Google Earth Engine and Artificial Intelligence for Earth Observation

Algorithms and Sustainable Applications
Herausgeber: Sood, Vishakha; Pradhan, Biswajeet; Singh, Sartajvir; Gupta, Dileep Kumar

• Broschiertes Buch

Produktbeschreibung

Google Earth Engine and Artificial Intelligence for Earth Observation: Algorithms and Sustainable Applications explores a wide range of transformative data fusion techniques of Artificial Intelligence (AI) technologies applied to Google Earth Engine (GEE) techniques. The book includes a wide range of scientific domains that can utilize remote sensing and geographic information systems (GIS) through detailed case studies. It delves into the challenges of AI-driven tools and technologies for Earth observation data analysis, offering possible solutions and directly addressing current and upcoming needs within Earth Observation. This is a useful reference for geospatial scientists, remote sensing experts, and environmental scientists utilizing remote sensing to apply the latest AI techniques to data obtained from GEE for their research and teaching.

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Produktdetails

• Verlag: Elsevier Science
• Seitenzahl: 508
• Erscheinungstermin: 1. März 2025
• Englisch
• ISBN-13: 9780443273728
• ISBN-10: 0443273723
• Artikelnr.: 70984649

Inhaltsangabe

Section A: GEE cloud computing based Remote Sensing
1. Cloud computing platforms based remote sensing big data applications
2. Role of GEE in earth observation via remote sensing
3. Applications of GEE in sustainable society and environment
4. Sustainable Remote Sensing Data Analysis using GEE and AI
5. Systematic survey on GEE-based projects and their perspectives
Section B: AI-based GEE tool and technologies
6. A comprehensive review of emerging AI-based Machine and Deep learning
algorithms for GEE
7. Comparative Analysis of various Machine and Deep learning classification
algorithms
8. Estimation of land-use land-cover variations using GEE and AI-based
change detection tools
9. Monitoring and mapping of urban development with integration of GEE and
AI
10. Image fusion of optical and microwave satellite datasets using deep
neural networks
11. AI-driven cloud-based remote sensing for big data analysis
Section C: Emerging applications and case studies of GEE in earth
observation
12. Remote sensing for Water resource management with GEE
13. Agriculture mapping for crop monitoring using remote sensing and GEE
14. Mapping and monitoring of forest resources and activities using GEE
15. Response to climate change using AI and cloud computing platforms
16. Role of GEE in natural hazard monitoring and management
17. Estimation of Snow/ice cover parameters using GEE and AI
Section D: Challenges and future trends of GEE
18. Challenges and limitations of the cloud-based platforms
19. Futuristic AI-driven tools and technologies for earth observation data
analytics
20. Exploration of the science of remote sensing and GIS with Google Earth
Engine
21. Creative integration of GEE with AI for algorithms to applications