Optimizing UAV-based uncooled thermal cameras in field conditions for precision agriculture

Abstract

Unoccupied aerial vehicles (UAVs) equipped with thermal cameras show great promise for precision agriculture, but challenges persist in analyzing land surface temperature (LST). This study explores the influence of ambient environmental conditions and intrinsic characteristics of uncooled thermal cameras on the accuracy of temperature measurements obtained through UAV-based thermal cameras. The research utilized DJI Matrice 210 quad-rotor UAVs equipped with FLIR Tau 2 and WIRIS 2nd Gen thermal cameras. The experimental design involved strategically selected temperature reference materials of diverse compositions. UAV flights were conducted at varying altitudes, capturing thermal images correlated with ground-based thermocouple measurements. Results indicate that increasing flight altitude resulted in underestimated temperatures measured by UAVs for objects with higher kinematic temperatures, while objects with lower temperatures displayed higher measurements. The study integrates multiple environmental metrics, illustrating the complex influence of air temperature, humidity, net radiation, and wind speed on temperature measurements, with variations observed between FLIR Tau 2 and WIRIS 2nd Gen camera models. Linear regression models highlight the diverse impact of these metrics on UAV-based temperature observations. Furthermore, an analysis of uncooled thermal sensor characteristics reveals a correlation between UAV-measured temperatures and the focal plane array (FPA) temperature, emphasizing the importance of considering intrinsic sensor dynamics. These findings provide valuable insights for enhancing the reliability of UAV-based thermal measurements in agricultural and environmental monitoring. The research underscores the necessity for a comprehensive understanding of both ambient conditions and camera-model-specific dynamics to optimize thermal imaging accuracy for precision agriculture applications. Accordingly, the recommended procedures have been described to reduce the effect of identified sources of influence.

Keywords

• UAV
• Uncooled thermal camera
• Calibration
• Land surface temperature
• Sensor temperature
• Ambient environment