PANGAEA_904718
Hyperspectral imagery-enhanced virtual outcrop models of two palaeoseismic trenches in northern Finnish Lapland
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 E K; Mattila, Jussi; Nordbäck, Nicklas; Palmu, Jukka-Pekka; Tiljander, Mia; Ruskeeniemi, Timo
Hyperspectral imagery-enhanced virtual outcrop models of two palaeoseismic trenches in northern Finnish Lapland
2019-08-09
PANGAEA
Dataset
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 E K; 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
https://doi.pangaea.de/10.1594/PANGAEA.904718
Investigator
Moritz
Kirsch
m.kirsch@hzdr.de
Earth Science
File content
File name
File format
File size
Uniform resource locator/link to file
geoscientificInformation
FinnishLapland
geology
hyperspectral imaging
Multiple investigations
palaeoseismology
Photogrammetry
remote sensing
Complete
67.225
67.225
26.148
26.148
unrestricted
CC-BY-4.0: Creative Commons Attribution 4.0 International
English
Helmholtz-Zentrum Dresden-Rossendorf
PANGAEA
Data Publisher for Earth & Environmental Science
https://www.pangaea.de/
Data Center Contact
Michael
Diepenbroek
info@pangaea.de
Leobener Str.
Bremen
Bremen
28359
Germany
online
70 data points
text/tab-separated-values
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. ** For all details see the full metadata description at "https://doi.pangaea.de/10.1594/PANGAEA.904718"!
https://doi.org/10.1111/phor.12300
Hyperspectral outcrop models for palaeoseismic studies
DIF
9.4
2019-08-09
2026-04-30