Characterizing Volcaniclastic Deposits on Planetary Surfaces Using Remote Sensing Observations

Explosive volcanic products, i.e. tephra, are found on nearly every terrestrial planet in the solar system (e.g., Wilhelms, 1987; Hartmann et al., 1999; Byrne et al., 2018) and contain a heterogeneous mix of minerals, debris, and glass (quenched melt). Remote characterization of the terrestrial planets utilizes spectroscopic methods to constrain surface compositions, which in turn rely on robust laboratory calibration of spectral libraries. The presence of the glass component complicates spectral identification of tephra due to the amorphous nature of glass, which results in poorly-constrained spectral characteristics in both the visible-near-infrared (VNIR) and mid-infrared (MIR) spectral regions (Minitti et al., 2002; Dalby and King 2006; Horgan et al., 2014). Here we generate and characterize a spectral library of 21 natural tephra samples and use it to generate Partial Least Squares (PLS) regression models to predict the glass SiO2 wt%, bulk SiO2 wt%, phase percentage of glass, sample vesicularity, and size fraction of the spectra from the spectra. Samples were ground and sieved into five size fractions, and VNIR and MIR spectra were collected for each. Phase assemblages of samples were obtained via particle counting on a scanning electron microscope (SEM). Resin molds were made for pointcounting and electron microprobe analysis to obtain the glass, bulk, and mineral compositions, and glass beads were made for bulk compositional analysis. We find that PLS models built from either the VNIR or MIR spectra can predict the modal abundance of glass present, as well as the glass and bulk SiO2 weight percent, sample size fraction, and sample vesicularity.