GeoAI Research in the Global South: Mapping Productivity and Trends Through Bibliometric Analysis

This study conducts a bibliometric analysis of the development and evolution of research on Geospatial Artificial Intelligence (GeoAI) literature in the Global South region, examining growth patterns, collaboration, and thematic priorities. The data for this bibliometric analysis were specifically compiled from Web of Science and include publications on context-specific themes that include ‘challenges, barriers, opportunities, as well as applications’ related to GeoAI authored by 1,316 authors and published through 110 sources from 2011 to 2025. The data reveals a high average annual growth rate of 29.67%, which marks an increase in publications since 2016. This could be attributed to advancements in technology and satellite imagery. The collaboration pattern was also exhibited, with an average of 8.97 authors per publication, with over half of all publications authored by international collaborations. The topics with identifiable major hotspots include South Africa, China, and the USA, with many citations per publication in Qatar and Egypt. Thematic analysis revealed that remote sensing, machine learning, and deep learning emerged as dominant themes, predominantly in the context of environmental, disaster, and agricultural applications. Although research articles on GeoAI are gradually growing in the Global South, there are still infrastructure, quality, and capacity development challenges.