| Description |
1 online resource (x, 418 pages) : illustrations (chiefly color), color maps |
| Contents |
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 |
| Summary |
"Artificial Intelligence in Earth Science: Best Practices and Fundamental Challenges provides a comprehensive, step-by-step guide to AI workflows for solving problems in Earth Science. The book focuses on the most challenging problems in applying AI in Earth system sciences, such as training data preparation, model selection, hyperparameter tuning, model structure optimization, spatiotemporal generalization, transforming model results into products, and explaining trained models. In addition, it provides full-stack workflow tutorials to help walk readers through the whole process, regardless of previous AI experience. The book tackles the complexity of Earth system problems in AI engineering, fully guiding geoscientists who are planning to implement AI in their daily work." -- Provided by publisher |
| Bibliography |
Includes blibliographical references and index |
| Notes |
Description based on online resource; title from digital title page (viewed on January 09, 2024) |
| Subject |
Artificial intelligence -- Geophysical applications.
|
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Earth sciences -- Data processing.
|
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Artificial intelligence -- Geophysical applications
|
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Earth sciences -- Data processing
|
| Form |
Electronic book
|
| Author |
Sun, Ziheng, editor
|
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Cristea, Nicoleta, editor.
|
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Rivas Perea, Pablo, 1980- editor.
|
| ISBN |
9780323972161 |
|
0323972160 |
|
