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GIScience in the era of Artificial Intelligence: a research agenda towards Autonomous GIS

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Bibliographic Details
Title: GIScience in the era of Artificial Intelligence: a research agenda towards Autonomous GIS
Authors: Zhenlong Li, Huan Ning, Song Gao, Krzysztof Janowicz, Wenwen Li, Samantha T. Arundel, Chaowei Yang, Budhendra Bhaduri, Shaowen Wang, A-Xing Zhu, Mark Gahegan, Shashi Shekhar, Xinyue Ye, Grant McKenzie, Guido Cervone, Michael E. Hodgson
Source: Annals of GIS. :1-36
Publication Status: Preprint
Publisher Information: Informa UK Limited, 2025.
Publication Year: 2025
Subject Terms: Software Engineering (cs.SE), FOS: Computer and information sciences, Computer Science - Software Engineering, Artificial Intelligence (cs.AI), Emerging Technologies (cs.ET), Computer Science - Artificial Intelligence, Computer Science - Emerging Technologies
Description: The advent of generative AI exemplified by large language models (LLMs) opens new ways to represent and compute geographic information and transcends the process of geographic knowledge production, driving geographic information systems (GIS) towards autonomous GIS. Leveraging LLMs as the decision core, autonomous GIS can independently generate and execute geoprocessing workflows to perform spatial analysis. In this vision paper, we further elaborate on the concept of autonomous GIS and present a conceptual framework that defines its five autonomous goals, five autonomous levels, five core functions, and three operational scales. We demonstrate how autonomous GIS could perform geospatial data retrieval, spatial analysis, and map making with four proof-of-concept GIS agents. We conclude by identifying critical challenges and future research directions, including fine-tuning and self-growing decision-cores, autonomous modeling, and examining the societal and practical implications of autonomous GIS. By establishing the groundwork for a paradigm shift in GIScience, this paper envisions a future where GIS moves beyond traditional workflows to autonomously reason, derive, innovate, and advance geospatial solutions to pressing global challenges. Meanwhile, as we design and deploy increasingly intelligent geospatial systems, we carry a responsibility to ensure they are developed in socially responsible ways, serve the public good, and support the continued value of human geographic insight in an AI-augmented future.
Document Type: Article
Language: English
ISSN: 1947-5691
1947-5683
DOI: 10.1080/19475683.2025.2552161
DOI: 10.48550/arxiv.2503.23633
Access URL: http://arxiv.org/abs/2503.23633
Rights: CC BY
Accession Number: edsair.doi.dedup.....21f7e85b3fcc88ea65d5bac53ff5efd5
Database: OpenAIRE
Description
Abstract:The advent of generative AI exemplified by large language models (LLMs) opens new ways to represent and compute geographic information and transcends the process of geographic knowledge production, driving geographic information systems (GIS) towards autonomous GIS. Leveraging LLMs as the decision core, autonomous GIS can independently generate and execute geoprocessing workflows to perform spatial analysis. In this vision paper, we further elaborate on the concept of autonomous GIS and present a conceptual framework that defines its five autonomous goals, five autonomous levels, five core functions, and three operational scales. We demonstrate how autonomous GIS could perform geospatial data retrieval, spatial analysis, and map making with four proof-of-concept GIS agents. We conclude by identifying critical challenges and future research directions, including fine-tuning and self-growing decision-cores, autonomous modeling, and examining the societal and practical implications of autonomous GIS. By establishing the groundwork for a paradigm shift in GIScience, this paper envisions a future where GIS moves beyond traditional workflows to autonomously reason, derive, innovate, and advance geospatial solutions to pressing global challenges. Meanwhile, as we design and deploy increasingly intelligent geospatial systems, we carry a responsibility to ensure they are developed in socially responsible ways, serve the public good, and support the continued value of human geographic insight in an AI-augmented future.
ISSN:19475691
19475683
DOI:10.1080/19475683.2025.2552161