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Title Artificial intelligence in earth science : best practices and fundamental challenges / edited by Ziheng Sun, Nicoleta Cristea, Pablo Rivas.

Publication Info. Amsterdam, Netherlands ; Cambridge, MA, United States : Elsevier, [2023]

Copies

Location Call No. OPAC Message Status
 Axe Elsevier ScienceDirect Ebook  Electronic Book    ---  Available
Description 1 online resource (x, 418 pages) : illustrations (chiefly color), color maps
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Bibliography Includes blibliographical references and index.
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.
Note Description based on online resource; title from digital title page (viewed on January 09, 2024).
Subject Artificial intelligence -- Geophysical applications.
Earth sciences -- Data processing.
Intelligence artificielle -- Applications géophysiques.
Artificial intelligence -- Geophysical applications
Earth sciences -- Data processing
Added Author Sun, Ziheng, editor.
Cristea, Nicoleta, editor.
Rivas Perea, Pablo, 1980- editor.
Other Form: Print version: 0323917372 9780323917377 (OCoLC)1331704030
ISBN 9780323972161 electronic book
0323972160 electronic book
9780323917377 paperback
0323917372 paperback
Standard No. AU@ 000074215276
AU@ 000074384468
UKMGB 020870833

 
    
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