Evaluating small unmanned aerial systems for detecting drought stress in turfgrass

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dc.contributor.author Hong, Mu
dc.date.accessioned 2019-03-01T15:29:42Z
dc.date.available 2019-03-01T15:29:42Z
dc.date.issued 2019-05-01
dc.identifier.uri http://hdl.handle.net/2097/39434
dc.description.abstract Recent advances in small unmanned aerial systems (sUAS) may provide rapid and accurate methods for turf research and management. The study was to evaluate early drought detection ability of ultra-high resolution remote sensing with sUAS technology, and compare it with traditional techniques on fairway-height ‘Declaration’ creeping bentgrass (Agrostis stolonifera L.) treated from severe deficit to well-watered irrigation (15, 30, 50, 65, 80, and 100% evapotranspiration replacement). Airborne measurements with a modified digital camera mounted on a hexacopter included reflectance from broad bands (near infrared [NIR, 680-780 nm], and green and blue bands [overlapped, 400-580 nm]), from which eight vegetation indices (VIs) were derived for evaluation. Canopy temperature was measured only in the final year with a thermal infrared camera mounted on a drone. Traditional measurements were volumetric water content (VWC), visual quality (VQ), percentage green cover (PGC), and VIs from handheld devices. Declines in VWC in irrigation-deficit treatments were consistently detected by the NIR band and six VIs from sUAS, and NDVI and red band from a handheld device, before drought stress was evident in VQ. These bands and indices predicted drought stress at least one week before symptoms appeared in VQ. Canopy temperature predicted drought stress as early as the best VIs and NIR, 16 days before symptoms appeared in VQ in 2017. Only the NIR and GreenBlue VI [(green-blue)/(green+blue)] consistently predicted drought stress throughout three years. Results indicate using ultra-high resolution remote sensing with sUAS can detect drought stress before it is visible to the human eye and may prove viable for irrigation management on turfgrass. en_US
dc.description.sponsorship United States Golf Association, Kansas Turfgrass Foundation, and Lebanon Turf Inc. en_US
dc.language.iso en_US en_US
dc.subject sUAS en_US
dc.subject remote sensing en_US
dc.subject drought stress en_US
dc.subject creeping bentgrass en_US
dc.subject vegetation index en_US
dc.subject deficit irrigation en_US
dc.title Evaluating small unmanned aerial systems for detecting drought stress in turfgrass en_US
dc.type Thesis en_US
dc.description.degree Master of Science en_US
dc.description.level Masters en_US
dc.description.department Department of Horticulture and Natural Resources en_US
dc.description.advisor Dale Bremer en_US
dc.date.published 2019 en_US
dc.date.graduationmonth May en_US


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