GeoCode-GPT: A Large Language Model for Geospatial Code
Fine-tunes an open LLM on purpose-built geospatial code corpora for pretraining, instruction tuning and evaluation, giving a model specialised in generating geospatial code.
Citation
Hou S., Shen Z., Zhao A., Liang J., Gui Z., Guan X., Li R., Wu H. (2025). GeoCode-GPT: a large language model for geospatial code generation. International Journal of Applied Earth Observation and Geoinformation, 104456. doi:10.1016/j.jag.2025.104456
Cover figure: Technical workflow of GeoCode-GPT. From Hou et al. (2025), International Journal of Applied Earth Observation and Geoinformation.
Authors
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.