Publication Type
Journal Article
Version
publishedVersion
Publication Date
2-2025
Abstract
Geospatial Artificial Intelligence (GeoAI), as the integration of geospatial studies and AI, has become one of the fastest-developing research directions in spatial data science and geography. This rapid change in the field calls for a deeper understanding of the recent developments and envision where the field is going in the near future. In this work, we provide a quantitative analysis of the GeoAI literature from the spatial, temporal, and semantic aspects. We briefly discuss the history of AI and GeoAI by highlighting some pioneering work. Then we discuss the current landscape of GeoAI by selecting five representative subdomains including remote sensing, urban computing, Earth system science, cartography, and geospatial semantics. Finally, we highlight several unique future research directions of GeoAI which are classified into two groups: GeoAI method development challenges and GeoAI Ethics challenges. Topics include heterogeneity-aware GeoAI, knowledge-guided GeoAI, spatial representation learning, geo-foundation models, fairness-aware GeoAI, privacy-aware GeoAI, as well as interpretable and explainable GeoAI. We hope our review of GeoAI’s past, present, and future is comprehensive and can enlighten the next generation of GeoAI research.
Keywords
Geospatial Artificial Intelligence, Heterogeneity-aware GeoAI, Knowledge-Guided GeoAI, Spatial representation learning, Geo-Foundation Models, Fairness-aware GeoAI, Privacy-aware GeoAI, Interpretable and explainable GeoAI
Discipline
Artificial Intelligence and Robotics | Geographic Information Sciences
Research Areas
Integrative Research Areas
Publication
International Journal of Applied Earth Observation and Geoinformation
Volume
136
First Page
1
Last Page
20
ISSN
1569-8432
Identifier
10.1016/j.jag.2025.104368
Publisher
Elsevier
Citation
MAI, Gengchen; XIE, Yiqun; JIA, Xiaowei; LAO, Ni; RAO, Jinmeng; ZHU, Qing; LIU, Zeping; CHIANG, Yao-Yi; and JIAO, Junfeng.
Towards the next generation of Geospatial Artificial Intelligence. (2025). International Journal of Applied Earth Observation and Geoinformation. 136, 1-20.
Available at: https://ink.library.smu.edu.sg/cis_research/472
Copyright Owner and License
Authors-CC-BY
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.
Additional URL
https://doi.org/10.1016/j.jag.2025.104368