Unexplored Antarctic meteorite collection sites revealed through machine learning

Tollenaar Veronica, H. Zekollari, S.L.M. Lhermitte, D.M.J. Tax, Vinciane Debaille, Steven Goderis, Philippe Claeys, Frank Pattyn

Research output: Contribution to journalArticleScientificpeer-review

17 Citations (Scopus)
79 Downloads (Pure)

Abstract

Meteorites provide a unique view into the origin and evolution of the Solar System. Antarctica is the most productive region for recovering meteorites, where these extraterrestrial rocks concentrate at meteorite stranding zones. To date, meteorite-bearing blue ice areas are mostly identified by serendipity and through costly reconnaissance missions. Here, we identify meteorite-rich areas by combining state-of-the-art datasets in a machine learning algorithm and provide continent-wide estimates of the probability to find meteorites at any given location. The resulting set of ca. 600 meteorite stranding zones, with an estimated accuracy of over 80%, reveals the existence of unexplored zones, some of which are located close to research stations. Our analyses suggest that less than 15% of all meteorites at the surface of the Antarctic ice sheet have been recovered to date. The data-driven approach will greatly facilitate the quest to collect the remaining meteorites in a coordinated and cost-effective manner.
Original languageEnglish
Article numbereabj8138
Number of pages14
JournalScience Advances
Volume8
Issue number4
DOIs
Publication statusPublished - 2022

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