Artificial Intelligence in Web-Based Geographic Information Systems: A Cross-Disciplinary Review

Hayati, Euis Neni

International Journal of Research and Applied Technology (INJURATECH)
Vol. 4 No. 2 (2024): Vol 4 No 2 (2024)

This study examines the integration of Artificial Intelligence (AI) into Web-Based Geographic Information Systems (WebGIS) from a cross-disciplinary perspective. By conducting a structured review of 15 scholarly articles published between 2019 and 2025, this paper aims to explore how AI technologies—such as machine learning, natural language processing, and computer vision enhance spatial analysis and decision-making across various sectors. The findings indicate a growing trend in AI-WebGIS research, particularly in areas like environmental monitoring, disaster management, smart agriculture, public health, and education. While AI integration offers significant advancements in automation, scalability, and user interactivity, several limitations remain, including ethical considerations, data standardization issues, and limited real-world implementation. This review highlights future opportunities in building more inclusive, interoperable, and operationally scalable WebGIS platforms powered by AI.