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Updated: Apr 26, 2026

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
Published on: February 9, 2024
Airborne transport of herbicides from UAV applications under varied operational and meteorological conditions
Neriya Perez Lapid1, Ran Darzi1, Ran Lati2
1Faculty of Civil and Environmental Engineering, Technion, Israel Institute of Technology, Haifa, 32000, Israel.
Abstract:
The use of unmanned aerial vehicles (UAVs) for agricultural spraying is expanding rapidly worldwide, yet research has not kept pace with technological progress, regulatory frameworks remain limited, and key data gaps hinder the optimization of UAV spray applications. This study quantifies the airborne drift profile and sedimentary drift generated by a commercial UAV under a range of operational and environmental conditions and compares these outcomes with drift from a conventional tractor-mounted boom sprayer. Airborne drift was measured using active air sampling via polyurethane foam (PUF) plugs mounted at multiple heights (between 2 and 8 m) on a mast located 15 m downwind from the sprayed plot. Sedimentary drift was assessed with water-sensitive papers (WSPs) placed on the ground at fixed intervals between the field edge and the mast. In a few cases, additional WSPs were attached to the mast to detect airborne droplets. Three flight speeds (10, 17, and 22 km h-1) and three spray heights (2.5, 4, and 6 m above ground) were tested. Airborne pesticide drift was detected by active sampling in all UAV trials, including cases where impaction or sedimentary drift were minimal or below the detection limit. Drift profiles generally depicted the highest concentrations near the ground and under the fastest and highest flight conditions. Compared to a tractor-mounted boom sprayer, the UAV produced more airborne drift near the ground, but at higher sampling levels, both systems showed comparable amounts. Overall, the combined use of active air sampling and droplet impaction measurements provides robust datasets that can inform and improve best practices for UAV-based pesticide applications.
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