Global, Seasonal Mars Frost Maps
Description
Global frost Martian maps derived from five remote sensing datasets and processed with tools like CNNs and other data science techniques. Publicly available on JMARS
Detailed example
Near-global maps showing detections of seasonal frost in visible datasets (HiRISE, CTX) with associated uncertainties.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
(1) Mars seasonal frost maps that can be used by other researchers, enabling more time on analysis rather than data collection. (2) Demonstration of a deeply collaborative effort between data scientists and physical scientists.
Controls / human review
ATO: No; PIA: Not published
Data needed
Visible images acquired from orbit of the martian surface. Some images were human-labeled, then used in training, validation, and testing of the CNN.