Three-Dimensional, Km-Scale Hyperspectral Data of Well-Exposed Zn–Pb Mineralization at Black Angel Mountain, Greenland
Hyperspectral imaging is an innovative technology for non-invasive mapping, with increasing applications in many sectors. As with any novel technology, robust processing workflows are required to ensure a wide use. We present an open-source hypercloud dataset capturing the complex but spectacularly...
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ftmdpi:oai:mdpi.com:/2306-5729/7/8/104/ 2023-08-20T04:06:52+02:00 Three-Dimensional, Km-Scale Hyperspectral Data of Well-Exposed Zn–Pb Mineralization at Black Angel Mountain, Greenland Sandra Lorenz Sam T. Thiele Moritz Kirsch Gabriel Unger Robert Zimmermann Pierpaolo Guarnieri Nigel Baker Erik Vest Sørensen Diogo Rosa Richard Gloaguen 2022-07-28 application/pdf https://doi.org/10.3390/data7080104 EN eng Multidisciplinary Digital Publishing Institute Spatial Data Science and Digital Earth https://dx.doi.org/10.3390/data7080104 https://creativecommons.org/licenses/by/4.0/ Data; Volume 7; Issue 8; Pages: 104 open-source dataset hyperspectral data spectral imaging 3D hyperclouds photogrammetry mineral mapping Black Angel Maarmorilik minimum wavelength mapping interactive workflow Text 2022 ftmdpi https://doi.org/10.3390/data7080104 2023-08-01T05:52:25Z Hyperspectral imaging is an innovative technology for non-invasive mapping, with increasing applications in many sectors. As with any novel technology, robust processing workflows are required to ensure a wide use. 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. This contribution relies on very recent progress made on the correction, interpretation and integration of hyperspectral data in earth sciences. The possibility to fuse hyperspectral scans with 3D point cloud representations (hyperclouds) has opened up new possibilities for the mapping of complex natural targets. Spectroscopic and machine learning tools allow or the rapid and accurate characterization of geological structures in a 3D environment. Potential users can use this exemplary dataset and the associated tools to train themselves or test new algorithms. As the data and the tools have a wide range of application, we expect this contribution to benefit the scientific community at large. Text Greenland MDPI Open Access Publishing Greenland Maarmorilik ENVELOPE(-51.283,-51.283,71.133,71.133) Data 7 8 104 |
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Open Polar |
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MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
open-source dataset hyperspectral data spectral imaging 3D hyperclouds photogrammetry mineral mapping Black Angel Maarmorilik minimum wavelength mapping interactive workflow |
spellingShingle |
open-source dataset hyperspectral data spectral imaging 3D hyperclouds photogrammetry mineral mapping Black Angel Maarmorilik minimum wavelength mapping interactive workflow Sandra Lorenz Sam T. Thiele Moritz Kirsch Gabriel Unger Robert Zimmermann Pierpaolo Guarnieri Nigel Baker Erik Vest Sørensen Diogo Rosa Richard Gloaguen Three-Dimensional, Km-Scale Hyperspectral Data of Well-Exposed Zn–Pb Mineralization at Black Angel Mountain, Greenland |
topic_facet |
open-source dataset hyperspectral data spectral imaging 3D hyperclouds photogrammetry mineral mapping Black Angel Maarmorilik minimum wavelength mapping interactive workflow |
description |
Hyperspectral imaging is an innovative technology for non-invasive mapping, with increasing applications in many sectors. As with any novel technology, robust processing workflows are required to ensure a wide use. 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. This contribution relies on very recent progress made on the correction, interpretation and integration of hyperspectral data in earth sciences. The possibility to fuse hyperspectral scans with 3D point cloud representations (hyperclouds) has opened up new possibilities for the mapping of complex natural targets. Spectroscopic and machine learning tools allow or the rapid and accurate characterization of geological structures in a 3D environment. Potential users can use this exemplary dataset and the associated tools to train themselves or test new algorithms. As the data and the tools have a wide range of application, we expect this contribution to benefit the scientific community at large. |
format |
Text |
author |
Sandra Lorenz Sam T. Thiele Moritz Kirsch Gabriel Unger Robert Zimmermann Pierpaolo Guarnieri Nigel Baker Erik Vest Sørensen Diogo Rosa Richard Gloaguen |
author_facet |
Sandra Lorenz Sam T. Thiele Moritz Kirsch Gabriel Unger Robert Zimmermann Pierpaolo Guarnieri Nigel Baker Erik Vest Sørensen Diogo Rosa Richard Gloaguen |
author_sort |
Sandra Lorenz |
title |
Three-Dimensional, Km-Scale Hyperspectral Data of Well-Exposed Zn–Pb Mineralization at Black Angel Mountain, Greenland |
title_short |
Three-Dimensional, Km-Scale Hyperspectral Data of Well-Exposed Zn–Pb Mineralization at Black Angel Mountain, Greenland |
title_full |
Three-Dimensional, Km-Scale Hyperspectral Data of Well-Exposed Zn–Pb Mineralization at Black Angel Mountain, Greenland |
title_fullStr |
Three-Dimensional, Km-Scale Hyperspectral Data of Well-Exposed Zn–Pb Mineralization at Black Angel Mountain, Greenland |
title_full_unstemmed |
Three-Dimensional, Km-Scale Hyperspectral Data of Well-Exposed Zn–Pb Mineralization at Black Angel Mountain, Greenland |
title_sort |
three-dimensional, km-scale hyperspectral data of well-exposed zn–pb mineralization at black angel mountain, greenland |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2022 |
url |
https://doi.org/10.3390/data7080104 |
long_lat |
ENVELOPE(-51.283,-51.283,71.133,71.133) |
geographic |
Greenland Maarmorilik |
geographic_facet |
Greenland Maarmorilik |
genre |
Greenland |
genre_facet |
Greenland |
op_source |
Data; Volume 7; Issue 8; Pages: 104 |
op_relation |
Spatial Data Science and Digital Earth https://dx.doi.org/10.3390/data7080104 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/data7080104 |
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Data |
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7 |
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8 |
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104 |
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