords: copper mining ; mine surface weathering ; hyperspectral ; spectral library ; copper minerals ; Earth Remote Sensing Instruments 〉 Passive Remote Sensing 〉 Spectrometers/Radiometers 〉 Imaging Spectrometers/Radiometers ; EARTH SCIENCE 〉 SOLID EARTH 〉 ROCKS/MINERALS/CRYSTALS 〉 IGNEOUS ROCKS 〉 IGNEOUS ROCK PHYSICAL/OPTICAL PROPERTIES ; EARTH SCIENCE 〉 SOLID EARTH 〉 ROCKS/MINERALS/CRYSTALS 〉 METALS 〉 METALS PHYSICAL/OPTICAL PROPERTIES
    Type: Dataset , Dataset
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    DATA GFZ
  • 4
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    Mineral spectra and chemistry of 37 copper bearing surface samples from Apliki copper-gold-pyrite mine in the Republic of Cyprus (2019)
    GFZ Data Services
    Details
    Publication Date: 2021-09-20
    Description: Abstract
    Description: The data set contains mineral chemical analyses of 37 different surface materials from the copper-gold-pyrite mine Apliki in the Republic of Cyprus and their corresponding hyperspectral spectra. The field samples were sampled in March 2018 in cooperation of the Cyprus Geological Survey Department of the Republic of Cyprus (GSD) and the German Research Centre for Geosciences (GFZ). The hyperspectral data was acquired with the HySpex system in a range of 400 – 2500nm and is presented in a spectral library. Detailed information about the mineral specimen, sample area and geochemistry is presented in the data sheets. The spectral library presented here is part of a bigger collection of spectral libraries including samples from rare-earth minerals, rare-earth-oxides (Koerting et al., 2019a, http://doi.org/10.5880/GFZ.1.4.2019.004) and copper-bearing minerals (Koellner et al., 2019, http://doi.org/10.5880/GFZ.1.4.2019.003).
    Keywords: copper mining ; mine surface weathering ; hyperspectral ; spectral library ; copper mineral ; geochemical analyses ; EARTH SCIENCE 〉 SOLID EARTH 〉 ROCKS/MINERALS/CRYSTALS 〉 MINERALS 〉 MINERAL PHYSICAL/OPTICAL PROPERTIES ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOCHEMISTRY 〉 GEOCHEMICAL PROCESSES 〉 CHEMICAL WEATHERING ; EARTH SCIENCE 〉 SOLID EARTH 〉 ROCKS/MINERALS/CRYSTALS 〉 METALS 〉 METALS PHYSICAL/OPTICAL PROPERTIES ; Earth Remote Sensing Instruments 〉 Passive Remote Sensing 〉 Spectrometers/Radiometers 〉 Imaging Spectrometers/Radiometers
    Type: Dataset
    Format: 2 Files
    Format: application/octet-stream
    Format: application/octet-stream
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    DATA GFZ
  • 5
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    Mineral reflectance spectra and LIBS data of 18 lithium-bearing mineral samples (lepidolite, petalite and spodumene specimen) (2021)
    GFZ Data Services
    Details
    Publication Date: 2022-02-04
    Description: Abstract
    Description: The data set contains LIBS (Laser-Induced Breakdown Spectroscopy) emission spectra of 18 lithium-bearing minerals and their corresponding hyperspectral reflectance spectra. The data were collected within the research project LIGHTS (Lightweight Integrated Ground and Airborne Hyperspectral Topological Solutions, http://lights.univ-lorraine.fr/) which aims at developing a new exploration process for Li targets combining drone-borne hyperspectral data and field observations. Hyperspectral data were acquired with the HySpex system in a wavelength range of 414 - 2498 nm and are presented in a spectral library. Detailed information about the samples and area of spectral retrieval is presented in the data sheet below. The spectral library presented here expands the collection of spectral libraries including samples from rare-earth minerals, rare-earth-oxides (Koerting et al., 2019a) and copper-bearing minerals (Koellner et al., 2019) which are fully described in Koerting et al. (2021). These libraries aim to give a spectral overview of important resources and deposit mineralizations. 18 samples taken partly from the collections of the University of Potsdam (UP) and the Federal Institute for Geosciences and Natural Resources (BGR) and partly in the field during previous measurement campaigns were hyperspectrally measured and geochemically analysed by using a LIBS handheld analyzer. A description of the HySpex system in lab use can be found in Koerting et al. (2021). The lithium-bearing mineral samples were measured without prior sample preparation as the surface of the minerals and the influence of the mineral structure were of interest (Figure 1). Figure 1 shows one HySpex scan of four lepidolite samples (Lep1, Lep2, Lep3, Lep4) displayed as a true color RGB image in order to show the untreated samples and the white reflectance (WR) panel needed for the hyperspectral measurements (WR 90%).
    Keywords: hyperspectral ; spectral library ; geochemical ; Li-bearing minerals ; LIBS ; Laser-Induced Breakdown Spectroscopy ; Earth Remote Sensing Instruments 〉 Passive Remote Sensing 〉 Spectrometers/Radiometers ; EARTH SCIENCE 〉 SOLID EARTH 〉 ROCKS/MINERALS/CRYSTALS 〉 IGNEOUS ROCKS 〉 IGNEOUS ROCK PHYSICAL/OPTICAL PROPERTIES ; EARTH SCIENCE 〉 SOLID EARTH 〉 ROCKS/MINERALS/CRYSTALS 〉 SEDIMENTARY ROCKS 〉 SEDIMENTARY ROCK PHYSICAL/OPTICAL PROPERTIES
    Type: Dataset , Dataset
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    DATA GFZ
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