This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1007/978-981-19-3816-0_17. This is version 1 of this Preprint.
GeoAI and the Future of Spatial Analytics
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Abstract
This chapter discusses the challenges of traditional spatial analytical methods in their limited capacity to handle big and messy data, as well as mining unknown or latent patterns. It then introduces a new form of spatial analytics – geospatial artificial intelligence (GeoAI) - and describes the advantages of this new strategy in big data analytics and data-driven discovery. Finally, a convergent spatial analytical framework is suggested as a potential future pathway for spatial analysis.
DOI
https://doi.org/10.31223/X5DT3J
Subjects
Computer Sciences, Earth Sciences, Environmental Sciences, Environmental Studies, Geography, Library and Information Science, Physical Sciences and Mathematics, Social and Behavioral Sciences
Keywords
spatial analysis, GeoAI, Artificial Intelligence, Deep learning, Data-driven discovery
Dates
Published: 2024-05-01 07:29
Last Updated: 2024-05-01 11:29
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