http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Artificial intelligence in earth science
best practices and fundamental challenges
1 online resource ( x, 418 pages) : illustrations (chiefly color), color maps.
Part I: Fundamentals of Earth AI -- 1. Basic Concepts of Earth AI -- 2. Introductory AI Algorithms -- 3. AI Infrastructure -- hardware and software for developing Earth AI -- Part II. Existing Best Practices -- 4. AI for Earthquake Hidden Signal Detection -- 5. AI for Dust Storm Detection -- 6. AI for Snow Monitoring -- 7. AI for Volcano Pre-warning and Prediction -- 8. AI for Landslide Damage Assessment -- 9. AI for Hurricane Prediction -- 10. AI for Precipitation Prediction -- 11. AI for Drought Monitoring -- 12. AI for Wildfire Detection -- 13. AI for Air Quality Prediction -- 14. AI for Agricultural Irrigation Decision Making -- 15. AI for Land Cover Land Use Classification -- 16. AI for Ocean mesoscale eddies detection -- Part III Fundamental Challenges for AI in Earth Sciences -- 17. AI Model Selection and Tuning -- 18. Training Data Preparation -- 19. Explainable AI -- 20. AI Generalization -- 21. AI Integration with Physics-based Models -- 22. AI Provenance (Replicability & Reproducibility) -- 23. AI Ethics
edited by Ziheng Sun, Nicoleta Cristea, Pablo Rivas.
Includes blibliographical references and index.