Improving Accuracy of Unmanned Aerial System Thermal Infrared Remote Sensing for Use in Energy Balance Models in Agriculture Applications

• Published in: Remote sensing (Basel, Switzerland) Vol. 13; no. 9; p. 1635
• Main Authors: Maguire, Mitchell S., Neale, Christopher M. U., Woldt, Wayne E.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.05.2021
• Subjects: Accuracy; Aircraft; Artificial neural networks; Atmospheric correction; Atmospheric models; Calibration; Cameras; corn; Emissivity; Energy; Energy balance; FLIR; Heat detection; Infrared cameras; Infrared detectors; Infrared imagery; infrared photography; Infrared signatures; Interference; irrigation; Irrigation water; Laboratories; linear models; Neural networks; Polynomials; Radiometers; Remote sensing; Remote sensors; Sensors; Software; Soybeans; Stability; Surface temperature; Temperature; Temperature measurement; Thermal imaging; thermal infrared; Thermal measurement; thermography; Thermometers; unmanned aerial system (UAS); Unmanned aerial vehicles; Vegetation; Water stress

Unmanned aerial system (UAS) remote sensing has rapidly expanded in recent years, leading to the development of several multispectral and thermal infrared sensors suitable for UAS integration. Remotely sensed thermal infrared imagery has been used to detect crop water stress and manage irrigation by...