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  • 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  (1)
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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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