Handbook of Geospatial Artificial Intelligence (Paperback, 1)

Section 1: Historical Roots of GeoAI  1. Introduction to Geospatial Artificial Intelligence (GeoAI)  2. GeoAI’s Thousands Years of History  3. Philosophical Foundations of GeoAI  Section 2: GeoAI Methods  4. GeoAI Methodological Foundations: Deep Neural Networks and Knowledge Graphs  5. GeoAI for Spatial Image Processing  6. Spatial Representation Learning in GeoAI  7. Intelligent Spatial Prediction and Interpolation Methods  8. Heterogeneity-Aware Deep Learning in Space: Performance and Fairness  9. Explainability in GeoAI  10. Spatial Cross-Validation for GeoAI  Section 3: GeoAI Applications  11. GeoAI for the Digitization of Historical Maps  12. Spatiotemporal AI for Transportation  13. GeoAI for Humanitarian Assistance  14. GeoAI for Disaster Response  15. GeoAI for Public Health  16. GeoAI for Agriculture  17. GeoAI for Urban Sensing  Section 4: Perspectives for the Future of GeoAI  18. Reproducibility and Replicability in GeoAI  19. Privacy and Ethics in GeoAI  20. A Humanistic Future of GeoAI  21. (Geographic) Knowledge Graphs and Their Applications  22. Forward Thinking on GeoAI