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  • 1
    Publication Date: 2018-08-28
    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.
    Electronic ISSN: 2072-4292
    Topics: Architecture, Civil Engineering, Surveying , Geography
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  • 2
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    PANGAEA
    In:  Helmholtz-Zentrum Dresden-Rossendorf | Supplement to: Kirsch, Moritz; Lorenz, Sandra; Zimmermann, Robert; Andreani, Louis; Tusa, Laura; Pospiech, Solveig; Jackisch, Robert; Khodadadzadeh, Mahdi; Ghamisi, Pedram; Unger, Gabriel; Hödl, Philip; Gloaguen, Richard; Middleton, Maarit; Sutinen, Raimo; Ojala, Antti; Mattila, Jussi; Nordbäck, Nicklas; Palmu, Jukka-Pekka; Tiljander, Mia; Ruskeeniemi, Timo (2019): Hyperspectral outcrop models for palaeoseismic studies. Photogrammetric Record, 34(168), 385-407, https://doi.org/10.1111/phor.12300
    Publication Date: 2023-12-23
    Description: The traditional study of palaeoseismic trenches involving logging, stratigraphic and structural interpretation can be time-consuming and affected by biases and inaccuracies. To overcome these limitations, we present a new workflow that integrates infrared hyperspectral and photogrammetric data to support field-based palaeoseismic observations. As a case study, this method is applied on two palaeoseismic trenches excavated across a post-glacial fault scarp in northern Finnish Lapland. The hyperspectral imagery (HSI) is geometrically and radiometrically corrected, processed using established image processing algorithms and machine learning approaches, and co-registered to a Structure-from-Motion point cloud. HSI-enhanced virtual outcrop models are a useful complement to palaeoseismic field studies as they not only provide an intuitive visualisation of the outcrop and a versatile data archive, but also enable an unbiased assessment of the mineralogical composition of lithologic units and a semi-automatic delineation of contacts and deformational structures in a 3D virtual environment. Uploaded data: 14 individual 3D point clouds (ascii format) from two palaeoseismic trenches, including two structure-from-motion photogrammetric RGB point clouds and 12 hyperspectral-enhanced point clouds. Data headers contain point coordinates in m (ETRS89/UTM35N), RGB color (0–255), and point normals (only for SfM RGB point clouds) in the following order: X, Y, Z, Red, Green, Blue, Nx, Ny, Nz.
    Keywords: File content; File format; File name; File size; Finland; FinnishLapland; geology; hyperspectral imaging; MULT; Multiple investigations; palaeoseismology; Photogrammetry; remote sensing; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 70 data points
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  • 3
    Publication Date: 2021-11-10
    Description: The traditional study of palaeoseismic trenches, involving logging, stratigraphic and structural interpretation, can be time consuming and affected by biases and inaccuracies. To overcome these limitations, a new workflow is presented that integrates infrared hyperspectral and photogrammetric data to support field-based palaeoseismic observations. As a case study, this method is applied on two palaeoseismic trenches excavated across a post-glacial fault scarp in northern Finnish Lapland. The hyperspectral imagery (HSI) is geometrically and radiometrically corrected, processed using established image processing algorithms and machine learning approaches, and co-registered to a structure-from-motion point cloud. HSI-enhanced virtual outcrop models are a useful complement to palaeoseismic field studies as they not only provide an intuitive visualisation of the outcrop and a versatile data archive, but also enable an unbiased assessment of the mineralogical composition of lithologic units and a semi-automatic delineation of contacts and deformational structures in a 3D virtual environment. Résumé L'étude traditionnelle des tranchées paléosismiques, impliquant l'enregistrement des coupes et l'interprétation stratigraphique et structurelle, peut prendre beaucoup de temps et être entachée de biais et d'inexactitudes. Pour surmonter ces limites, une nouvelle méthodologie est présentée, intégrant des données photogrammétriques et hyperspectrales infrarouges en appui aux observations paléosismiques de terrain. Comme étude de cas, cette méthode est appliquée à deux tranchées paléosismiques creusées à travers un escarpement de faille post-glaciaire dans le nord de la Laponie finlandaise. L'imagerie hyperspectrale (HSI) est corrigée géométriquement et radiométriquement, traitée à l'aide d'algorithmes classiques de traitement d'images et d'apprentissage machine, et recalée sur un nuage de points photogrammétrique. Les modèles virtuels d'affleurements améliorés par HSI constituent un complément utile aux études paléosismiques de terrain, car ils fournissent non seulement une visualisation intuitive de l'affleurement et une archive de données facile d'emploi, mais permettent également une évaluation non biaisée de la composition minéralogique d'unités lithologiques ainsi qu'une délimitation semi-automatique des contacts et des structures de déformation dans un environnement virtuel 3D.
    Keywords: 551.22 ; geology ; hyperspectral imaging ; outcrop models ; palaeoseismology ; remote sensing ; SfM photogrammetry
    Language: English
    Type: map
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