Strategic Planning Insights for Future Science-Driven Extravehicular Activity on Mars
Author(s) -
Allyson L. Brady,
S. E. Kobs Nawotniak,
S. S. Hughes,
Samuel J. Payler,
Adam Stevens,
Charles S. Cockell,
R. C. Elphic,
A. Sehlke,
C. W. Haberle,
G. F. Slater,
D. S. S. Lim
Publication year - 2019
Publication title -
astrobiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.234
H-Index - 90
eISSN - 1531-1074
pISSN - 1557-8070
DOI - 10.1089/ast.2018.1850
Subject(s) - mars exploration program , habitability , software deployment , multispectral image , earth science , terrain , computer science , exploration of mars , strategic planning , systems engineering , remote sensing , environmental resource management , environmental science , astrobiology , engineering , geology , geography , artificial intelligence , business , planet , physics , cartography , marketing , astrophysics , operating system
Short-term and long-term science plans were developed as part of the strategic planning process used by the Biologic Analog Science Associated with Lava Terrains (BASALT) science team to conduct two Mars-simulation missions investigating basalt habitability at terrestrial volcanic analog sites in 2016. A multidisciplinary team of scientists generated and codified a range of scientific hypotheses distilled into a Science Traceability Matrix (STM) that defined the set of objectives pursued in a series of extravehicular activity (EVA) campaigns performed across multiple field deployments. This STM was used to guide the pre-deployment selection of sampling stations within the selected Mars analog sites on the Earth based on precursor site information such as multispectral imagery. It also informed selection of hand-held instruments and observational data to collect during EVA to aid sample selection through latency-impacted interaction with an Earth-based Science Support Team. A significant portion of the pre-deployment strategic planning activities were devoted to station selection, ultimately the locations used for sample collection and EVA planning. During development of the EVAs, the BASALT science team identified lessons learned that could be used to inform future missions and analog activities, including the critical need for high-resolution precursor imagery that would enable the selection of stations that could meet the scientific objectives outlined in the STM.
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