Buch, Englisch, 375 Seiten, Format (B × H): 152 mm x 229 mm
Exploring Applications with Geospatial Insights
Buch, Englisch, 375 Seiten, Format (B × H): 152 mm x 229 mm
ISBN: 978-0-443-26741-3
Verlag: Elsevier Science
Remote Sensing, Big Data, and GeoAI: Exploring Applications with Geospatial Insights is a foundational analysis and review exploring the transformative intersection of cutting-edge technologies in remote sensing. From fundamentals to advanced applications, this book equips readers with the knowledge and tools needed to apply AI and Big Data to remote sensing research, in order to improve decision-making and analysis. The book employs a dual approach, providing accessible explanations followed by real-world examples and case studies to bridge the gap between theory and practice. Readers will gain a deeper understanding of practical implications through a structured format that balances theoretical knowledge with immersive case studies, and will also gain an appreciation for ethical and legal considerations, making it an invaluable resource. Remote Sensing, Big Data, and GeoAI: Exploring Applications with Geospatial Insights offers insights for researchers, professionals, and students interested in harnessing the latest AI and Big Data techniques in remote sensing to address complex geospatial challenges.
Autoren/Hrsg.
Fachgebiete
- Geowissenschaften Geographie | Raumplanung Geodäsie, Kartographie, GIS, Fernerkundung
- Geowissenschaften Geologie GIS, Geoinformatik
- Geowissenschaften Geologie Geologie
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
- Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware
Weitere Infos & Material
1. Big Data in Geospatial Context: Challenges and Opportunities
2. Fundamental of GeoAI: Common Approaches in Remote Sensing
3. Earth Observations and Satellite Imagery in a Big Data World
4. Big Data Remote Sensing and Data Acquisition and Preprocessing
5. Big Data Analytics for Geospatial Applications
6. GEOAI Algorithms and Techniques for Image Analysis
7. Integration of Remote Sensing, Big Data, and GeoAI
8. Remote Sensing and Big Data Applications in Agriculture
9. Remote Sensing and Big Data Applications in Water
10. Remote Sensing and Big Data Applications in Coastal Environmental
11. Remote Sensing and Big Data Applications in Environmental Management
12. Environmental Monitoring and Conservation Using Remote Sensing and Big Data
13. Disaster Management and Remote Sensing Applications
14. Spatial Data Visualization and Interpretation as it Pertains to Big Data, Remote Sensing, and GeoAI
15. Ethical and Legal Considerations in Remote Sensing and Big Data
16. How Citizen Science and New Technologies can Integrate with Big Data
17. Bringing Big Data and GeoAI into the Classroom: Preparing Undergraduate and Graduate Students for the Future of Geospatial Research
18. Future Trends and Emerging Technologies in Remote Sensing, Big Data, and GeoAI