Quantifying misidentification rates of Europa's microfeatures in low-resolution Galileo imaging

Abstract

Europa is a compelling target because of its unique geology and potential for habitability. Efforts to map the small-scale global geology of the moon have been hampered by the availability of suitable imaging (≤ 230 m/pix), which covers only 15% of the surface. New data on the abundance of microfeatures (features ≤100 km2 in area) on a global scale and their locations would help put better constraints on the geophysics of the icy world. We mapped microfeatures in low-resolution images of the E15RegMap01 region of Europa and compared our low-resolution dataset to a validated dataset collected using regional mosaic imaging. We evaluated how many features were missed in low-resolution mapping, the feature types to which they belonged, how often misclassifications were made, and how many false-positive features there were in the low-resolution dataset. We found that microchaos, hybrids, and spots were found at relatively high completeness rates when compared to the regional mosaic dataset, but domes and especially pits were almost always missed. Microchaos, hybrids, and spots also had the highest rates of consistent classification between the low-resolution and regional mosaic datasets. Finally, 36% of our total potential feature count from the low-resolution dataset were revealed to be false positives, mostly caused by ridges and shadows that were mistaken for features in low-resolution imaging. These findings quantitatively estimate the likely errors in existing and future global geologic maps that note the presence of microfeatures, offer remedies to minimize these errors, and provide guidance for future Europa mappers.