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A system for managing mobile Earth science sensors integrates machine learning with planning and data visualization. The method involves data mining to identify discrepancies between past observations and model predictions, which then inform future flight planning targets. This dataset from NASA Ames, last updated in March 2026, supports a continuous cycle of observation, analysis, and planning over multi-week investigations.
Primary data files appear to be PNG and HTML formats, which may contain visualizations or documentation rather than raw sensor or planning data.