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

dc.contributorHáskóli Íslandsen_US
dc.contributorUniversity of Icelanden_US
dc.contributor.authorAufaristama, Muhammad
dc.contributor.authorHöskuldsson, Ármann
dc.contributor.authorUlfarsson, Magnus
dc.contributor.authorJónsdóttir, Ingibjörg
dc.contributor.authorThordarson, Thorvaldur
dc.contributor.departmentJarðvísindastofnun (HÍ)en_US
dc.contributor.departmentInstitute of Earth Sciences (UI)en_US
dc.contributor.departmentJarðvísindadeild (HÍ)en_US
dc.contributor.departmentFaculty of Earth Sciences (UI)en_US
dc.contributor.departmentRafmagns- og tölvuverkfræðideild (HÍ)en_US
dc.contributor.departmentFaculty of Electrical and Computer Engineering (UI)en_US
dc.contributor.schoolVerkfræði- og náttúruvísindasvið (HÍ)en_US
dc.contributor.schoolSchool of Engineering and Natural Sciences (UI)en_US
dc.date.accessioned2020-05-04T11:37:10Z
dc.date.available2020-05-04T11:37:10Z
dc.date.issued2020-03-31
dc.descriptionPublisher's version (útgefin grein)en_US
dc.description.abstractRoughness 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 roughnessen_US
dc.description.sponsorshipThe 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.en_US
dc.description.versionPeer Revieweden_US
dc.format.extent125en_US
dc.identifier.citationAufaristama, M.; Höskuldsson, Á.; Ulfarsson, M.O.; Jónsdóttir, I.; Thordarson, T. Lava Flow Roughness on the 2014–2015 Lava Flow-Field at Holuhraun, Iceland, Derived from Airborne LiDAR and Photogrammetry. Geosciences 2020, 10, 125. doi:10.3390/geosciences10040125en_US
dc.identifier.doi10.3390/geosciences10040125
dc.identifier.issn2076-3263
dc.identifier.journalGeosciencesen_US
dc.identifier.urihttps://hdl.handle.net/20.500.11815/1767
dc.language.isoenen_US
dc.publisherMDPI AGen_US
dc.relation.ispartofseriesGeosciences;10(4)
dc.relation.urlhttps://www.mdpi.com/2076-3263/10/4/125/pdfen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectLava roughnessen_US
dc.subjectTPIen_US
dc.subjectHurst exponenten_US
dc.subjectLiDARen_US
dc.subjectPhotogrammetryen_US
dc.subjectHraunen_US
dc.subjectHraunrennslien_US
dc.subjectLoftmyndiren_US
dc.subjectKortagerðen_US
dc.titleLava Flow Roughness on the 2014–2015 Lava Flow-Field at Holuhraun, Iceland, Derived from Airborne LiDAR and Photogrammetryen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dcterms.licenseThis is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly citeden_US

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