Primary Convener:
Yun Yang, Cornell University

Convener:
Zhe Zhu, University of Connecticut
Shi Qiu, University of Connecticut
Martha Anderson, USDA ARS

Early Career Convener:
Shi Qiu, Texas Tech University

Chair:
Yun Yang, University of Maryland College Park
Martha Anderson, USDA ARS
Zhe Zhu, University of Connecticut
Shi Qiu, Texas Tech University

The recent development of data fusion, time series analysis, and artificial intelligence (AI) creates new science and applications in fields such as climate-smart agriculture, natural resources management, and urban management. The fused time series data provides critical information for more productive and sustainable production and conservation in agricultural practices. Similarly, data fusion, time series analysis, and AI have made sustainable management of natural resources and cities possible. We have witnessed continuous successes in crop monitoring, yield prediction, land cover and land use change detection, forest resilience assessment, urban/suburban characterization, coastal wetland mapping, understory species and change detection, and more. This session will focus on showcasing methodologies and applications for the use of data fusion, time series analysis and AI. We invite you to share findings and discuss how science and technology advancements will contribute to sustainable agriculture, natural resources, and urban systems.

Index Terms
0480 Remote sensing
1640 Remote sensing
1855 Remote sensing

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

Neighborhoods:
3. Earth Covering