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    Differentiating Fissure-Fed Lava Flow Types and Facies Using RADAR and LiDAR: An Example From the 2014–2015 Holuhraun Lava Flow-Field

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    JGR_Solid_Earth_2022_Tolometti ...
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    Author
    Tolometti, G.D.
    Neish, C.D.
    Hamilton, C.W.
    Osinski, G.R.
    Kukko, A.
    Voigt, J.R.C.
    Issue Date
    2022
    Keywords
    Holuhraun lava flow-field
    lava facies
    lava types
    LiDAR
    radar
    surface roughness
    
    Metadata
    Show full item record
    Publisher
    John Wiley and Sons Inc
    Citation
    Tolometti, G. D., Neish, C. D., Hamilton, C. W., Osinski, G. R., Kukko, A., & Voigt, J. R. C. (2022). Differentiating Fissure-Fed Lava Flow Types and Facies Using RADAR and LiDAR: An Example From the 2014–2015 Holuhraun Lava Flow-Field. Journal of Geophysical Research: Solid Earth, 127(7).
    Journal
    Journal of Geophysical Research: Solid Earth
    Rights
    Copyright © 2022 American Geophysical Union. All Rights Reserved.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    Distinguishing between lava types and facies using remote sensing data is important for interpreting the emplacement history of lava flow-fields on Earth and other planetary bodies. Lava facies typically include a mixture of lava types and record the collective emplacement history of material preserved at a particular location. We seek to determine if lava facies in the 2014–2015 Holuhraun lava flow-field are discernible using radar roughness analysis. Furthermore, we also seek to distinguish between lava types using high resolution Light Detection and Ranging (LiDAR) data. We extracted circular polarization ratios (CPR) from the Uninhabited Aerial Vehicle Synthetic Aperture Radar and cross-polarization (VH/VV) data from the Sentinel-1 satellite to analyze the surface roughness of three previously mapped lava facies: rubbly, spiny, and undifferentiated rubbly–spiny. Using the Kruskal-Wallis test, we reveal that all but one pair of the facies are statistically separable. However, the populations overlap by 88%–89% for CPR and 64%–67% for VH/VV. Therefore, owing to large sample populations (n > 2 × 105), slight differences in radar data may be used to probabilistically infer the presence of a particular facies, but not directly map them. We also calculated the root-mean-square slope and Hurst exponents of five different lava types using LiDAR topography (5 cm/pixel). Our results show minute differences between most of the lava types, with the exception of the rubbly pāhoehoe, which is discernible at 1σ. In brief, the presence of “transitional” lava types (e.g., rubbly pāhoehoe) within fissure-fed lava flow-fields complicates remote sensing-based mapping. © 2022. American Geophysical Union. All Rights Reserved.
    Note
    6 month embargo; first published: 20 June 2022
    ISSN
    2169-9313
    DOI
    10.1029/2021JB023419
    Version
    Final published version
    ae974a485f413a2113503eed53cd6c53
    10.1029/2021JB023419
    Scopus Count
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    UA Faculty Publications

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