Integration of Terrestrial and Drone-Borne Hyperspectral and Photogrammetric Sensing Methods for Exploration Mapping and Mining Monitoring

Mapping lithology and geological structures accurately remains a challenge in difficult terrain or in active mining areas. We demonstrate that the integration of terrestrial and drone-borne multi-sensor remote sensing techniques significantly improves the reliability, safety, and efficiency of geolo...

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Main Authors: Moritz Kirsch, Sandra Lorenz, Robert Zimmermann, Laura Tusa, Robert Möckel, Philip Hödl, René Booysen, Mahdi Khodadadzadeh, Richard Gloaguen
Format: Article
Language:English
Published: MDPI AG 2018-08-01
Series:Remote Sensing
Subjects:
UAV
Online Access:http://www.mdpi.com/2072-4292/10/9/1366
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spelling doaj-2340d875f0d14dc78207aec8ec56805f2020-11-24T21:27:19ZengMDPI AGRemote Sensing2072-42922018-08-01109136610.3390/rs10091366rs10091366Integration of Terrestrial and Drone-Borne Hyperspectral and Photogrammetric Sensing Methods for Exploration Mapping and Mining MonitoringMoritz Kirsch0Sandra Lorenz1Robert Zimmermann2Laura Tusa3Robert Möckel4Philip Hödl5René Booysen6Mahdi Khodadadzadeh7Richard Gloaguen8Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Chemnitzer Straße 40, 09599 Freiberg, GermanyHelmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Chemnitzer Straße 40, 09599 Freiberg, GermanyHelmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Chemnitzer Straße 40, 09599 Freiberg, GermanyHelmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Chemnitzer Straße 40, 09599 Freiberg, GermanyHelmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Chemnitzer Straße 40, 09599 Freiberg, GermanyHelmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Chemnitzer Straße 40, 09599 Freiberg, GermanyHelmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Chemnitzer Straße 40, 09599 Freiberg, GermanyHelmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Chemnitzer Straße 40, 09599 Freiberg, GermanyHelmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Chemnitzer Straße 40, 09599 Freiberg, GermanyMapping lithology and geological structures accurately remains a challenge in difficult terrain or in active mining areas. We demonstrate that the integration of terrestrial and drone-borne multi-sensor remote sensing techniques significantly improves the reliability, safety, and efficiency of geological activities during exploration and mining monitoring. We describe an integrated workflow to produce a geometrically and spectrally accurate combination of a Structure-from-Motion Multi-View Stereo point cloud and hyperspectral data cubes in the visible to near-infrared (VNIR) and short-wave infrared (SWIR), as well as long-wave infrared (LWIR) ranges acquired by terrestrial and drone-borne imaging sensors. Vertical outcrops in a quarry in the Freiberg mining district, Saxony (Germany), featuring sulfide-rich hydrothermal zones in a granitoid host, are used to showcase the versatility of our approach. The image data are processed using spectroscopic and machine learning algorithms to generate meaningful 2.5D (i.e., surface) maps that are available to geologists on the ground just shortly after data acquisition. We validate the remote sensing data with thin section analysis and laboratory X-ray diffraction, as well as point spectroscopic data. The combination of ground- and drone-based photogrammetric and hyperspectral VNIR, SWIR, and LWIR imaging allows for safer and more efficient ground surveys, as well as a better, statistically sound sampling strategy for further structural, geochemical, and petrological investigations.http://www.mdpi.com/2072-4292/10/9/1366hyperspectral imagingStructure-from-Motion (SfM)mineral mappingvirtual outcropsgeologyhydrothermalUAVlong-wave infrared
collection DOAJ
language English
format Article
sources DOAJ
author Moritz Kirsch
Sandra Lorenz
Robert Zimmermann
Laura Tusa
Robert Möckel
Philip Hödl
René Booysen
Mahdi Khodadadzadeh
Richard Gloaguen
spellingShingle Moritz Kirsch
Sandra Lorenz
Robert Zimmermann
Laura Tusa
Robert Möckel
Philip Hödl
René Booysen
Mahdi Khodadadzadeh
Richard Gloaguen
Integration of Terrestrial and Drone-Borne Hyperspectral and Photogrammetric Sensing Methods for Exploration Mapping and Mining Monitoring
Remote Sensing
hyperspectral imaging
Structure-from-Motion (SfM)
mineral mapping
virtual outcrops
geology
hydrothermal
UAV
long-wave infrared
author_facet Moritz Kirsch
Sandra Lorenz
Robert Zimmermann
Laura Tusa
Robert Möckel
Philip Hödl
René Booysen
Mahdi Khodadadzadeh
Richard Gloaguen
author_sort Moritz Kirsch
title Integration of Terrestrial and Drone-Borne Hyperspectral and Photogrammetric Sensing Methods for Exploration Mapping and Mining Monitoring
title_short Integration of Terrestrial and Drone-Borne Hyperspectral and Photogrammetric Sensing Methods for Exploration Mapping and Mining Monitoring
title_full Integration of Terrestrial and Drone-Borne Hyperspectral and Photogrammetric Sensing Methods for Exploration Mapping and Mining Monitoring
title_fullStr Integration of Terrestrial and Drone-Borne Hyperspectral and Photogrammetric Sensing Methods for Exploration Mapping and Mining Monitoring
title_full_unstemmed Integration of Terrestrial and Drone-Borne Hyperspectral and Photogrammetric Sensing Methods for Exploration Mapping and Mining Monitoring
title_sort integration of terrestrial and drone-borne hyperspectral and photogrammetric sensing methods for exploration mapping and mining monitoring
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2018-08-01
description Mapping lithology and geological structures accurately remains a challenge in difficult terrain or in active mining areas. We demonstrate that the integration of terrestrial and drone-borne multi-sensor remote sensing techniques significantly improves the reliability, safety, and efficiency of geological activities during exploration and mining monitoring. We describe an integrated workflow to produce a geometrically and spectrally accurate combination of a Structure-from-Motion Multi-View Stereo point cloud and hyperspectral data cubes in the visible to near-infrared (VNIR) and short-wave infrared (SWIR), as well as long-wave infrared (LWIR) ranges acquired by terrestrial and drone-borne imaging sensors. Vertical outcrops in a quarry in the Freiberg mining district, Saxony (Germany), featuring sulfide-rich hydrothermal zones in a granitoid host, are used to showcase the versatility of our approach. The image data are processed using spectroscopic and machine learning algorithms to generate meaningful 2.5D (i.e., surface) maps that are available to geologists on the ground just shortly after data acquisition. We validate the remote sensing data with thin section analysis and laboratory X-ray diffraction, as well as point spectroscopic data. The combination of ground- and drone-based photogrammetric and hyperspectral VNIR, SWIR, and LWIR imaging allows for safer and more efficient ground surveys, as well as a better, statistically sound sampling strategy for further structural, geochemical, and petrological investigations.
topic hyperspectral imaging
Structure-from-Motion (SfM)
mineral mapping
virtual outcrops
geology
hydrothermal
UAV
long-wave infrared
url http://www.mdpi.com/2072-4292/10/9/1366
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