Surface roughness characterization of the 2014–2015 Holuhraun lava flow-field in Iceland: implications for facies mapping and remote sensing.
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| Title: | Surface roughness characterization of the 2014–2015 Holuhraun lava flow-field in Iceland: implications for facies mapping and remote sensing. |
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| Authors: | Voigt, Joana R. C.1 (AUTHOR) voigt@lpl.arizona.edu, Hamilton, Christopher W.1 (AUTHOR), Steinbrügge, Gregor2 (AUTHOR), Scheidt, Stephen P.3,4,5 (AUTHOR) |
| Source: | Bulletin of Volcanology. Dec2021, Vol. 83 Issue 12, p1-14. 14p. |
| Subject Terms: | *Surface analysis, *Surface roughness, *Remote sensing, *Facies, *Lava |
| Geographic Terms: | Iceland |
| Abstract: | Surface roughness is a commonly used parameter for the quantitative analysis and characterization of geological terrains on Earth, as well as on other planetary bodies, particularly where detailed optical data may not be available. Here, we statistically investigate if surface roughness can be used to distinguish between different lava facies in remote sensing data by examining the entire 2014–2015 Holuhraun lava flow-field in Iceland. Root-mean-square (RMS) height deviation, Hurst exponents, and breakpoints were calculated to quantify the surface roughness characteristics of eight facies using stereo-derived topographic datasets at three different pixel scales, ranging from 0.05 to 0.5 m/pixel. We show that most of the investigated lava facies (rubbly, spiny, undifferentiated rubbly–spiny, shelly, pāhoehoe, and flat-lying–knobby) are indistinguishable by surface roughness down to the 5 cm baseline, with the exception of topography-building facies like the vent-proximal edifice and the exceptionally blocky channel interior facies. Additionally, we considered baselines corresponding to radar S-band (10 cm), L-band (20 cm), and P-band (90 cm). Our findings imply that when transitional lava types are considered in addition to traditional end-members, topographic roughness data, including RMS height deviation and Hurst exponent values alone, cannot be used to uniquely identify lava facies at these baselines. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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| Header | DbId: enr DbLabel: Energy & Power Source An: 154247753 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Surface roughness characterization of the 2014–2015 Holuhraun lava flow-field in Iceland: implications for facies mapping and remote sensing. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Voigt%2C+Joana+R%2E+C%2E%22">Voigt, Joana R. C.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> voigt@lpl.arizona.edu</i><br /><searchLink fieldCode="AR" term="%22Hamilton%2C+Christopher+W%2E%22">Hamilton, Christopher W.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Steinbrügge%2C+Gregor%22">Steinbrügge, Gregor</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Scheidt%2C+Stephen+P%2E%22">Scheidt, Stephen P.</searchLink><relatesTo>3,4,5</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Bulletin+of+Volcanology%22">Bulletin of Volcanology</searchLink>. Dec2021, Vol. 83 Issue 12, p1-14. 14p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Surface+analysis%22">Surface analysis</searchLink><br />*<searchLink fieldCode="DE" term="%22Surface+roughness%22">Surface roughness</searchLink><br />*<searchLink fieldCode="DE" term="%22Remote+sensing%22">Remote sensing</searchLink><br />*<searchLink fieldCode="DE" term="%22Facies%22">Facies</searchLink><br />*<searchLink fieldCode="DE" term="%22Lava%22">Lava</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Iceland%22">Iceland</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Surface roughness is a commonly used parameter for the quantitative analysis and characterization of geological terrains on Earth, as well as on other planetary bodies, particularly where detailed optical data may not be available. Here, we statistically investigate if surface roughness can be used to distinguish between different lava facies in remote sensing data by examining the entire 2014–2015 Holuhraun lava flow-field in Iceland. Root-mean-square (RMS) height deviation, Hurst exponents, and breakpoints were calculated to quantify the surface roughness characteristics of eight facies using stereo-derived topographic datasets at three different pixel scales, ranging from 0.05 to 0.5 m/pixel. We show that most of the investigated lava facies (rubbly, spiny, undifferentiated rubbly–spiny, shelly, pāhoehoe, and flat-lying–knobby) are indistinguishable by surface roughness down to the 5 cm baseline, with the exception of topography-building facies like the vent-proximal edifice and the exceptionally blocky channel interior facies. Additionally, we considered baselines corresponding to radar S-band (10 cm), L-band (20 cm), and P-band (90 cm). Our findings imply that when transitional lava types are considered in addition to traditional end-members, topographic roughness data, including RMS height deviation and Hurst exponent values alone, cannot be used to uniquely identify lava facies at these baselines. [ABSTRACT FROM AUTHOR] |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=154247753 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s00445-021-01499-4 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 1 Subjects: – SubjectFull: Surface analysis Type: general – SubjectFull: Surface roughness Type: general – SubjectFull: Remote sensing Type: general – SubjectFull: Facies Type: general – SubjectFull: Lava Type: general – SubjectFull: Iceland Type: general Titles: – TitleFull: Surface roughness characterization of the 2014–2015 Holuhraun lava flow-field in Iceland: implications for facies mapping and remote sensing. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Voigt, Joana R. C. – PersonEntity: Name: NameFull: Hamilton, Christopher W. – PersonEntity: Name: NameFull: Steinbrügge, Gregor – PersonEntity: Name: NameFull: Scheidt, Stephen P. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2021 Type: published Y: 2021 Identifiers: – Type: issn-print Value: 02588900 Numbering: – Type: volume Value: 83 – Type: issue Value: 12 Titles: – TitleFull: Bulletin of Volcanology Type: main |
| ResultId | 1 |