Mr. Ryan C. Phillips Profile

Ryan C. Phillips

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Proceedings Article | 21 April 2020 Presentation + Paper

Assessing crop response to simulated damage utilizing UAS imagery

Ryan Phillips, Jason Ward

Proceedings Volume 11414, 1141403 (2020) https://doi.org/10.1117/12.2560702

KEYWORDS: Unmanned aerial vehicles, RGB color model, Ear, Reflectivity, Sensors, Visualization, Vegetation, Agriculture, Clouds, Sun

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Crop assessment through the use of unmanned aerial systems (UAS) have increased over recent years. More farmers or their service providers have access to their own UAS, although advanced sensors and UAS platforms may not have been widely adopted. Severe tropical weather events, such as hurricanes, can have widespread negative impacts to late-season crops. The timely response necessary to detect and quantify crop damage, has led to the need for farmers and other parties to have a quick and quantifiable method to assess lodging. Most, if not all, UAS users have access to visual band color imagery. Extraction of data from this imagery as different indices and as a digital elevation model creates the opportunity to identify metrics that can detect and quantify crop lodging damage. The goal of this study was to compare multiple vegetative indices which can be calculated from RGB imagery for their ability to detect simulated crop damage. Six indices as well as a digital elevation model were extracted from UAS flights occurring over 4 weeks over a maize field. Lodging was simulated at the root and ear level with new plots being damaged at each week of treatment. Results indicated that none of the indices or extracted data examined in this study would provide information on significant differences among treatments so it would not be advised to use these metrics on their own for detecting or classifying late-season maize lodging.

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