B076
Science and Applications Enabled by Remote Sensing Data Fusion, Time Series Analysis, and AI
Science and Applications Enabled by Remote Sensing Data Fusion, Time Series Analysis, and AI
Session ID#: 250984
Session Description:
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 [BIOGEOSCIENCES]
1640 Remote sensing [GLOBAL CHANGE]
1855 Remote sensing [HYDROLOGY]
Primary Convener: Yun Yang, Cornell University, Soil and Crop Sciences Section, Ithaca, NY, United States
Conveners: Zhe Zhu1, Simon Kraatz2 and Shi Qiu1, (1)University of Connecticut, Department of Natural Resources and the Environment, Storrs, United States(2)USDA ARS, Hydrology and Remote Sensing Laboratory, Beltsville, United States
See more of: Biogeosciences