GPT-Enhanced Knowledge Extraction for Earth Engine Models

publications

A GPT-assisted workflow that extracts structured knowledge about geographic analysis models from Google Earth Engine scripts and reuses it to support model construction.

Citation
Liang J., Zhao A., Hou S., Wu H., Jin F. (2024). A GPT-enhanced framework on knowledge extraction and reuse for geographic analysis models in Google Earth Engine. International Journal of Digital Earth, 17(1). doi:10.1080/17538947.2024.2398063

Cover figure: Prompt design and interaction with ChatGPT. From Liang et al. (2024), International Journal of Digital Earth.

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.