Due to its micron-scale resolution and micro-destructiveness, laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is especially suited for the analysis of the oldest and highly thinned sections of polar ice cores. State-of-the-art 2D elemental imaging by LA-ICP-MS has great potential for investigating the location of impurities on the ice sample surface and is crucial to avoid misinterpretation of ultra-fine resolution signals. The impurity imaging with LA-ICP-MS comprises several millions of laser shots fired over just a few square mm. This technique combines new chemical images with visual analysis and, in so doing raises new questions that may be answered through techniques in automated image analysis and computer vision. As an illustration of this new frontier, a selected set of key problems is presented, with first examples of how automated image analysis techniques can help solving them. This concerns the relationship between impurity localization and the grain boundary network as well as the paleoclimate significance of single line profiles along the main core axis. Ultimately, this demonstrates that it is the right time to spark an intensified exchange among the two scientific communities of computer vision and ice core science.

Two-dimensional impurity imaging in polar ice cores sparks new demand for automated image analysis

Bohleber, Pascal
;
Roman, Marco;Vascon, Sebastiano;Pelillo, Marcello;Barbante, Carlo
2021

Abstract

Due to its micron-scale resolution and micro-destructiveness, laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is especially suited for the analysis of the oldest and highly thinned sections of polar ice cores. State-of-the-art 2D elemental imaging by LA-ICP-MS has great potential for investigating the location of impurities on the ice sample surface and is crucial to avoid misinterpretation of ultra-fine resolution signals. The impurity imaging with LA-ICP-MS comprises several millions of laser shots fired over just a few square mm. This technique combines new chemical images with visual analysis and, in so doing raises new questions that may be answered through techniques in automated image analysis and computer vision. As an illustration of this new frontier, a selected set of key problems is presented, with first examples of how automated image analysis techniques can help solving them. This concerns the relationship between impurity localization and the grain boundary network as well as the paleoclimate significance of single line profiles along the main core axis. Ultimately, this demonstrates that it is the right time to spark an intensified exchange among the two scientific communities of computer vision and ice core science.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/5004828
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