![]() ![]() For Maarmorilik, 712 photos were used to build a dense cloud with a ground resolution of 26.3 cm/pixel and a mean reprojection error of 0.2 pixels. Agisoft Metashape Professional version 1.6.3 was used to generate a photogrammetric reconstruction following the protocols outlined by. The photos were geotagged using an external GPS (error ± 5–10 m). In total, 859 RGB images were collected from the Maarmorilik and Nunngarut area from a helicopter using a pre-calibrated 36.3-megapixel Nikon D800E digital-SLR camera equipped with a 35 mm 1.4 L Zeiss lens (focus fixed to infinity). ![]() Ī photogrammetric survey of the field area was conducted in 2015 by the Geological Survey of Denmark and Greenland (GEUS) for the KarratZinc project to generate high-resolution digital outcrop models. Accessory minerals are pyrrhotite, chalcopyrite, tennantite and arsenopyrite. The ore is mainly composed of pyrite, sphalerite and galena, with abundant rotated marble fragments and quartz inclusions. These lenses appear to be structurally controlled, although the complex deformation and metamorphism of the ore body and surrounding host rock, and the associated ore remobilization, make it difficult to distinguish primary and secondary controls at ore location. Mineralization occurs as strata-bound lenses up to 30 m thick within metamorphosed carbonates (marbles) of the Paleoproterozoic Mârmorilik Formation, and is thought to represent deformed MVT-type mineralization. The Black Angel mine produced 11.2 million tons of Zn–Pb concentrate (12.3% Zn, 4.0% Pb and 29 ppm Ag) between 19. Smaller satellite ore bodies are also located at Nunngarut, on the southern side of the Affarlikassaa Fjord. The Black Angel is the largest carbonate-hosted Zn–Pb deposit in Greenland, located on the north side of the Affarlikassaa Fjord at Maarmorilik (71° N, 51° W Figure 2), West Greenland. There, we demonstrate the dataset’s value in increasing the understanding of the deformation style in the Mârmorilik marbles and the subdivision between evaporite–carbonate platform facies and carbonate slope facies. In an accompanying paper, we extend on the actual geological interpretation and validation of the dataset. With this dataset we aim to (1) showcase good practices in oblique hyperspectral data processing, (2) demonstrate the added value of fully corrected 3D hyperspectral data to mineral exploration, (3) motivate further workflow development, and (4) provide a relevant geological test case for spectral analysis and machine learning, e.g., the development of deep spectral unmixing methods that could help to make more specific predictions of mineral abundances. In this contribution, we build on this to publish a three-dimensional, km-scale hyperspectral dataset of a well-exposed mineral deposit-the Black Angel at Maarmorilik (West Greenland, Figure 1)-along with interactive tools that fully document an open-source workflow for data projection, correction, analysis and visualization. As the data and the tools have a wide range of application, we expect this contribution to benefit the scientific community at large. Potential users can use this exemplary dataset and the associated tools to train themselves or test new algorithms. Spectroscopic and machine learning tools allow or the rapid and accurate characterization of geological structures in a 3D environment. The possibility to fuse hyperspectral scans with 3D point cloud representations (hyperclouds) has opened up new possibilities for the mapping of complex natural targets. This contribution relies on very recent progress made on the correction, interpretation and integration of hyperspectral data in earth sciences. We present an open-source hypercloud dataset capturing the complex but spectacularly well exposed geology from the Black Angel Mountain in Maarmorilik, West Greenland, alongside a detailed and interactive tutorial documenting relevant processing workflows. As with any novel technology, robust processing workflows are required to ensure a wide use. ![]() Hyperspectral imaging is an innovative technology for non-invasive mapping, with increasing applications in many sectors. ![]()
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