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

Format:

Book

Contributor:

Sun, Ziheng, editor.

Cristea, Nicoleta, editor.

Rivas Perea, Pablo, 1980- editor.

ScienceDirect (Online service)

Language:

English

Subjects (All):

Artificial intelligence--Geophysical applications.

Artificial intelligence.

Earth sciences--Data processing.

Earth sciences.

Physical Description:

1 online resource (x, 418 pages) : illustrations (chiefly color), color maps

Place of Publication:

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

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

Notes:

Includes blibliographical references and index.

Electronic reproduction. Amsterdam Available via World Wide Web.

Description based on online resource; title from digital title page (viewed on January 09, 2024).

Other Format:

Print version:

ISBN:

9780323972161

0323972160

Publisher Number:

90100839878

Access Restriction:

Restricted for use by site license.