Primary Convener:
Nasrin Alamdari, Florida State University

Convener:
Elmira Hassanzadeh, Polytechnique Montreal
Marzieh Azarderakhsh, The City University of New York
Dongmei Feng, University of Cincinnati

Chair:
Nasrin Alamdari, Florida State University
Elmira Hassanzadeh, Polytechnique Montreal

In the face of climatic and anthropogenic changes, there is an urgent need for innovative approaches to enhance our ability to monitor and manage freshwater resources. The integration of remote sensing and Artificial Intelligence (AI) is a promising approach for water quality monitoring, which is critical for ecosystem health, public safety, and economic resilience. This session invites papers that explore the innovative application of remote sensing and AI in water quality assessment, focusing on their ability to provide comprehensive information. We welcome a wide range of research that includes the development and application of remote sensing and AI models, as well as machine learning algorithms—including shallow machine learning methods for predictive analysis, trend identification, and water quality management under current and changing conditions. Interdisciplinary studies involving socio-economic impacts of water quality, policy and management implications, advancements in sensor technology, and economic analysis of water quality management are also invited.

Index Terms
1847 Modeling
1855 Remote sensing
1871 Surface water quality
1879 Watershed

Suggested Itineraries:
Climate Change and Global Policy
Machine Learning and AI

Neighborhoods:
3. Earth Covering