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ARS Home » Southeast Area » Gainesville, Florida » Center for Medical, Agricultural and Veterinary Entomology » Mosquito and Fly Research » Research » Publications at this Location » Publication #331296

Research Project: Biting Arthropod Surveillance and Control

Location: Mosquito and Fly Research

Title: Analytical models integrated with satellite images for optimized pest management

Author
item Bright, L
item Handley, Michael
item Chein, Isabel
item Curi, Sebastian
item Brownworth, L
item Bernier, Ulrich - Uli
item Gurman, Pablo
item Elman, Noel

Submitted to: Precision Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/30/2016
Publication Date: 11/20/2016
Citation: Bright, L.Z., Handley, M., Chein, I., Curi, S., Brownworth, L.A., Bernier, U.R., Gurman, P., Elman, N.M. 2016. Analytical models integrated with satellite images for optimized pest management . Precision Agriculture. DOI:https://doi.org/10.1007/s11119-016-9434-0.

Interpretive Summary: Scientists at the USDA-ARS Center for Medical, Agricultural and Veterinary Entomology collaborated with researchers from the Institute for Soldier Nanotechnologies at MIT, the , Instituto Tecnolo´gico de Buenos Aires, Argentina, and the University of Texas-Dallas to evaluate the use of drones to deliver small devices containing insecticides. The purpose of this work is to show that a system can be designed where drones deliver the insecticide containing devices to precise locations as a way to protect people from being bitten by mosquitoes and other pests. The results of this study benefit people at risk of mosquito attack throughout the world, and may be of specific use to researchers and commercial entities that are developing new repellents for personal protection from mosquito attack.

Technical Abstract: The global field protection (GFP) was developed to protect and optimize pest management resources integrating satellite images for precise field demarcation with physical models of controlled release devices of pesticides to protect large fields. The GFP was implemented using a graphical user interface to aid the end-user to select location and define an arbitrary perimeter for protection. The system provides coordinates of drop points for the controlled release devices which can be delivered using drone technology, e.g. unmanned air vehicles. In this work, we present the first proof of concept of this technology. A vast number of pest management applications can benefit from this work, including prevention against vector-borne diseases as well as protection of large agriculture fields.