Lava Flow Roughness on the 2014–2015 Lava Flow-Field at Holuhraun, Iceland, Derived from Airborne LiDAR and Photogrammetry

Publisher's version (útgefin grein) Roughness can be used to characterize the morphologies of a lava flow. It can be used to identify lava flow features, provide insight into eruption conditions, and link roughness pattern across a lava flow to emplacement conditions. In this study, we use both...

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Bibliographic Details
Published in:Geosciences
Main Authors: Aufaristama, Muhammad, Höskuldsson, Ármann, Ulfarsson, Magnus, Jónsdóttir, Ingibjörg, Thordarson, Thorvaldur
Other Authors: Jarðvísindastofnun (HÍ), Institute of Earth Sciences (UI), Jarðvísindadeild (HÍ), Faculty of Earth Sciences (UI), Rafmagns- og tölvuverkfræðideild (HÍ), Faculty of Electrical and Computer Engineering (UI), Verkfræði- og náttúruvísindasvið (HÍ), School of Engineering and Natural Sciences (UI), Háskóli Íslands, University of Iceland
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2020
Subjects:
Lava roughness
TPI
Hurst exponent
LiDAR
Photogrammetry
Hraun
Hraunrennsli
Loftmyndir
Kortagerð
Holuhraun
Iceland
Online Access:https://hdl.handle.net/20.500.11815/1767
https://doi.org/10.3390/geosciences10040125
Description
Summary:Publisher's version (útgefin grein) Roughness can be used to characterize the morphologies of a lava flow. It can be used to identify lava flow features, provide insight into eruption conditions, and link roughness pattern across a lava flow to emplacement conditions. In this study, we use both the topographic position index (TPI) and the one-dimensional Hurst exponent (H) to derive lava flow unit roughness on the 2014–2015 lava field at Holuhraun using both airborne LiDAR and photogrammetric datasets. The roughness assessment was acquired from four lava flow features: (1) spiny lava, (2) lava pond, (3) blocky surface, and (4) inflated channel. The TPI patterns on spiny lava and inflated channels show that the intermediate TPI values correspond to a small surficial slope indicating a flat and smooth surface. Lava pond is characterized by low to high TPI values and forms a wave-like pattern. Meanwhile, irregular transitions patterns from low to high TPI values indicate a rough surface that is found in blocky surface and flow margins. The surface roughness of these lava features falls within the H range of 0.30 ± 0.05 to 0.76 ± 0.04. The roughest surface is the blocky, and inflated lava flows appear to be the smoothest surface among these four lava units. In general, the Hurst exponent values in the 2014–2015 lava field at Holuhraun has a strong tendency in 0.5, both TPI and Hurst exponent successfully derive quantitative flow roughness The first author was supported by the Indonesia Endowment Fund for Education (LPDP) Grant No. 20160222025516, European Network of Observatories and Research Infrastructures for Volcanology (EUROVOLC), and Vinir Vatnajökuls during his Ph.D. project. LiDAR airborne datasets provided by The European Facility for Airborne Research (EUFAR) and airborne photogrammetry provided by Loftmyndir ehf. Peer Reviewed

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