127-3 Early Observations of Using UAS Images to Evaluate Durum and Spring Wheat Responses to N Fertilization in the Northern Great Plains.
Poster Number 321
See more from this Division: ASA Section: Climatology & Modeling
See more from this Session: Agricultural Remote Sensing: II
Monday, November 16, 2015
Minneapolis Convention Center, Exhibit Hall BC
Abstract:
Agriculture is considered by far the largest market for Unmanned Aircraft Systems (UAS) in the US, at least 10 times larger than the second one. As mandate by the Congress, FAA announced in 2013 a list of six UAS test sites in US. The Northern Plains UAS Test Site was the first one to become operational (April 2014), when it started flying a Dragonflyer X4ES small UAS. The main goal of the flights was to show that sensors mounted on an UAS can be used to assess different aspects related to crop production (weeds, stand counting, nutritional status). The goal of this study was to verify how NDVI values calculated from images taken with an UAS compare to NDVI values collected with a handheld sensor (GreenSeeker) in two wheat trials (durum and spring wheat) fertilized with 0, 50, 100, 150, and 200 lbs N/ac. The plot mean NDVI values for the UAS images were extracted from the images using ArcGis 10.2. There was good agreement between UAS and GreenSeeker NDVI values for the two crops, and that relationship was improved by considering the crop individually. The correlation between the NDVI values and N rates for durum showed a linear response for both UAS and GreenSeeker NDVI, while spring wheat showed a quadratic response for both sensors. NDVI values were a better yield predictor for durum than for spring wheat. The sensor mounted in the UAS was able to capture the differences in response of spring wheat and durum to N rates and they were in concordance with data collected by the GreenSeeker sensor. More studies are necessary to confirm our initial findings and to develop a product to assist wheat growers with N fertilizer management during the growing season.
See more from this Division: ASA Section: Climatology & Modeling
See more from this Session: Agricultural Remote Sensing: II