Thermal Imaging Detects Early Drought Stress in Turfgrass Utilizing Small Unmanned Aircraft Systems

Authors

Mu Hong, Kansas State UniversityFollow
Dale J. Bremer, Kansas State UniversityFollow
Deon van der Merwe, GD Animal Health, Deventer, The Netherlands

Keywords

drought stress, drone, thermal imaging, creeping bentgrass fairway, spectral reflectance

Abstract

Plots of fairway-height creeping bentgrass were watered differently to create a gradient of drought stress from severe deficit irrigation to well-watered, under an automatic rainout shelter in Manhattan, KS. Canopy temperature (Tc) measured by a small unmanned aerial system (sUAS) predicted drought stress approximately 5 days or more before drought symptoms were evident in either turfgrass visual quality (VQ) or percentage green cover (PGC). The ability of Tc to predict drought stress was comparable to the best spectral parameters acquired by sUAS on companion flights [i.e., near infrared (NIR) and GreenBlue VI], and slightly better than with spectral data obtained from handheld sensors. Better drought-prediction ability combined with faster data collection using sUAS indicates significant potential for sUAS-based compared with ground-based drought stress monitoring methods.

Recommended Citation

Hong, Mu; Bremer, Dale J.; and van der Merwe, Deon (2019) "Thermal Imaging Detects Early Drought Stress in Turfgrass Utilizing Small Unmanned Aircraft Systems," Kansas Agricultural Experiment Station Research Reports: Vol. 5: Iss. 5. https://doi.org/10.4148/2378-5977.7766