Open AccessThermal Imaging Detects Early Drought Stress in Turfgrass Utilizing Small Unmanned Aircraft Systems
Author(s) -
Hong Mu,
Bremer Dale J.,
Merwe Deon
Publication year - 2019
Publication title -
agrosystems, geosciences and environment
Language(s) - English
Resource type - Journals
ISSN - 2639-6696
DOI - 10.2134/age2019.04.0028
Subject(s) - canopy , agrostis stolonifera , remote sensing , environmental science , agrostis , evapotranspiration , thermal infrared , vegetation (pathology) , irradiance , water content , multispectral image , spectral bands , near infrared spectroscopy , atmospheric sciences , infrared , geology , agronomy , biology , optics , ecology , poaceae , medicine , physics , geotechnical engineering , pathology , neuroscience
Core Ideas Canopy temperature via measurements in turfgrass via drones have not been assessed. Rises in canopy temperature were detected before visible drought symptoms. This early detection was similar to top spectral parameters on companion flights. Canopy temperature was closely correlated with spectral data. Recent advances in aerial platforms and thermal imaging provide opportunities to improve water management in turfgrass, but research on this topic is limited. Our objectives were to: (i) evaluate the ability of canopy temperature ( T c ) imaging from small unmanned aircraft systems (sUAS) to detect drought stress early in turfgrass; (ii) compare early drought‐stress detection ability of T c measurements with that of sUAS‐mounted and handheld optical sensors; and (iii) evaluate thermal data's relationship to spectral reflectance from sUAS‐mounted and handheld sensors, soil volumetric water content (VWC), soil temperature, turfgrass visual quality (VQ), and percentage green cover (PGC). The study was conducted during summer 2017 on creeping bentgrass ( Agrostis stolonifera L.) irrigated with 15 to 100% evapotranspiration (ET) replacements to impose a gradient of drought stress. Airborne spectral reflectance measurements included three bands (near infrared [NIR, 680–780 nm], green and blue bands [overlapped, 400–580 nm]) and eight derived vegetation indices. Results indicated T c measurements via the sUAS detected rises of T c in 15 and 30% compared with 100% ET plots, corresponding with declines in VWC, before drought stress became visible. This was comparable to the best spectral parameters on companion flights, and T c was closely correlated with spectral data from sUAS‐mounted (| r | = 0.52–0.69) and handheld sensors (| r | = 0.75–0.82). Thermal data were more strongly correlated with turfgrass VQ ( r = −0.60 to −0.77) and PGC ( r = −0.58 to −0.78) than with VWC ( r = −0.43 to −0.63) and soil temperature (| r | = 0.27–0.41).