10.1594/PANGAEA.904718Kirsch, MoritzMoritzKirsch0000-0003-1512-5511Lorenz, SandraSandraLorenz0000-0001-8464-2331Zimmermann, RobertRobertZimmermannAndreani, LouisLouisAndreani0000-0002-5916-155XTusa, LauraLauraTusaPospiech, SolveigSolveigPospiechJackisch, RobertRobertJackisch0000-0001-5696-8721Khodadadzadeh, MahdiMahdiKhodadadzadehGhamisi, PedramPedramGhamisiUnger, GabrielGabrielUngerHödl, PhilipPhilipHödlGloaguen, RichardRichardGloaguenMiddleton, MaaritMaaritMiddletonSutinen, RaimoRaimoSutinenOjala, Antti E KAntti E KOjalaMattila, JussiJussiMattila0000-0003-1953-2114Nordbäck, NicklasNicklasNordbäck0000-0002-7152-7550Palmu, Jukka-PekkaJukka-PekkaPalmuTiljander, MiaMiaTiljanderRuskeeniemi, TimoTimoRuskeeniemi0000-0002-9084-4199PANGAEA2019geologyhyperspectral imagingpalaeoseismologyPhotogrammetryremote sensingFile contentFile nameFile formatFile sizeUniform resource locator/link to fileMultiple investigationsHelmholtz-Zentrum Dresden-Rossendorfhttps://ror.org/01zy2cs03Supplementary Dataset10.1111/phor.1230070 data pointstext/tab-separated-valuesCreative Commons Attribution 4.0 InternationalThe 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.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), 385-40726.14867.225Finland