GeoAI: Beyond mapping earth and cities through explainability, adaptability, and sustainability
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Summary
This summary is machine-generated.Geospatial artificial intelligence (GeoAI) integrates AI with geospatial data to advance Earth and urban system understanding. This special issue explores GeoAI
Area Of Science
- Earth and Urban System Science
- Artificial Intelligence
- Geospatial Data Science
Background
- Geospatial artificial intelligence (GeoAI) is revolutionizing Earth and urban system analysis.
- A special issue in *iScience* showcases recent GeoAI advancements and applications.
- GeoAI integrates artificial intelligence (AI) with geospatial data and methodologies.
Purpose Of The Study
- To highlight recent GeoAI advances and applications.
- To present perspectives on GeoAI's explainability, adaptability, and sustainability.
- To map interactions among GeoAI dimensions for future solution design.
Main Methods
- Review of 11 case studies from the *iScience* special issue.
- Analysis of GeoAI applications in Earth and urban systems.
- Mapping of GeoAI dimensions: four types of explainability, three levels of adaptability, and three sustainability areas.
Main Results
- GeoAI applications extend beyond traditional mapping.
- Methodological diversity and practical relevance of GeoAI demonstrated.
- Interactions among GeoAI explainability, adaptability, and sustainability are mapped.
Conclusions
- GeoAI offers significant opportunities for understanding and managing Earth and urban systems.
- Future research directions are outlined to address complex challenges.
- GeoAI's potential for explainability, adaptability, and sustainability is emphasized.
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