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Hyperspectral outcrop models for palaeoseismic studies
Kirsch, M.ORC; Lorenz, S.; Zimmermann, R.ORC; Andreani, L.ORC; Tusa, L.; Pospiech, S.; Jackisch, R.ORC; Unger, G.; Khodadadzadeh, M.; Ghamisi, P.; Middleton, M.; Ojala, A.; Mattila, J.; Nordbäck, N.; Palmu, J.-P.; Ruskeeniemi, T.; Sutinen, R.; Tiljander, M.; Heikkilä, P.; Gloaguen, R.ORC
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.
Keywords: palaeoseismology, SfM photogrammetry, hyperspectral imaging, geology, remote sensing, outcrop models

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Permalink: https://www.hzdr.de/publications/Publ-29768
Publ.-Id: 29768