Database Research Summaries2018 Low Altitude Plant Sensing on Unmanned Aerial Vehicle with a Hyperspectral Imager for Detection of Glyphosate-Resistant Weeds in Soybean Fields
The focus of this research is to develop UAV-based hyperspectral remote sensing techniques for rapid, consistent, and accurate differentiation between naturally grown GR and GS weeds in soybean fields.
- Determine the optimal flight altitude to best characterize the hyperspectral reflectance properties of GR and GS weeds in soybean fields
- Classify GR and GS weeds from the hyperspectral data acquired from soybean fields.
- Map the distribution of GR and GS weeds in soybean fields based on the results of classification.
- Evaluate technical and economic feasibilities of UAV-imaging systems for detection of GR and GS weeds in practical soybean production
Results will be updated once the research project is complete
This research will assist farmers in getting better yields with fewer weeds.
For more information about this research project, please visit the National Soybean Checkoff Research Database.
Funded in part by the soybean checkoff.