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A Genetic Algorithm Procedure for the Automatic Updating of FEM Based on Ambient Vibration Tests
Article

A Calibration Procedure for Field and UAV-Based Uncooled Thermal Infrared Instruments

1
Water Desalination and Reuse Center, King Abdullah University of Science of Technology, Thuwal 23955, Saudi Arabia
2
Discipline of Geography and Spatial Sciences, College of Sciences and Engineering, University of Tasmania, Hobart, TAS 7001, Australia
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(11), 3316; https://doi.org/10.3390/s20113316
Received: 7 May 2020 / Revised: 5 June 2020 / Accepted: 6 June 2020 / Published: 10 June 2020
(This article belongs to the Section Physical Sensors)
Thermal infrared cameras provide unique information on surface temperature that can benefit a range of environmental, industrial and agricultural applications. However, the use of uncooled thermal cameras for field and unmanned aerial vehicle (UAV) based data collection is often hampered by vignette effects, sensor drift, ambient temperature influences and measurement bias. Here, we develop and apply an ambient temperature-dependent radiometric calibration function that is evaluated against three thermal infrared sensors (Apogee SI-11(Apogee Electronics, Santa Monica, CA, USA), FLIR A655sc (FLIR Systems, Wilsonville, OR, USA), TeAx 640 (TeAx Technology, Wilnsdorf, Germany)). Upon calibration, all systems demonstrated significant improvement in measured surface temperatures when compared against a temperature modulated black body target. The laboratory calibration process used a series of calibrated resistance temperature detectors to measure the temperature of a black body at different ambient temperatures to derive calibration equations for the thermal data acquired by the three sensors. As a point-collecting device, the Apogee sensor was corrected for sensor bias and ambient temperature influences. For the 2D thermal cameras, each pixel was calibrated independently, with results showing that measurement bias and vignette effects were greatly reduced for the FLIR A655sc (from a root mean squared error (RMSE) of 6.219 to 0.815 degrees Celsius (℃)) and TeAx 640 (from an RMSE of 3.438 to 1.013 ℃) cameras. This relatively straightforward approach for the radiometric calibration of infrared thermal sensors can enable more accurate surface temperature retrievals to support field and UAV-based data collection efforts. View Full-Text
Keywords: thermal infrared camera; calibration; vignetting; UAV; agricultural monitoring; Apogee SI-111; FLIR A655sc; TeAx 640; Tau 2; RPAS thermal infrared camera; calibration; vignetting; UAV; agricultural monitoring; Apogee SI-111; FLIR A655sc; TeAx 640; Tau 2; RPAS
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MDPI and ACS Style

Aragon, B.; Johansen, K.; Parkes, S.; Malbeteau, Y.; Al-Mashharawi, S.; Al-Amoudi, T.; Andrade, C.F.; Turner, D.; Lucieer, A.; McCabe, M.F. A Calibration Procedure for Field and UAV-Based Uncooled Thermal Infrared Instruments. Sensors 2020, 20, 3316. https://doi.org/10.3390/s20113316

AMA Style

Aragon B, Johansen K, Parkes S, Malbeteau Y, Al-Mashharawi S, Al-Amoudi T, Andrade CF, Turner D, Lucieer A, McCabe MF. A Calibration Procedure for Field and UAV-Based Uncooled Thermal Infrared Instruments. Sensors. 2020; 20(11):3316. https://doi.org/10.3390/s20113316

Chicago/Turabian Style

Aragon, Bruno; Johansen, Kasper; Parkes, Stephen; Malbeteau, Yoann; Al-Mashharawi, Samir; Al-Amoudi, Talal; Andrade, Cristhian F.; Turner, Darren; Lucieer, Arko; McCabe, Matthew F. 2020. "A Calibration Procedure for Field and UAV-Based Uncooled Thermal Infrared Instruments" Sensors 20, no. 11: 3316. https://doi.org/10.3390/s20113316

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