Day 4

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Paper title Simulation of Factors Influencing Temperature Measurements from Miniaturized Thermal Infrared (TIR) Cameras: a Laboratory-based Approach
Authors
  1. Quanxing Wan Wageningen UR Speaker
  2. Benjamin Brede Wageningen University
  3. Magdalena Smigaj Wageningen UR
  4. Lammert Kooistra Wageningen UR
Form of presentation Poster
Topics
  • C4. HAPs/UAVs
    • C4.01 Innovative UAV applications
Abstract text [Background]
The workflow for estimating the surface temperature in agricultural fields from multiple sensors needs to be optimized upon testing each type of sensor’s actual user performance. In this sense, readily available miniaturized UAV-based thermal infrared (TIR) cameras can be combined with proximal sensors in measuring the surface temperature. Before these types of cameras can be operationally used in the field, laboratory experiments are needed to fully understand their capabilities and all the influencing factors.
[Research Objectives]
The primary goal of the research is to explore the feasibility of applying different types of miniaturized TIR cameras to field practices requiring high accuracy, such as crop water stress mapping. The controlled-environment experiment results will be used to put forward practical recommendations towards the design of field tests, for obtaining high-precision in field measurements.
Specifically, the influence of the intrinsic characteristics of the TIR camera on the accurate temperature measurement has been tested based on the following research questions: a. How long does it take for the miniaturized TIR cameras to stabilize after being switched on? b. How does the periodic process of non-uniformity correction (NUC) affect the temperature measurements? c. To what extent can we explain the variation within the response across TIR imagery? d. Will changes in sensor temperature have a significant impact on the measured temperature values of the UAV-mounted and handheld TIR cameras? Besides, the influence of environmental factors has also been tested: e. Will the measuring distance have a strong effect on the measured temperature values of UAV-mounted and handheld TIR cameras? f. How do changes in wind and radiation affect the temperature measured by a UAV-mounted TIR camera?
[Methods]
For this study, we used two radiometric TIR cameras designed specifically for the use on a UAV (WIRIS 2nd GEN and FLIR Tau 2), and two handheld cameras only for reference measurements on the ground (FLIR E8-XT and NEC Avio S300SR). All of these miniaturized TIR cameras used a core equipped with a vanadium oxide (VOx) microbolometer focal plane array (FPA), and their working principle was comparable to that of other camera models. Therefore, the practices using these cameras are of significant reference to the tests with other models.
The main research method is to design a series of experiments by controlling variables in a laboratory environment to determine the influence of the ambient environment and the TIR camera's intrinsic characteristics on the accuracy of temperature measurement. Upon all the key parameters and environmental factors being adjusted and quantified, the experimental design of the field tests can be optimized by evaluating the laboratory results.
Five experiments have been conducted for testing the response characteristics of TIR sensors to thermal radiation signals. Two of the experiments were used to explore the influence of the intrinsic characteristics of TIR cameras on the temperature measurements: (a) assessing the stabilization time of TIR cameras, (b) generating calibration curves by measuring the cameras’ responses to different sensor temperatures, indirectly achieved by adjusting the ambient temperature. (c) assessing sensor’s fixed-pattern noise and/or vignetting effects of cameras. The remaining sessions aimed to explain the influence of ambient environmental factors on accurate measurements: (d) the effect of the change in the thickness of the atmospheric layer between the sensor and the target on the measured temperature, caused by the distance variation between the camera and the blackbody, (e) assessing wind and heating effects on temperature outputs of cameras. All sub-experiments in this research used two blackbody calibrators with fixed temperatures of 35 °C and 55 °C to compare the performance of adopted cameras against the target objects.
[Results and Conclusions]
The laboratory experiments in a climate room suggest that the duration of the warm-up period may vary among different models. However, a half-hour for handheld cameras and one hour for UAV-mounted cameras can guarantee acceptable measurement accuracy afterward already. During measurements, automatic NUC’s influence on measurement accuracy should not be neglected. It is recommended to contact the manufacturers for understanding the NUC’s effects based on the differences between the factory calibration and user tests. To diminish the effect of noises in the measured signal, it is recommended to apply signal processing knowledge. Concerning the influence of the cameras’ intrinsic characteristics, the variation in sensor temperature and vignetting effects in images both have negative influences on the measurement accuracy. According to the results in wind and radiation tests and distance tests, ambient environmental influencing factors which occur in field tests should also be counted in the experimental design. The measurement uncertainty may expand to several degrees if these factors are not considered. In noise compensation experiments, pixels toward to edge of the sensors record lower-than-average values while those towards the center record higher-than-average values because of the vignetting effects. Further experiments in fields are needed to exclude the influence of uneven heat distribution over the surface of the blackbody.