Field-Based Calibration of Unmanned Aerial Vehicle Thermal Infrared Imagery with Temperature-Controlled References. Academic Article uri icon


  • Accurate and reliable calibration methods are required when applying unmanned aerial vehicle (UAV)-based thermal remote sensing in precision agriculture for crop stress monitoring, irrigation planning, and harvesting. The primary objective of this study was to improve the calibration accuracies of UAV-based thermal images using temperature-controlled ground references. Two temperature-controlled ground references were installed in the field to serve as high- and low-temperature references, approximately spanning the expected range of crop surface temperatures during the growing season. Our results showed that the proposed method using temperature-controlled references was able to reduce errors due to ambient conditions from 9.29 to 1.68 C, when tested with validation panels. There was a significant improvement in crop temperature estimation from the thermal image mosaic, as the error reduced from 14.0 C in the un-calibrated image to 1.01 C in the calibrated image. Furthermore, a multiple linear regression model (R2 = 0.78; p-value < 0.001; relative RMSE = 2.42%) was established to quantify soil moisture content based on canopy surface temperature and soil type, using UAV-based thermal image data and soil electrical conductivity (ECa) data as the predictor variables.

published proceedings

  • Sensors (Basel)

author list (cited authors)

  • Han, X., Thomasson, J. A., Swaminathan, V., Wang, T., Siegfried, J., Raman, R., Rajan, N., & Neely, H.

citation count

  • 3

complete list of authors

  • Han, Xiongzhe||Thomasson, J Alex||Swaminathan, Vaishali||Wang, Tianyi||Siegfried, Jeffrey||Raman, Rahul||Rajan, Nithya||Neely, Haly

publication date

  • January 2020