Location: Water Management and Systems Research
Project Number: 3012-13210-001-013-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Apr 3, 2023
End Date: Mar 31, 2025
To improve the understanding of physiological responses of crop plants to drought and water stress using multi-source remote sensing data and advanced machine learning (ML) algorithms in semi-arid regions.
Data will be collected from USDA-ARS research farms in Greeley (Limited irrigation research farm, LIRF) and Akron (dryland) Colorado. LIRF corn crops are managed with different irrigation levels at different management scales. Proposed imagery datasets will be taken from both satellite and unmanned aerial vehicle (UAV) platforms. A set of ground-based measurements, including plant growth parameters, soil moisture, IRT thermometer, sap flow, solar-induced fluorescence (SIF), and an eddy, covariance (EC) tower, will also be collected in the summer growing season of each year. The collaborator will start with LIRF data from the past to explore the capability of different types of remote sensing data or combinations for monitoring crop growth and predicting crop water stress. The collaborator and ARS PI will work together to examine and develop the linkages between crop physiological and remote sensing measurements of crop water stress and crop yield.