GeoColab: Multi-Agent Collaboration for Geospatial Code
Coordinates role-specialised LLM agents in a collaborative workflow that decomposes, writes, reviews and refines geospatial code.
Citation
Wu H., Jiao H., Hou S., Liang J., Shen Z., Zhao A., et al. (2025). GeoColab: an LLM-based multi-agent collaborative framework for geospatial code generation. International Journal of Digital Earth, 18(2). doi:10.1080/17538947.2025.2569405
Cover figure: Concept of the GeoColab multi-agent system. From Wu et al. (2025), International Journal of Digital Earth.
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.