In this paper GeoAI is introduced as an emergent spatial analytical framework for data-intensive GIScience. As the new fuel of geospatial research, GeoAI leverages recent breakthroughs in machine learning and advanced computing to achieve scalable processing and intelligent analysis of geospatial big data. The three-pillar view of GeoAI, its two methodological threads (data-driven and knowledge-driven), as well as their geospatial applications are highlighted. The paper concludes with discussion of remaining challenges and future research directions of GeoAI.
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"GeoAI: Where machine learning and big data converge in GIScience,"
Journal of Spatial Information Science:
Available at: https://digitalcommons.library.umaine.edu/josis/vol2020/iss20/9