An autonomous GIS agent framework for geospatial data retrieval
Powered by the emerging large language models (LLMs), autonomous geographic information system (GIS) agents can perform spatial analyses and cartographic tasks. However, a research gap exists in enabling these agents to autonomously discover and retrieve the necessary data for spatial analysis. This...
Saved in:
| Main Authors: | Huan Ning, Zhenlong Li, Temitope Akinboyewa, M. Naser Lessani |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-08-01
|
| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2025.2458688 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
GIS Copilot: towards an autonomous GIS agent for spatial analysis
by: Temitope Akinboyewa, et al.
Published: (2025-08-01) -
LLMAGENTNET: A COLLABORATIVE NETWORK OF AUTONOMOUS AI AGENTS FOR COMPLEX TASK EXECUTION
by: А. Р. Бідочко, et al.
Published: (2025-06-01) -
Leveraging Retrieval-Augmented Generation for Automated Smart Home Orchestration
by: Negin Jahanbakhsh, et al.
Published: (2025-04-01) -
Dual retrieving and ranking medical large language model with retrieval augmented generation
by: Qimin Yang, et al.
Published: (2025-05-01) -
Assessing Building Seismic Exposure Using Geospatial Technologies in Data-Scarce Environments: Case Study of San José, Costa Rica
by: Javier Rodríguez-Saiz, et al.
Published: (2025-06-01)