How cutting-edge technology can help uncover hidden meteorites in Antarctica
When it comes to chasing meteorites, Antarctica is the place to be. At the most basic level, an entire continent, much of it covered in blue-white ice, provides visual contrast that makes it a bit easier to spot dark space rocks, and certain ice processes tend to collect meteorites in rich veins. called meteorite stranding zones.
Still, it’s a whole freaking continent. Even though scientists use aerial photography and similar techniques, many meteorite hunting missions go empty-handed or yield disappointing results. They rely on luck.
What scientists could really use is a really good map of where meteorites are most likely to be, and thanks to new research published Friday in the journal Scientists progress, they might have one soon. The researchers trained a machine-learning algorithm on images of meteor-rich and meteor-poor patches from Antarctica and found that it could identify meteorite stranding areas with more than 80% accuracy.
Although it has not yet been tested in the field, the researchers hope their algorithm-generated map will help scientists find more Antarctic meteorites more efficiently. Meteorites offer planetary scientists a way to study the early solar system without having to travel off-planet. All they have to do is take a treasure map to Antarctica.
What’s up?- After training their machine learning algorithm, the researchers found that it could identify nearly 83% of known meteorite stranding areas in Antarctica. It also predicted the existence of previously unknown meteorite-rich areas, some of which are near existing Antarctic research stations so researchers can track the algorithm’s predictions.
In addition, the first author of the study and doctoral student at the Free University of Brussels in Brussels Veronica Tollenaar tells Reverse, “Our analyzes suggest that there are still many meteorites on the ice sheet that we could collect”, with only about 15% of the existing meteorites having been found.
How they did— The genesis of the new study lies in the meteorite hunting mission undertaken years ago by Tollenaar co-author Harry Zekollari, now a professor of glaciology at ETH Zurich but then a postdoctoral researcher at the Delft University of Technology in the Netherlands. On his return to Delft, he meets Tollenaar, then a graduate student. Zekollar began to wonder why the meteorites were concentrated in the area he had visited; Tollenaar suggested using machine learning techniques to answer this question.
“We are the first researchers to have taken a data-driven approach in this quest and achieved a continent-wide result,” says Tollenaar.
Tollenaar and his colleagues trained their algorithm on thousands of “cells,” 450-meter resolution observations of known Antarctic meteorite stranding areas and millions of areas with unknown meteorite content. The model took into account factors such as surface temperature, surface slope and radar readings to determine the type of ice – all factors associated with processes thought to concentrate meteorites in certain parts of the Antarctic ice and not in other.
The resulting model isn’t perfect, Tollenaar says, but “still, it’s a great help in prioritizing meteor missions.”
What is important in discovery?— There are three reasons to hunt meteorites in Antarctica.
First, they are easy to spot due to their color contrast with the underlying ice, and second, “there is a clustering mechanism related to ice flow, which gathers meteorites into relatively limited areas” , explains Tollenaar. These meteor stranding areas are usually found in blue ice regions, and “scientists searched for meteorites after the concentration mechanism was discovered after the chance discovery of meteorites on a blue ice area in 1969 by a Japanese team “.
But third, cold conditions preserve meteorites, which is important because scientists aren’t hunting them just for fun. “They contain crucial information about the origin and evolution of our solar system,” Tollenaar says.
In 1996, scientists studying the Allan Hills 84001 meteorite (ALH 84001) announced that they may have found evidence of extraterrestrial life, with the meteorite determined to have come from Mars. Although the discovery was ultimately determined to be a false alarm for signs of Martian life, it’s not impossible in principle – a meteorite harboring signs of life on another planet could still be buried under Antarctic ice.
And after?- Tollenaar and his colleagues have shared their code and data with other scientists, and the research community will begin to use and improve their work. She hopes to use more high-resolution data and drones in the field to increase the accuracy of the model.
But of course, the real test and promise of the job is putting boots on the ice and collecting new meteorites where the algorithm predicts they are waiting.
“This year’s Belgian meteorite mission had to be canceled due to covid, but we are starting to make the first preparations for a possible mission next year,” Tollenaar said. “If that happens, we’ll bring the treasure map!”
Summary – Meteorites offer a unique insight into the origin and evolution of the solar system. Antarctica is the most productive region for recovering meteorites, where these extraterrestrial rocks are concentrated in meteorite stranding areas. To date, areas of blue ice bearing meteorites are mostly identified by chance and through expensive reconnaissance missions. Here, we identify areas rich in meteorites by combining state-of-the-art datasets in a machine learning algorithm and provide continent-wide estimates of the likelihood of finding meteorites at a given location. The resulting set of ca. 600 meteorite stranding areas, with an estimated accuracy of over 80%, reveal the existence of unexplored areas, some of which are located near research stations. Our analyzes suggest that less than 15% of all meteorites on 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.