Soil Moisture Virtual Seminar Series: Using AI and Machine Learning to Improve Soil Moisture Products
Oct7
October 7, 2026
10:30 am – 11:30 am
MT
Location
Virtual
Register Here
Computer models supported by Artificial Intelligence (AI) and machine learning (ML) have greatly improved our ability to combine data measured in the field and modeled soil moisture data, resulting in more reliable soil moisture estimates.
In this virtual seminar, Zachary Hoylman (Montana Climate Office at the University of Montana) and Shrideep Pallickara (Colorado State University) will present their research in this field. They will discuss why these combined soil moisture products are needed, how AI and ML are used in the process, and current insights into the benefits and limits of these new techniques.
This event is part of a virtual soil moisture seminar series co-hosted by theNational Coordinated Soil Moisture Monitoring Network (NCSMMN)in partnership with NOAA’s National Integrated Drought Information System (NIDIS), USDA’s Agricultural Research Service (ARS), and USDA’s Forest Service.
For more information, please contact Elise Osenga (elise.osenga@noaa.gov).
National Oceanic and Atmospheric Administration (NOAA)
Office of Oceanic and Atmospheric Research (OAR)
Climate Program Office (CPO)
National Integrated Drought Information System (NIDIS)
U.S. Department of Agriculture (USDA)
U.S. Forest Service
Colorado State University
Montana Climate Office
