Primary Convener:
Sheng Wang, University of Illinois at Urbana-Champaign

Convener:
Sherrie Wang, Massachusetts Institute of Technology
Jillian Deines, Stanford University
Kaiyu Guan, University of Illinois Urbana-Champaign

Chair:
Sheng Wang, Key Laboratory of Water Cycle and Related Land Surfaces, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science
Sherrie Wang, Stanford University
Jillian Deines, Stanford University
Kaiyu Guan, University of Illinois Urbana-Champaign

Sustainable agriculture faces the challenges of lacking scalable solutions and sufficient data for monitoring plant characteristics, environmental conditions, and management practices. Remote sensing from spaceborne, unmanned/manned airborne, and proximal sensors provides unprecedented data sources for agriculture monitoring across scales. The synergy of hyperspectral, multispectral, thermal, LiDAR, or microwave data can thoroughly identify crop stress and predict agroecosystem productivity with ecosystem modeling. This session welcomes a wide range of contributions on remote sensing for sustainable agriculture including, but not limited to: (1) the development of novel sensing instruments and technologies; (2) the quantification of ecosystem energy, carbon, water, and nutrient fluxes across spatial and temporal scales; (3) the applications of machine learning, radiative transfer modeling, or their hybrid; (4) the integration of remotely sensed plant traits to assess agroecosystem functioning and services; and (5) remote sensing to advance nature-based solutions in agriculture for climate change mitigation.

Index Terms
0402 Agricultural systems
1615 Biogeochemical cycles, processes, and modeling
1813 Eco-hydrology
1988 Temporal analysis and representation

Cross-Listed:
IN - Informatics
A - Atmospheric Sciences
B - Biogeosciences
H - Hydrology

Suggested Itineraries:
Climate Change and Global Policy
Biochemistry
Machine Learning and AI
Open Science and Open Data
Global Impacts‚ Solutions‚ & Policies

Co-Organized Sessions:
Atmospheric Sciences

Neighborhoods:
3. Earth Covering