<![CDATA[This study aims to analyze the opportunities and risks of using geospatial artificial intelligence, or GeoAI, in disaster risk mapping and to formulate an ethical responsible GeoAI governance framework for local government decision-making. This research employed a qualitative approach using a conceptual-analytical case study method. Data were collected through in-depth interviews, limited discussions, and document analysis of regulations, disaster management documents, risk maps, geospatial data policies, and relevant academic publications. The data were analyzed thematically through data reduction, theme categorization, data presentation, interpretation, and framework formulation. The findings show that GeoAI offers strategic opportunities to strengthen disaster risk mapping through the integration of spatial data, satellite imagery, remote sensing, demographic data, socio-economic data, infrastructure data, and environmental data. GeoAI can support the identification of hazard-prone areas, vulnerable groups, mitigation priorities, evacuation routes, risk-based budgeting, and pre-disaster action. However, the use of GeoAI also presents ethical risks, including spatial bias, unequal territorial representation, location privacy violations, algorithmic opacity, and limited community participation in validating risk maps. The main contribution of this study is the formulation of an ethical responsible GeoAI governance framework consisting of seven components: geospatial data governance, model transparency, algorithmic accountability, field validation and public participation, location privacy protection, spatial justice, and continuous adaptive evaluation. This framework positions GeoAI as a spatial decision-support system that is rapid, ethical, inclusive, and remains under meaningful human control.]]>
Copyrights © 2025
