[M-IS19] Aqua planetology

[MIS19-P02] Serch for Martian Subsurface Cryosphere based on Rampart Crater Distribution and Morphology

*Kanori Sugimoto^1,2, Tomohiro Usui², Hirohide Demura³ (1.The University of Tokyo, 2.JAXA ISAS, 3.University of Aizu)

Keywords:Mars, Subsurface Ice, Cryosphere, Rampart Crater

Mars is believed to have once hosted a warm and wet environment capable of sustaining liquid water on its surface, which has since dissipated into space. Recent observations from orbiters have unveiled ice exposed on the Martian surface, affirming the current presence of water in its frozen state. However, the volume of this present-day water ice does not align with estimates of the volumes of ancient Martian oceans, even when accounting for the water lost to space over time. This inconsistency hints at the possible existence of remnants of these ancient oceans beneath the Martian surface. The study of Rampart craters, formed by impacts into a subsurface layer rich in volatile substances, provides ample information of subsurface ice at the time of their formation.Rampart craters are differentiated based on their ejecta patterns into Single-Layered Ejecta (SLE), Double-Layered Ejecta (DLE), and Multiple-Layered Ejecta (MLE) categories. The two-layered lobes of DLE craters are comprised of a thick inner lobe, formed from subsurface volatiles, and a thin outer lobe, interpreted to be the result of interactions between ejecta curtains and the atmosphere. In contrast, the formation of SLE craters, potentially through both volatile and atmospheric processes, necessitates caution when using them as indicators of subsurface ice. Although previous research has investigated the distribution of SLE, DLE, and MLE craters, there has not yet been a comprehensive classification that distinguishes between volatile-derived and atmospheric origins for SLE craters. Then, it is necessary to investigate the distribution of Rampart craters including classification of each SLE craters, which is formed by atmospheric and volatiles. Traditional visual classification of the rampart craters have posed significant challenges in estimating the depth of subsurface ice based on crater morphology and distribution. To overcome these challenges, we employed a machine learning classification model to analyze Martian rampart craters using high-resolution visible and thermal infrared imagery, reporting on the accuracy of our methodology.
[1] Weiss, David K., and James W. Head. "Formation of double-layered ejecta craters on Mars: A glacial substrate model" (2013) [2] Schultz, Peter H. "Atmospheric effects on ejecta emplacement." (1992) [3] Li, Li, et al. "Observations pf Martian layered ejecta craters and constraints on their formation mechanisms." (2015)