A Review of Recent Researches and Reflections on Geospatial Artificial Intelligence

GAO Song

doi:10.13203/j.whugis20200597

Volume 45 Issue 12

Dec. 2020

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Geomatics and Information Science of Wuhan University > 2020 > 45(12): 1865-1874. > DOI: 10.13203/j.whugis20200597

GAO Song. A Review of Recent Researches and Reflections on Geospatial Artificial Intelligence[J]. Geomatics and Information Science of Wuhan University, 2020, 45(12): 1865-1874. DOI: 10.13203/j.whugis20200597

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A Review of Recent Researches and Reflections on Geospatial Artificial Intelligence

GAO Song^1,

1.
GeoDS Lab, Department of Geography, University of Wisconsin-Madison, WI 53706, USA

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Author Bio:
GAO Song, PhD, assistant professor. He received his PhD from the University of California-Santa Barbara, and is currently an assistant professor and director of the Geospatial Data Science Lab at the University of Wisconsin-Madison. His research focuses on theories of place-based geographic information science, GeoAI, spatiotemporal big data and social sensing. E-mail:song.gao@wisc.edu
Received Date: November 02, 2020
Published Date: December 04, 2020

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Abstract

Abstract

The technological progress in the field of artificial intelligence (AI) has brought new opportunities and challenges to the intelligent development and innovative research in geospatial related fields. Geospatial artificial intelligence (GeoAI) refers to the interdisciplinary research direction that combines geography, earth science and artificial intelligence, and seeks to solve major scientific and engineering problems in human-environmental interaction systems through the research and development of spatial intelligence in machines to improve the dynamic perception, intelligent reasoning and knowledge discovery of geographic phenomena and earth science processes. This paper briefly summarizes the historical origins of GeoAI development, introduces spatially explicit and implicit AI models, reviews recent GeoAI research and applications(including spatial representation learning, spatiotemporal prediction and spatial interpolation, monitoring of geographic resources and environment, cartography, and geo-text data semantic analysis), and identifies several potential research challenges and directions for the future development of GeoAI.
- geospatial artificial intelligence (GeoAI),
- spatially explicit model,
- deep learning,
- geographic big data

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References (96)

References

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A Review of Recent Researches and Reflections on Geospatial Artificial Intelligence

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