AI & Environmental Science

Scheduled: 22. 09. to 23. 09. 2025

This session explores the rapidly evolving role of artificial intelligence (AI) in advancing environmental studies. We invite respective contributions covering all branches of Earth System sciences and related technologies. This session aims  to map how AI methods—ranging from machine learning and deep learning to hybrid physical–data-driven approaches—are advancing the understanding, monitoring, and prediction of complex environmental systems. By improving the accuracy and timeliness of forecasts,  AI has already been shown to offer critical support for informed decision-making, risk management, and policy development. Ultimately, advancing our understanding through AI not only deepens scientific insight but also strengthens public safety and resilience in the face of climate change. Topics may include, but are not limited to, AI-based weather and climate forecasting, flood and drought prediction, aquatic ecosystems modeling, ocean state reconstruction, crop yield modeling, urban health, urban water management, nature-based solutions modelling and optimization, sensing technologies and biodiversity monitoring. The session aims to foster interdisciplinary dialogue on methodological innovation, data integration, model interpretability, and the responsible use of AI in support of sustainable environmental decision-making. The event will take place from September 22 to 23, 2025.

Use a text editor of your choice to compile your abstract: title, author(s), affiliation(s) of author(s), and abstract text. Your abstract should have 1-4 pages in LNCS format (https://resource-cms.springernature.com/springer-cms/rest/v1/content/19242230/data/v17). Use the abstract submission link at the chosen session website. Please keep in mind that submission of the same abstract to more than one session is not allowed and duplicates will be rejected.