TITLE:
Quantifying Temporal Distortions of Artificial UAV Crop Canopy Temperature Measurements
AUTHORS:
Timothy S. Goebel, James R. Mahan, Paxton Payton, Andrew Young, N. Ace Pugh, Zhanguo Xin, John E. Stout, Robert J. Lascano
KEYWORDS:
Fixed-Infrared Thermometer (Fixed-IRT), Irrigation Treatment, Thermal Distortion
JOURNAL NAME:
Advances in Remote Sensing,
Vol.14 No.2,
June
30,
2025
ABSTRACT: The crop canopy temperature (Tc) measured with fixed-infrared thermometers (IRT’s), provides high-resolution data but only measures small areas of the canopy. Conversely, thermal sensors mounted on UAVs measure Tc over larger areas, overcoming this limitation. However, these measurements may introduce distortions of Tc’s values due to the time of day when they are measured. We measured Tc of a cotton crop over a growing season using fixed-IRTs and compared these measurements to the same data with an assumed time delay of 0.25 - 2 hours. This delay was used as a proxy of Tc values measured with a UAV. The dataset consisted of 7 IRTs measuring 96 values/day over 67 days. Results showed that artificial UAV flight missions resulted in a thermal distortion related to the flight duration. This distortion was applied to detect differences of Tc in seven irrigation treatments. The difference in Tc from the UAV and fixed IRT was affected by the time of day, irrigation treatment, and UAV-flight duration. To identify irrigation treatments, the assumed UAV-Tc produced up to 27% spurious treatment differences relative to the fixed-IRT. Distortion in UAV-Tc was minimal for flights of c data should consider this distortion.