10 AI in Arctic Science
10.1 Cyberinfrastructure and AI in Arctic Science: Tracking and Mapping Arctic Permafrost Thaw
Cyber2A is a project focused on increasing the relevance and utility of machine learning and deep learning for Arctic research. This will be accomplished bby designing a training curriculum on machine learning that focuses on Arctic researc problems, and that can introduce new epople to this field. The Cyber2A network will serve as an important venue for collecting community input on training needs, to engage and recruit potential trainees, and to cultivate new connections with existing Arctic research communities to achieve collective and broader impacts of the Cyber2A training and education.
10.2 Resources
Dr. Wenwen Li, 2024, Cyberinfrastructure and AI in Arctic Science: Tracking and Mapping Arctic Permafrost Thaw
- Download GeoAI: Where machine leanrning and big data converge in GIScience
- Download Capturing the dance of the earth: PolarGlobe; Real-time scientific visualization of vector field data to support climate science
- Download Segment Anything Model Can Not Segment Anything: Assessing AI Foundation Model’s Generalizability in Permafrost Mapping
Download Lowering the Barriers for Accesing Distributed Geospatial Big Data to Advance Spatial Data Science: The PolarHub Solution