Differentiating Fissure‐Fed Lava Flow Types and Facies Using RADAR and LiDAR: An Example From the 2014–2015 Holuhraun Lava Flow‐Field. Issue 7 (5th July 2022)

• Record Type: Journal Article
• Authors: Tolometti, G. D.; Neish, C. D.; Hamilton, C. W.; Osinski, G. R.; Kukko, A.; Voigt, J. R. C.
• Is Part Of: Journal of geophysical research. Volume 127:Issue 7(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-07-05
• Subjects: Holuhraun lava flow‐field -- radar -- LiDAR -- surface roughness -- lava facies -- lava types; Geomagnetism -- Periodicals; Geochemistry -- Periodicals; Geophysics -- Periodicals; Earth sciences -- Periodicals; 551.1
• DOI: 10.1029/2021JB023419
• Languages: English
• ISSNs: 2169-9313

Abstract

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 × 10 5 ), 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. Plain Language Summary: The characteristics of geologically recent lava flow‐fields inform our understanding magmatic and volcanic processes on Earth and other terrestrial planetary bodies. Fissure‐fed lava flow‐fields, like the 2014–2015 Holuhraun lava flow‐field in Iceland, include "transitional" surface textures formed from the disruption of solidified crusts. The resulting lava types form in multiple stages, which modify and mix the surfaces, making them challenging to map. At reasonable scales (e.g., 1:800, where 1 mm on the map equates to 80 cm on the ground), mappable units, or "facies, " include a mixture of lava types. On Earth, field observations may be used to identify lava types within such facies, but in remote, inaccessible locations on Earth, and on the surface of other planetary bodies, we can only study lava flow‐fields using data collected from orbiting spacecraft. We seek to determine if lava facies and their constituent lava types in a setting with generally rough surfaces can be differentiated using radar and Light Detection and Ranging (LiDAR) data. We find we are not able to separate the major lava facies using radar data, and few lava types can be discerned using decimeter‐scale LiDAR topography data. The surface characteristics of the lava flow‐field are therefore complex, and it is important to recognize the limitations of automated mapping techniques for mapping the distribution of materials within similar fissure‐fed lava flow fields on Earth and other planets using solely radar and LiDAR data. Key Points: Two polarimetric radar datasets were used to determine if Holuhraun lava facies could be differentiated Our results reveals we cannot uniquely categorize or map the 2014–2015 Holuhraun lava flow‐field lava facies using polarimetric radar data LiDAR topography data reveals that lava types in lava facies are more challenging to differentiate at the cm‐scale compared to dm‐scale