GEE-OPs: Operator Knowledge Base for Earth Engine Code

publications

Mines operator call relationships from Earth Engine scripts with syntax-tree parsing and frequent-pattern analysis, forming a knowledge base that improves LLM code generation.

Citation
Hou S., Liang J., Zhao A., Wu H. (2025). GEE-OPs: an operator knowledge base for geospatial code generation on Google Earth Engine powered by large language models. Geo-spatial Information Science. doi:10.1080/10095020.2025.2505556

Cover figure: Framework for constructing the GEE-OPs knowledge base. From Hou et al. (2025), Geo-spatial Information Science.

LLM Knowledge Graphs
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.