A primary advantage of unmanned aerial vehicle-based imaging systems is responsiveness.  Herbicide drift events require prompt attention from a flexible collection system, making unmanned aerial vehicles a good option for drift analysis.  In April 2015, a drift event was documented on a Mississippi farm.  A combination of corn and rice fields exhibited symptomology consist with non-target injury from a tank mix of glyphosate and clethodim.  An interesting observation was the corn, which was glyphosate-tolerant, was injured only by the clethodim; the rice, which was not glyphosate-tolerant, was mostly injured by the glyphosate.  This provided two different outcomes from a single drift event.  Over 700 acres were impacted, the majority of which was corn.  Injury was apparent six days after application.  In addition to on-the-ground assessments, an unmanned aerial vehicle was used to collect aerial imagery over affected fields on multiple occasions.  Drift plumes were evident in images collected approximately three weeks after application, and in subsequent images; this coincided with peak injury symptomology observed on-ground.  Although plants visually recovered, reduced stands and delayed maturity translated into yield reductions between 16 to 40% based on yield monitor data comparisons from affected vs. unaffected portions of each field; these losses were assigned an economic value based on market prices for corn and rice.  Unmanned aerial vehicle-based imagery enabled a full characterization of injury extent.  These data were coupled to more traditional forms collected by producers to better support their claim of negative impact, and also to rapidly and fully assess the herbicide drift event.  Limitations of the unmanned aerial vehicle were related to tradeoffs between spatial resolution and time to collect.  Because the extent of the damage was quite large, a compromise was necessary to find a spatial resolution which would provide needed information but which could be obtained within a reasonable amount of time.  For a production environment, the issue of battery life and number of batteries necessary to overfly the area become significant.  The application of an unmanned aerial vehicle to this real-world problem resulted in an improved outcome for the producer and more supporting evidence for the insurance company.