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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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:
Online Access:https://hdl.handle.net/20.500.11815/1767
https://doi.org/10.3390/geosciences10040125
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author Aufaristama, Muhammad
Höskuldsson, Ármann
Ulfarsson, Magnus
Jónsdóttir, Ingibjörg
Thordarson, Thorvaldur
author2 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
author_facet Aufaristama, Muhammad
Höskuldsson, Ármann
Ulfarsson, Magnus
Jónsdóttir, Ingibjörg
Thordarson, Thorvaldur
author_sort Aufaristama, Muhammad
collection Unknown
container_issue 4
container_start_page 125
container_title Geosciences
container_volume 10
description 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
format Article in Journal/Newspaper
genre Iceland
genre_facet Iceland
geographic Holuhraun
Hraun
geographic_facet Holuhraun
Hraun
id ftopinvisindi:oai:opinvisindi.is:20.500.11815/1767
institution Open Polar
language English
long_lat ENVELOPE(-16.831,-16.831,64.852,64.852)
ENVELOPE(-19.263,-19.263,63.507,63.507)
op_collection_id ftopinvisindi
op_doi https://doi.org/20.500.11815/176710.3390/geosciences10040125
op_relation Geosciences;10(4)
https://www.mdpi.com/2076-3263/10/4/125/pdf
https://hdl.handle.net/20.500.11815/1767
Geosciences
doi:10.3390/geosciences10040125
op_rights info:eu-repo/semantics/openAccess
publishDate 2020
publisher MDPI AG
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spelling ftopinvisindi:oai:opinvisindi.is:20.500.11815/1767 2025-06-15T14:30:59+00:00 Lava Flow Roughness on the 2014–2015 Lava Flow-Field at Holuhraun, Iceland, Derived from Airborne LiDAR and Photogrammetry Aufaristama, Muhammad Höskuldsson, Ármann Ulfarsson, Magnus Jónsdóttir, Ingibjörg Thordarson, Thorvaldur 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 2020-03-31 125 https://hdl.handle.net/20.500.11815/1767 https://doi.org/10.3390/geosciences10040125 en eng MDPI AG Geosciences;10(4) https://www.mdpi.com/2076-3263/10/4/125/pdf https://hdl.handle.net/20.500.11815/1767 Geosciences doi:10.3390/geosciences10040125 info:eu-repo/semantics/openAccess Lava roughness TPI Hurst exponent LiDAR Photogrammetry Hraun Hraunrennsli Loftmyndir Kortagerð info:eu-repo/semantics/article 2020 ftopinvisindi https://doi.org/20.500.11815/176710.3390/geosciences10040125 2025-05-23T03:05:41Z 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 Article in Journal/Newspaper Iceland Unknown Holuhraun ENVELOPE(-16.831,-16.831,64.852,64.852) Hraun ENVELOPE(-19.263,-19.263,63.507,63.507) Geosciences 10 4 125
spellingShingle Lava roughness
TPI
Hurst exponent
LiDAR
Photogrammetry
Hraun
Hraunrennsli
Loftmyndir
Kortagerð
Aufaristama, Muhammad
Höskuldsson, Ármann
Ulfarsson, Magnus
Jónsdóttir, Ingibjörg
Thordarson, Thorvaldur
Lava Flow Roughness on the 2014–2015 Lava Flow-Field at Holuhraun, Iceland, Derived from Airborne LiDAR and Photogrammetry
title Lava Flow Roughness on the 2014–2015 Lava Flow-Field at Holuhraun, Iceland, Derived from Airborne LiDAR and Photogrammetry
title_full Lava Flow Roughness on the 2014–2015 Lava Flow-Field at Holuhraun, Iceland, Derived from Airborne LiDAR and Photogrammetry
title_fullStr Lava Flow Roughness on the 2014–2015 Lava Flow-Field at Holuhraun, Iceland, Derived from Airborne LiDAR and Photogrammetry
title_full_unstemmed Lava Flow Roughness on the 2014–2015 Lava Flow-Field at Holuhraun, Iceland, Derived from Airborne LiDAR and Photogrammetry
title_short Lava Flow Roughness on the 2014–2015 Lava Flow-Field at Holuhraun, Iceland, Derived from Airborne LiDAR and Photogrammetry
title_sort lava flow roughness on the 2014–2015 lava flow-field at holuhraun, iceland, derived from airborne lidar and photogrammetry
topic Lava roughness
TPI
Hurst exponent
LiDAR
Photogrammetry
Hraun
Hraunrennsli
Loftmyndir
Kortagerð
topic_facet Lava roughness
TPI
Hurst exponent
LiDAR
Photogrammetry
Hraun
Hraunrennsli
Loftmyndir
Kortagerð
url https://hdl.handle.net/20.500.11815/1767
https://doi.org/10.3390/geosciences10040125