2016
Understanding soybeans spatial and temporal variability at the field scale Unmanned Aerial Vehicles (UAVs) and airborne remote sensing imagery
Contributor/Checkoff:
Category:
Sustainable Production
Keywords:
Data analysisData Management
Parent Project:
This is the first year of this project.
Lead Principal Investigator:
Bruno Basso, Michigan State University
Co-Principal Investigators:
Project Code:
1620
Contributing Organization (Checkoff):
Institution Funded:
Brief Project Summary:

Dr. Basso’s group at Michigan State University has been flying an FAA approved UAVs over farmers’ fields with interesting results. In this project the main goal is to fly the drone over field experiments with different imposed or natural treatments ranging from foliar fertilizer response, to diseases detection, weed management, soil spatial variability (pH, depth and topographic positions). We will delineate a protocol to strategically apply the UAV sensors (thermal, laser, and multispectral) to fully exploit the advantages of the most sophisticated and reliable systems to monitor growth of soybean crops throughout the growing season over space and time. We will also assess spatial variability...

Unique Keywords:
#analytical standards & measurements
Information And Results
Final Project Results

The United Soybean Research Retention policy will display final reports with the project once completed but working files will be purged after three years. And financial information after seven years. All pertinent information is in the final report or if you want more information, please contact the project lead at your state soybean organization or principal investigator listed on the project.