PICO
Recent advances in Large Language Models (LLMs) and Natural Language Processing (NLP) are rapidly changing geosciences research, offering new opportunities for knowledge discovery, data analysis, and real-time monitoring. At the same time, the increasing availability of digital text and image data—from scientific literature and newspaper articles to social media and historical archives—offers unprecedented opportunities to explore new data sources in geosciences research.
This session examines how geoscientists are using LLMs, NLP, and text-as-data approaches across various hydrology, natural hazards research, and the broader earth system sciences research fields. We invite contributions that showcase innovative uses of LLMs and NLP, discuss methodological challenges, or integrate text mining techniques into geoscientific workflows.
We particularly welcome submissions on topics including, but not limited to:
- Chatbots and AI assistants in geosciences
- Assessment of natural hazard impacts (e.g., floods, droughts, landslides, heatwaves, windstorms)
- Real-time disaster monitoring and early warning systems
- Evidence synthesis and literature mapping
- Public sentiment and perception analysis
- Policy tracking and narrative analysis
- Social media analyses
- Enhancement of metadata and data descriptions
- Automation of historical data rescue
- Integration of LLMs with remote sensing or image data
- Methodological challenges in using LLMs and NLP-based analyses, including bias, reproducibility, and interpretability
By sharing case studies, technical developments, and lessons learned, we aim to promote the effective use of these tools while also highlighting the challenges that newcomers may encounter, including issues with data coverage, quality control, and concerns about reproducibility. By sharing best practices, this session aims to inspire collaboration and innovation in harnessing LLMs, NLP, and text-as-data in geosciences.