Primary Convener:
Peng Fu, Louisiana State University AgCenter

Convener:
Shawn Serbin, Brookhaven National Laboratory
Carl Bernacchi, University of Illinois Urbana-Champaign

Chair:
Peng Fu, University of Illinois at Urbana Champaign
Shawn Serbin, Brookhaven National Laboratory
Carl Bernacchi, University of Illinois Urbana-Champaign

Imaging spectroscopy (IS) is transforming our ability to monitor agricultural landscapes and environmental systems with unprecedented detail. With the rise of airborne and spaceborne hyperspectral missions (e.g., PRISMA, DESIS, EMIT, EnMAP, PACE, and upcoming SBG), new opportunities have emerged to detect crop stress, soil properties, water quality, vegetation traits, and biogeochemical processes at scale. This session invites contributions that utilize imaging spectroscopy—independently or integrated with other datasets—to advance fundamental science and real-world applications in agricultural and natural systems. We welcome research on algorithm development, functional trait estimation, data fusion, machine learning and AI integration, and the ecological interpretation of hyperspectral signals. Contributions addressing scaling, calibration, uncertainty quantification, and field validation are especially encouraged. By bringing together diverse approaches and disciplines, this session aims to push the frontiers of imaging spectroscopy for sustainable land management, ecosystem monitoring, and climate adaptation.

Index Terms
0402 Agricultural systems
0439 Ecosystems, structure and dynamics
0466 Modeling
0480 Remote sensing

Cross-Listed:
IN - Informatics
GC - Global Environmental Change

Suggested Itineraries:
Machine Learning and AI

Neighborhoods:
3. Earth Covering