Primary Convener:
Romina Díaz Gómez, Stockholm Environment Institute

Convener:
Antarpreet Jutla, University of Florida
Aditya Kapoor, USDA ARS
Zhenghong Tang, University of Nebraska Lincoln
Marina Mautner, Stockholm Environment Institute
Rimsha Hasan, University of Nebraska Lincoln

Chair:
Marina Mautner, Stockholm Environment Institute
Rimsha Hasan, University of Nebraska Lincoln
Romina Díaz Gómez, Stockholm Environment Institute

Geospatial technologies are revolutionizing the monitoring, modeling, and management of critical water-related ecosystems such as wetlands, rivers, and aquifers. This session invites research that integrates remote sensing (satellite, airborne, UAV), spatial statistics, machine learning, AI, and data assimilation with hydrologic and ecosystem models to address water availability, quality, and ecological health under climate change and human pressures. We particularly welcome studies leveraging high-resolution imagery, cloud platforms like Google Earth Engine, and advanced analytics for mapping wetlands, tracking hydrological dynamics, classifying land cover, and identifying restoration opportunities. Contributions addressing land use change, socio-hydrological interactions, and public health indicators—especially through participatory methods, co-production of knowledge, and open-source, transferable approaches—are encouraged. By bridging technical innovation, ecological conservation, and equitable water governance, this session seeks to foster interdisciplinary dialogue and deliver actionable, AI-driven insights for resilient, just, and climate-adaptive water and ecosystem management.

Index Terms
0480 Remote sensing
0497 Wetlands
1855 Remote sensing
1942 Machine learning

Suggested Itineraries:
Machine Learning and AI

Cross-Listed:
GH - GeoHealth
G - Geodesy
EP - Earth and Planetary Surface Processes

Neighborhoods:
3. Earth Covering