Responsible GeoAI Framework Proposed for Climate Disaster Mapping
A position paper on arXiv (2605.00315) introduces a framework for responsible Geospatial Artificial Intelligence (GeoAI) in climate extreme and disaster mapping. As climate events intensify, GeoAI offers transformative potential for large-scale disaster mapping and risk reduction. However, purely performance-driven deployment risks amplifying spatial inequalities, hindering emergency decisions, and increasing carbon footprint. The paper examines responsible GeoAI from a critical GIS perspective, addressing four theoretical dimensions: Representativeness, Explainability, Sustainability, and Ethics. It also proposes a conceptual governance model for operational practice.
Key facts
- arXiv paper 2605.00315 proposes responsible GeoAI framework
- GeoAI is used for large-scale disaster mapping and risk reduction
- Performance-driven GeoAI can amplify spatial inequalities
- Four dimensions: Representativeness, Explainability, Sustainability, Ethics
- Paper takes a critical GIS perspective
- Conceptual governance model proposed for operational practice
- Climate extreme events are becoming more frequent and intense
- GeoAI deployment can produce severe environmental carbon footprint
Entities
Institutions
- arXiv