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

Abstract

This study conducts a bibliometric analysis of the developmentand evolution of research on Geospatial Artificial Intelligence(GeoAI) literature in the Global South region, examining growthpatterns, collaboration, and thematic priorities. The data for thisbibliometric analysis were specifically compiled from Web ofScience and include publications on context-specific themesthat include ‘challenges, barriers, opportunities, as well as appli-cations’ related to GeoAI authored by 1,316 authors and pub-lished through 110 sources from 2011 to 2025. The data revealsa high average annual growth rate of 29.67%, which marks anincrease in publications since 2016. This could be attributed toadvancements in technology and satellite imagery. The collab-oration pattern was also exhibited, with an average of 8.97authors per publication, with over half of all publicationsauthored by international collaborations. The topics with iden-tifiable major hotspots include South Africa, China, and theUSA, with many citations per publication in Qatar and Egypt.Thematic analysis revealed that remote sensing, machine learn-ing, and deep learning emerged as dominant themes, predom-inantly in the context of environmental, disaster, and agriculturalapplications. Although research articles on GeoAI are graduallygrowing in the Global South, there are still infrastructure, qual-ity, and capacity development challenges.