%0 Journal Article
%T Quantifying Temporal Distortions of Artificial UAV Crop Canopy Temperature Measurements
%A Timothy S. Goebel
%A James R. Mahan
%A Paxton Payton
%A Andrew Young
%A N. Ace Pugh
%A Zhanguo Xin
%A John E. Stout
%A Robert J. Lascano
%J Advances in Remote Sensing
%P 87-102
%@ 2169-2688
%D 2025
%I Scientific Research Publishing
%R 10.4236/ars.2025.142006
%X The crop canopy temperature (T<sub>c</sub>) measured with fixed-infrared thermometers (IRT&#8217;s), provides high-resolution data but only measures small areas of the canopy. Conversely, thermal sensors mounted on UAVs measure T<sub>c</sub> over larger areas, overcoming this limitation. However, these measurements may introduce distortions of T<sub>c</sub>&#8217;s values due to the time of day when they are measured. We measured T<sub>c</sub> 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 T<sub>c</sub> 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 T<sub>c</sub> in seven irrigation treatments. The difference in T<sub>c</sub> 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-T<sub>c</sub> produced up to 27% spurious treatment differences relative to the fixed-IRT. Distortion in UAV-T<sub>c</sub> was minimal for flights of &lt;15-minutes. Interpretation of UAV-T<sub>c</sub> data should consider this distortion.
%K Fixed-Infrared Thermometer (Fixed-IRT)
%K Irrigation Treatment
%K Thermal Distortion
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=143706