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Software . 2026
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Software . 2026
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ZENODO
Software . 2026
Data sources: Datacite
ZENODO
Software . 2026
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GeoAI: A Python package for integrating artificial intelligence with geospatial data analysis and visualization

Authors: Wu, Qiusheng;

GeoAI: A Python package for integrating artificial intelligence with geospatial data analysis and visualization

Abstract

GeoAI provides a unified, user-friendly interface that abstracts the complexity of integrating multiple AI frameworks with geospatial data processing workflows. It lowers barriers for: (1) geospatial researchers who need accessible AI workflows without deep ML expertise; (2) AI practitioners who want streamlined geospatial preprocessing and domain-specific datasets; and (3) educators seeking reproducible examples and teaching-ready workflows. The package's design philosophy emphasizes simplicity without sacrificing functionality, enabling users to perform sophisticated analyses such as building footprint extraction from satellite imagery, land cover classification, and change detection with just a few lines of code. By integrating cutting-edge AI models and providing seamless access to major geospatial data sources, GeoAI significantly lowers the barrier to entry for geospatial AI applications while maintaining the flexibility needed for advanced research applications.

Related Organizations
Keywords

python, deep learning, geoai, geospatial

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average