Towards the intelligent era of spatial analysis and modeling

Di Zhu; Song Gao; Guofeng Cao

doi:10.1145/3557918.3565863

Towards the intelligent era of spatial analysis and modeling

Di Zhu, Song Gao, Guofeng Cao

Geography, Environment and Society

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Scopus citations

Abstract

Geographic phenomena are considered complex due to the heterogeneous nature of spatial dependencies. It is impossible to specify a universal law described in statistical or physical languages that can perfectly characterize a real-world geographic process and explain how it forms certain observed patterns. Traditional spatial analytics based on strict statistical principles, strong assumptions, or classic computation workflows are facing great challenges and opportunities when embracing the explosive growth of geospatial data and recent technical innovations. Here, we highlight the promises of Intelligent Spatial Analytics (ISA), a new set of spatial analytical approaches based on spatially explicit deep neural networks with more flexible data representation, modules for complex spatial dependence, weaker model prior assumptions, and hence the enhanced ability to predict/explain unknowns. Three essential topics in spatial analysis, i.e., geostatistics, spatial econometrics, and flow analytics are elaborated as examples in the vision of ISA. We also discuss challenging issues of ISA as an invitation to explore deeper linkages between machine/deep learning and spatial analysis at the frontier of Geospatial Artificial Intelligence.

Original language	English (US)
Title of host publication	Proceedings of the 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2022
Editors	Bruno Martins, Dalton Lunga, Song Gao, Shawn Newsam, Lexie Yang, Xueqing Deng, Gengchen Mai
Publisher	Association for Computing Machinery, Inc
Pages	10-13
Number of pages	4
ISBN (Electronic)	9781450395328
DOIs	https://doi.org/10.1145/3557918.3565863
State	Published - Nov 1 2022
Event	5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2022 - Seattle, United States Duration: Nov 1 2022 → …

Publication series

Name	Proceedings of the 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2022

Conference

Conference	5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2022
Country/Territory	United States
City	Seattle
Period	11/1/22 → …

Bibliographical note

Funding Information:
Di Zhu is supported by the New Faculty Set-up Funding, University of Minnesota (1000-10964-20042-5672018) and the Faculty Interactive Research Program from Center for Urban and Regional Affairs (1801-10964-21584-5672018); Song Gao is supported by the National Science Foundation (no. 2112606); Guofeng Cao is supported by the National Science Foundation (no. 2026331).

Publisher Copyright:
© 2022 ACM.

Keywords

GIS
GeoAI
intelligent spatial analytics
neural networks
spatial analysis

Publisher link

10.1145/3557918.3565863

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Zhu, D., Gao, S., & Cao, G. (2022). Towards the intelligent era of spatial analysis and modeling. In B. Martins, D. Lunga, S. Gao, S. Newsam, L. Yang, X. Deng, & G. Mai (Eds.), Proceedings of the 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2022 (pp. 10-13). (Proceedings of the 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2022). Association for Computing Machinery, Inc. https://doi.org/10.1145/3557918.3565863

Towards the intelligent era of spatial analysis and modeling. / Zhu, Di; Gao, Song; Cao, Guofeng.
Proceedings of the 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2022. ed. / Bruno Martins; Dalton Lunga; Song Gao; Shawn Newsam; Lexie Yang; Xueqing Deng; Gengchen Mai. Association for Computing Machinery, Inc, 2022. p. 10-13 (Proceedings of the 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Zhu, D, Gao, S & Cao, G 2022, Towards the intelligent era of spatial analysis and modeling. in B Martins, D Lunga, S Gao, S Newsam, L Yang, X Deng & G Mai (eds), Proceedings of the 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2022. Proceedings of the 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2022, Association for Computing Machinery, Inc, pp. 10-13, 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2022, Seattle, United States, 11/1/22. https://doi.org/10.1145/3557918.3565863

Zhu D, Gao S, Cao G. Towards the intelligent era of spatial analysis and modeling. In Martins B, Lunga D, Gao S, Newsam S, Yang L, Deng X, Mai G, editors, Proceedings of the 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2022. Association for Computing Machinery, Inc. 2022. p. 10-13. (Proceedings of the 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2022). doi: 10.1145/3557918.3565863

Zhu, Di ; Gao, Song ; Cao, Guofeng. / Towards the intelligent era of spatial analysis and modeling. Proceedings of the 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2022. editor / Bruno Martins ; Dalton Lunga ; Song Gao ; Shawn Newsam ; Lexie Yang ; Xueqing Deng ; Gengchen Mai. Association for Computing Machinery, Inc, 2022. pp. 10-13 (Proceedings of the 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2022).

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Towards the intelligent era of spatial analysis and modeling

Abstract

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Bibliographical note

Keywords

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