Semantic-Driven Geospatial Modeling Knowledge Graph

publications

Designs a geospatial modeling knowledge graph whose entities and relations are extracted with LLMs, supporting semantic retrieval and recommendation of modeling knowledge.

Citation
Liang J., Hou S., Zhao A., Xu Q., Xiang L., Li R., Wu H. (2025). Design and application of a semantic-driven geospatial modeling knowledge graph based on large language models. Geo-spatial Information Science. doi:10.1080/10095020.2025.2483884

Cover figure: Overview of the co-augmentation framework. From Liang et al. (2025), Geo-spatial Information Science.

Knowledge Graphs LLM
Anqi Zhao
Authors
Anqi Zhao
PhD Student in Geospatial AI
I am a PhD student at the Chair of Cartography and Visual Analytics at the Technical University of Munich, supervised by Prof. Liqiu Meng and mentored by Prof. Yu Feng. I came to AI from maps. I studied geodesy, cartography and GIS at Wuhan University, where I first used language models to make sense of geospatial code, and I now spend most of my time on the AI side of GeoAI. Besides research, I supervise Master’s students and maintain open learning resources on LLM agents and web scraping.