A bibliometric analysis of artificial intelligence applications in geospatial and geographic intelligence

Abstract

This study presents a comprehensive bibliometric analysis of the application of artificial intelligence in geospatial research and geographic intelligence. Using the Scopus database and visualization tools such as VOSviewer and Microsoft Excel, this study systematically maps the scientific literature across the five analytical dimensions: publication trends, citation structure, co-citation patterns, bibliographic merging, and keyword co-occurrence. The findings indicate a significant increase in global research interest, especially after 2020, with major contributions from the United States, China, and the United Kingdom. The results also reveal thematic clusters ranging from remote sensing and disaster response to smart city planning and spatial prediction. Through science mapping and performance analysis, the study highlights the intellectual structure and conceptual evolution of the field. The study contributes to academic understanding by identifying research gaps, emerging themes, and collaboration patterns, which can guide future interdisciplinary research in the artificial intelligence and geospatial domain.