Automatic detection and dynamics of Martian plasma boundaries from Mars Express and MAVEN missions
Abstract
Many spacecraft have probed planetary environments to understand their dynamics and evolution. The datasets returned from instruments on these spacecraft have been used by researchers to classify "events" and "boundaries" within the planetary environments. This has typically been a time-consuming task, leading in particular to empirical models that however often do not reflect the large dynamics observed. Moreover, eye-based detections may display strong and unexplained biases from a scientist to another. In this paper we report results from the use of machine learning techniques (in particular neural networks) to automatically detect plasma regions or boundaries at Mars (e.g. the solar wind, bow shock and close environment). We also investigate the variability in the Martian bow shock position with different drivers, in particular regarding the influence of the Martian crustal magnetic fields, solar wind parameters and extreme ultraviolet fluxes. We use for these two studies large datasets from both the Mars Express and MAVEN missions.
- Publication:
-
EGU General Assembly Conference Abstracts
- Pub Date:
- April 2019
- Bibcode:
- 2019EGUGA..21.9631G