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Hyperspectral REE (Rare Earth Element) Mapping of Outcrops-Applications for Neodymium Detection
(2015)
In this study, an in situ application for identifying neodymium (Nd) enriched surface materials that uses multitemporal hyperspectral images is presented (HySpex sensor). Because of the narrow shape and shallow absorption depth of the neodymium absorption feature, a method was developed for enhancing and extracting the necessary information for neodymium from image spectra, even under illumination conditions that are not optimal. For this purpose, the two following approaches were developed: (1) reducing noise and analyzing changing illumination conditions by averaging multitemporal image scenes and (2) enhancing the depth of the desired absorption band by deconvolving every image spectrum with a Gaussian curve while the rest of the spectrum remains unchanged (Richardson-Lucy deconvolution). To evaluate these findings, nine field samples from the Fen complex in Norway were analyzed using handheld X-ray fluorescence devices and by conducting detailed laboratory-based geochemical rare earth element determinations. The result is a qualitative outcrop map that highlights zones that are enriched in neodymium. To reduce the influences of non-optimal illumination, particularly at the studied site, a minimum of seven single acquisitions is required. Sharpening the neodymium absorption band allows for robust mapping, even at the outer zones of enrichment. From the geochemical investigations, we found that iron oxides decrease the applicability of the method. However, iron-related absorption bands can be used as secondary indicators for sulfidic ore zones that are mainly enriched with rare earth elements. In summary, we found that hyperspectral spectroscopy is a noninvasive, fast and cost-saving method for determining neodymium at outcrop surfaces.
EnGeoMAP 2.0-Automated Hyperspectral Mineral Identification for the German EnMAP Space Mission
(2016)
Algorithms for a rapid analysis of hyperspectral data are becoming more and more important with planned next generation spaceborne hyperspectral missions such as the Environmental Mapping and Analysis Program (EnMAP) and the Japanese Hyperspectral Imager Suite (HISUI), together with an ever growing pool of hyperspectral airborne data. The here presented EnGeoMAP 2.0 algorithm is an automated system for material characterization from imaging spectroscopy data, which builds on the theoretical framework of the Tetracorder and MICA (Material Identification and Characterization Algorithm) of the United States Geological Survey and of EnGeoMAP 1.0 from 2013. EnGeoMAP 2.0 includes automated absorption feature extraction, spatio-spectral gradient calculation and mineral anomaly detection. The usage of EnGeoMAP 2.0 is demonstrated at the mineral deposit sites of Rodalquilar (SE-Spain) and Haib River (S-Namibia) using HyMAP and simulated EnMAP data. Results from Hyperion data are presented as supplementary information.
EnGeoMAP 2.0
(2017)
Algorithms for a rapid analysis of hyperspectral data are becoming more and more important with planned next generation spaceborne hyperspectral missions such as the Environmental Mapping and Analysis Program (EnMAP) and the Japanese Hyperspectral Imager Suite (HISUI), together with an ever growing pool of hyperspectral airborne data. The here presented EnGeoMAP 2.0 algorithm is an automated system for material characterization from imaging spectroscopy data, which builds on the theoretical framework of the Tetracorder and MICA (Material Identification and Characterization Algorithm) of the United States Geological Survey and of EnGeoMAP 1.0 from 2013. EnGeoMAP 2.0 includes automated absorption feature extraction, spatio-spectral gradient calculation and mineral anomaly detection. The usage of EnGeoMAP 2.0 is demonstrated at the mineral deposit sites of Rodalquilar (SE-Spain) and Haib River (S-Namibia) using HyMAP and simulated EnMAP data. Results from Hyperion data are presented as supplementary information.
In this study, an in situ application for identifying neodymium (Nd) enriched surface materials that uses multitemporal hyperspectral images is presented (HySpex sensor). Because of the narrow shape and shallow absorption depth of the neodymium absorption feature, a method was developed for enhancing and extracting the necessary information for neodymium from image spectra, even under illumination conditions that are not optimal. For this purpose, the two following approaches were developed: (1) reducing noise and analyzing changing illumination conditions by averaging multitemporal image scenes and (2) enhancing the depth of the desired absorption band by deconvolving every image spectrum with a Gaussian curve while the rest of the spectrum remains unchanged (Richardson-Lucy deconvolution). To evaluate these findings, nine field samples from the Fen complex in Norway were analyzed using handheld X-ray fluorescence devices and by conducting detailed laboratory-based geochemical rare earth element determinations. The result is a qualitative outcrop map that highlights zones that are enriched in neodymium. To reduce the influences of non-optimal illumination, particularly at the studied site, a minimum of seven single acquisitions is required. Sharpening the neodymium absorption band allows for robust mapping, even at the outer zones of enrichment. From the geochemical investigations, we found that iron oxides decrease the applicability of the method. However, iron-related absorption bands can be used as secondary indicators for sulfidic ore zones that are mainly enriched with rare earth elements. In summary, we found that hyperspectral spectroscopy is a noninvasive, fast and cost-saving method for determining neodymium at outcrop surfaces
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 coppergold-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.