Managing Global Resources for a Secure Future

2017 Annual Meeting | Oct. 22-25 | Tampa, FL

197-2 Application of UAS in Precision Agriculture.

See more from this Division: ASA Section: Climatology and Modeling
See more from this Session: Symposium--the Future of Remote Sensing for Agriculture: How This Information Can be Effectively Used for Decision Making

Tuesday, October 24, 2017: 9:25 AM
Tampa Convention Center, Room 5

E. Raymond Hunt Jr., Hydrology and Remote Sensing Lab, USDA-ARS, Beltsville, MD and Craig S. T. Daughtry, 10300 Baltimore Ave, USDA-ARS, Beltsville, MD
Abstract:
Remote sensing from unmanned aircraft systems (UAS) were expected to be an important new technology to assist farmers for crop nutrient management and precision agriculture. However, a USDA Economic Research Report showed that only about 20% of farmers adopted variable rate applicators, so most farmers in the USA do not have the technology to benefit from UAS remote sensing. There have been three recent developments that distinguish remote sensing with UAS platforms from manned aircraft platforms: (1) even smaller pixel sizes, (2) incident light sensors for image calibration, and (3) structure-from-motion point clouds. These developments hold promise for future data products. We generalize application of UAS into three modes of action: (1) scouting for problems, (2) monitoring to prevent yield losses, and (3) planning crop prescriptions. The three different modes have different requirements for sensor calibration and accuracy, and thus different costs of operation. Planning crop prescriptions may have the most environmental benefits, but the economic benefits are unknown. New technologies are available for UAS to monitor crops for weeds, pests and diseases, but different methods of data acquisition are necessary to reduce acquisition and analysis costs to make crop monitoring profitable.

See more from this Division: ASA Section: Climatology and Modeling
See more from this Session: Symposium--the Future of Remote Sensing for Agriculture: How This Information Can be Effectively Used for Decision Making