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Product details:
- Publisher Elsevier Science
- Date of Publication 1 June 2026
- ISBN 9780443315749
- Binding Paperback
- No. of pages360 pages
- Size 235x191 mm
- Language English 700
Categories
Long description:
The Geoinformatics Frontier: AI, Big Data, and Crowdsourced Technologies tackles the critical challenge of integrating Geoinformatics, AI, Big Data, and VGI; offering a comprehensive introduction to these pivotal concepts, the book elucidates their foundations and relevance to Geoinformatics. It approaches builds on the theory discussed with practical guidance, examples, and detailed case studies; equipping readers with the knowledge needed to effectively implement them. The book presents case studies spanning various sectors, showcasing how the technologies can be successfully employed to address intricate spatial issues and facilitate well-informed decision-making for the complexities of managing large-scale spatial datasets. It also provides indispensable insights into data collection, storage, quality control, and fusion techniques, offering practical solutions to the challenges of data storage, processing, and analysis. The Geoinformatics Frontier serves as an indispensable guide, bridging the gap in understanding and practice for geospatial scientists, empowering readers to harness the transformative potential of Geoinformatics and advanced computer technologies.
MoreTable of Contents:
Section 1: Foundations of Geoinformatics
1. The New Era in Geoinformatics
2. Geoinformatics and spatial practice via new technologies
3. Big Earth data in practice
4. Fundamental of Crowdsourced technologies
5. Crowdsourced data contribution towards geospatial matureness
Section 2: Artificial Intelligence in spatial practice
6. AI in spatial object recognition
7. Geocomputation and geospatial artificial intelligence
8. Deep Learning-based flood recognition
9. UAV Imagery and Deep Learning
10. Earth observation data and AI
11. Neural Network techniques for spatial forecasting
12. AI, ANN in landslides modelling
Section 3: Big Earth Data in Geoinformatics
13. Imagery big data for mapping
14. Big earth observation data (Professor Xiao Huang)
15. Big Meteorological observation data towards making environmental indices
16. Lidar point cloud available techniques
17. Predicting changes via big earth observation data
18. Big data for Analysis Ready Data (ARD)
19. Using online platforms for handling big observation data
20. Big Earth data and FOSS4G
21. Sensors big data
Section 4: Crowdsourced technologies in the new Geoinformatics era
22. VGI and crowdsourcing in geographic practice
23. Innovative Crowd Science
24. Policy aspects of environmental information, crowdsourced geographic information, and citizen science
25. Volunteered Geographic Information (VGI) quality assessment
26. Volunteered Geographic Information (VGI) and Crowdsourced practices of spatial data in geographic research
27. Public Good Provision and online communities
28. VGI in environmental management
29. Spatial bias in VGI
30. Crowdsourcing, citizen science or volunteered geographic information
31. Conclusions
