Lava Flow Roughness on the 2014–2015 Lava Flow-Field at Holuhraun, Iceland, Derived from Airborne LiDAR and Photogrammetry
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...
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ftdoajarticles:oai:doaj.org/article:bcee7997e2a24faaa904313490fae391 2023-05-15T16:51:09+02:00 Lava Flow Roughness on the 2014–2015 Lava Flow-Field at Holuhraun, Iceland, Derived from Airborne LiDAR and Photogrammetry Muhammad Aufaristama Ármann Höskuldsson Magnus Orn Ulfarsson Ingibjörg Jónsdóttir Thorvaldur Thordarson 2020-03-01T00:00:00Z https://doi.org/10.3390/geosciences10040125 https://doaj.org/article/bcee7997e2a24faaa904313490fae391 EN eng MDPI AG https://www.mdpi.com/2076-3263/10/4/125 https://doaj.org/toc/2076-3263 doi:10.3390/geosciences10040125 2076-3263 https://doaj.org/article/bcee7997e2a24faaa904313490fae391 Geosciences, Vol 10, Iss 125, p 125 (2020) lava roughness TPI Hurst exponent LiDAR photogrammetry Geology QE1-996.5 article 2020 ftdoajarticles https://doi.org/10.3390/geosciences10040125 2022-12-30T23:59:24Z 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. Article in Journal/Newspaper Iceland Directory of Open Access Journals: DOAJ Articles Holuhraun ENVELOPE(-16.831,-16.831,64.852,64.852) Geosciences 10 4 125 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
lava roughness TPI Hurst exponent LiDAR photogrammetry Geology QE1-996.5 |
spellingShingle |
lava roughness TPI Hurst exponent LiDAR photogrammetry Geology QE1-996.5 Muhammad Aufaristama Ármann Höskuldsson Magnus Orn Ulfarsson Ingibjörg Jónsdóttir Thorvaldur Thordarson Lava Flow Roughness on the 2014–2015 Lava Flow-Field at Holuhraun, Iceland, Derived from Airborne LiDAR and Photogrammetry |
topic_facet |
lava roughness TPI Hurst exponent LiDAR photogrammetry Geology QE1-996.5 |
description |
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. |
format |
Article in Journal/Newspaper |
author |
Muhammad Aufaristama Ármann Höskuldsson Magnus Orn Ulfarsson Ingibjörg Jónsdóttir Thorvaldur Thordarson |
author_facet |
Muhammad Aufaristama Ármann Höskuldsson Magnus Orn Ulfarsson Ingibjörg Jónsdóttir Thorvaldur Thordarson |
author_sort |
Muhammad Aufaristama |
title |
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_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_sort |
lava flow roughness on the 2014–2015 lava flow-field at holuhraun, iceland, derived from airborne lidar and photogrammetry |
publisher |
MDPI AG |
publishDate |
2020 |
url |
https://doi.org/10.3390/geosciences10040125 https://doaj.org/article/bcee7997e2a24faaa904313490fae391 |
long_lat |
ENVELOPE(-16.831,-16.831,64.852,64.852) |
geographic |
Holuhraun |
geographic_facet |
Holuhraun |
genre |
Iceland |
genre_facet |
Iceland |
op_source |
Geosciences, Vol 10, Iss 125, p 125 (2020) |
op_relation |
https://www.mdpi.com/2076-3263/10/4/125 https://doaj.org/toc/2076-3263 doi:10.3390/geosciences10040125 2076-3263 https://doaj.org/article/bcee7997e2a24faaa904313490fae391 |
op_doi |
https://doi.org/10.3390/geosciences10040125 |
container_title |
Geosciences |
container_volume |
10 |
container_issue |
4 |
container_start_page |
125 |
_version_ |
1766041258841604096 |