GeoAI for Earth Observation Imagery
Fundamentals and Practical Applications
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Product details:
- Publisher Elsevier Science
- Date of Publication 1 July 2026
- ISBN 9780443437960
- Binding Paperback
- No. of pages400 pages
- Size 235x191 mm
- Weight 450 g
- Language English 700
Categories
Long description:
GeoAI for Earth Observation Imagery: Fundamentals and Practical Applications comprehensively covers methodologies of AI and Machine Learning applications of image processing for Earth Observation (EO) Imagery. As traditional image processing methods face challenges with handling vast volumes of EO imagery, leading to efficiencies and limitations when extracting meaningful insights, AI-driven approaches can enhance the efficiency, accuracy, and scalability of image processing. Chapters cover essential methodologies including atmospheric compensation, image enhancement techniques like deblurring and superresolution, and advanced analysis methods such as semantic segmentation and object detection.
Cutting-edge approaches to computing, automating, and optimizing image processing tasks are also covered. Additionally, emerging trends in GeoAi and their implication on future research are reviewed. The book serves as an essential guide for navigating the complexities of spatial data and equips readers with knowledge to enhance their analytical capabilities.
Table of Contents:
Part I - Image Preprocessing
1. Atmospheric Compensation
2. Rectification
3. Geocoding
4. Image Registration
5.Mosaicking
Part II - Image Enhancement
6. Image Restoration/Deblurring
7. Pansharpening
8. Superresolution
9. Denoising
Part III - Image Analysis
10. Semantic Segmentation
11. Synthesis
12. Visualization
13. Data Fusion
14. Foundation Models/Self-Supervised Learning/Fine-tuning
15. Object Detection
16. Visual Question Answering (VQA)
Part IV - Computing
17. Geospatial Libraries
18. Machine Learning Libraries
19. High Performance Computing
20. Cloud Computing
21. Conclusions/Future Perspectives
