Opportunities and challenges of integrating geographic information science and large language models
- Author
- Nico Van de Weghe (UGent) , Lars De Sloover (UGent) , Anthony Cohn, Haosheng Huang (UGent) , Simon Scheider, Renée Sieber, Sabine Timpf and Christophe Claramunt
- Organization
- Abstract
- The integration of large language models (LLMs) with geographic information science (GIScience) represents a new frontier in interdisciplinary research that combines advanced natural language processing with sophisticated spatial data analysis. This paper explores the synergistic potential of combining the natural language understanding and generation capabilities of LLMs with the expertise of GIScience in handling complex geospatial data. By exploring the specific contributions that LLMs can offer to GIScience, such as improving data processing, analysis, and visualization, and the mutual benefits that GIScience can offer to LLMs in terms of spatial reasoning and conceptual frameworks, we outline a comprehensive framework and a research agenda for this integration. Furthermore, we address the societal and ethical implications of this convergence, highlighting the challenges of bias, misinformation, and environmental impact. Through this exploration, we aim to set the stage for innovative applications in urban planning, environmental analysis, and beyond, while emphasizing the need for responsible use of AI.
- Keywords
- large language models (LLMs), geographic information science (GIScience), multimodal data integration, spatial reasoning
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01JXF3A61C5GXJZVQSA5FYQGY5
- MLA
- Van de Weghe, Nico, et al. “Opportunities and Challenges of Integrating Geographic Information Science and Large Language Models.” JOURNAL OF SPATIAL INFORMATION SCIENCE, no. 30, 2025, pp. 93–116, doi:10.5311/josis.2025.30.389.
- APA
- Van de Weghe, N., De Sloover, L., Cohn, A., Huang, H., Scheider, S., Sieber, R., … Claramunt, C. (2025). Opportunities and challenges of integrating geographic information science and large language models. JOURNAL OF SPATIAL INFORMATION SCIENCE, (30), 93–116. https://doi.org/10.5311/josis.2025.30.389
- Chicago author-date
- Van de Weghe, Nico, Lars De Sloover, Anthony Cohn, Haosheng Huang, Simon Scheider, Renée Sieber, Sabine Timpf, and Christophe Claramunt. 2025. “Opportunities and Challenges of Integrating Geographic Information Science and Large Language Models.” JOURNAL OF SPATIAL INFORMATION SCIENCE, no. 30: 93–116. https://doi.org/10.5311/josis.2025.30.389.
- Chicago author-date (all authors)
- Van de Weghe, Nico, Lars De Sloover, Anthony Cohn, Haosheng Huang, Simon Scheider, Renée Sieber, Sabine Timpf, and Christophe Claramunt. 2025. “Opportunities and Challenges of Integrating Geographic Information Science and Large Language Models.” JOURNAL OF SPATIAL INFORMATION SCIENCE (30): 93–116. doi:10.5311/josis.2025.30.389.
- Vancouver
- 1.Van de Weghe N, De Sloover L, Cohn A, Huang H, Scheider S, Sieber R, et al. Opportunities and challenges of integrating geographic information science and large language models. JOURNAL OF SPATIAL INFORMATION SCIENCE. 2025;(30):93–116.
- IEEE
- [1]N. Van de Weghe et al., “Opportunities and challenges of integrating geographic information science and large language models,” JOURNAL OF SPATIAL INFORMATION SCIENCE, no. 30, pp. 93–116, 2025.
@article{01JXF3A61C5GXJZVQSA5FYQGY5,
abstract = {{The integration of large language models (LLMs) with geographic information science (GIScience) represents a new frontier in interdisciplinary research that combines advanced natural language processing with sophisticated spatial data analysis. This paper explores the synergistic potential of combining the natural language understanding and generation capabilities of LLMs with the expertise of GIScience in handling complex geospatial data. By exploring the specific contributions that LLMs can offer to GIScience, such as improving data processing, analysis, and visualization, and the mutual benefits that GIScience can offer to LLMs in terms of spatial reasoning and conceptual frameworks, we outline a comprehensive framework and a research agenda for this integration. Furthermore, we address the societal and ethical implications of this convergence, highlighting the challenges of bias, misinformation, and environmental impact. Through this exploration, we aim to set the stage for innovative applications in urban planning, environmental analysis, and beyond, while emphasizing the need for responsible use of AI.}},
author = {{Van de Weghe, Nico and De Sloover, Lars and Cohn, Anthony and Huang, Haosheng and Scheider, Simon and Sieber, Renée and Timpf, Sabine and Claramunt, Christophe}},
issn = {{1948-660X}},
journal = {{JOURNAL OF SPATIAL INFORMATION SCIENCE}},
keywords = {{large language models (LLMs),geographic information science (GIScience),multimodal data integration,spatial reasoning}},
language = {{eng}},
number = {{30}},
pages = {{93--116}},
title = {{Opportunities and challenges of integrating geographic information science and large language models}},
url = {{http://doi.org/10.5311/josis.2025.30.389}},
year = {{2025}},
}
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