The evolution and current landscape of AI in geographical research: A large-scale systematic review

• A systematic review of AI use in geography based on 400,000 papers was conducted. • AI was used in 8.1 % of geography research, with over half applying traditional ML. • About 62.78 % of the studies reviewed were conducted in China and the US. • GIScience-related topics are the main focus of AI geography research. With the rapid advancement of Artificial Intelligence (AI) technologies, its applications have become increasingly widespread across various aspects of geography, offering unprecedented analytical capabilities across disciplinary boundaries. Despite this revolutionary potential, a comprehensive understanding of the current research landscape and development trajectory of AI in geographical sciences remains limited. To fill this gap, we conducted a large-scale systematic review based on 400,000 geographical publications published from 1990 to 2023. We utilized large language model (LLM) prompt engineering, topic modeling and other natural language processing techniques to analyze the publications. Our findings reveal that AI applications constitute 8.1 % of geographical research, with publication volume having increased 20-fold over three decades. Both China and the United States have been the leading contributors to AI-driven geographical studies, together accounting for 62.78 % of all publications in this field. Notably, more than half of the studies used traditional machine learning methods. Among the various geographical topics, remote sensing applications and spatial data analysis emerged as the most extensively explored areas using AI techniques, with image feature extraction being the topic with the deepest level of adoption and most significant ongoing impact of AI methods. This systematic review provides critical insights into the integration trajectory of AI within geographical sciences, establishing a foundation for identifying emerging research opportunities and enhancing our understanding of AI’s transformative role in advancing geographical knowledge.

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Publication Details

Journal
Geography and sustainability
Published
2025-11-28
DOI
https://doi.org/10.1016/j.geosus.2025.100392
Primary Topic
Human Mobility and Location-Based Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

The evolution and current landscape of AI in geographical research: A large-scale systematic review

Geography and sustainability
Human Mobility and Location-Based Analysis
article

The evolution and current landscape of AI in geographical research: A large-scale systematic review

article en

Abstract

• A systematic review of AI use in geography based on 400,000 papers was conducted. • AI was used in 8.1 % of geography research, with over half applying traditional ML. • About 62.78 % of the studies reviewed were conducted in China and the US. • GIScience-related topics are the main focus of AI geography research. With the rapid advancement of Artificial Intelligence (AI) technologies, its applications have become increasingly widespread across various aspects of geography, offering unprecedented analytical capabilities across disciplinary boundaries. Despite this revolutionary potential, a comprehensive understanding of the current research landscape and development trajectory of AI in geographical sciences remains limited. To fill this gap, we conducted a large-scale systematic review based on 400,000 geographical publications published from 1990 to 2023. We utilized large language model (LLM) prompt engineering, topic modeling and other natural language processing techniques to analyze the publications. Our findings reveal that AI applications constitute 8.1 % of geographical research, with publication volume having increased 20-fold over three decades. Both China and the United States have been the leading contributors to AI-driven geographical studies, together accounting for 62.78 % of all publications in this field. Notably, more than half of the studies used traditional machine learning methods. Among the various geographical topics, remote sensing applications and spatial data analysis emerged as the most extensively explored areas using AI techniques, with image feature extraction being the topic with the deepest level of adoption and most significant ongoing impact of AI methods. This systematic review provides critical insights into the integration trajectory of AI within geographical sciences, establishing a foundation for identifying emerging research opportunities and enhancing our understanding of AI’s transformative role in advancing geographical knowledge.

Geography and sustainabilityVol. 7(1)
Chinese Academy of Sciences (CN), Institute of Geographic Sciences and Natural Resources Research (CN), University of Chinese Academy of Sciences (CN)
Quality Education
Openalex Percentile: Top 38%
Human Mobility and Location-Based Analysis
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