Canopy temperature is an important variable directly linked to a plant’s water status. Recent advances in Unmanned Aerial Vehicle (UAV) and sensor technology provides a great opportunity to obtain high-quality imagery for crop monitoring and high-throughput phenotyping (HTP) applications. In this study, a UAV-based thermal system was developed to directly measure canopy temperature, skipping the traditional radiometric calibration process which is time-consuming and complicates data processing. Raw thermal imagery collected over a cotton field was converted to surface temperature using the Software Development Kit (SDK) provided by the sensor company. Canopy temperature map was generated using Structure from Motion (SfM), and Thermal Stress Index (TSI) was calculated for the test site. UAV temperature measurements were compared to ground measurements acquired by net radiometers and thermocouples. Temperature differences between UAV and ground measurements were less than 5%, and UAV measurements proved to be more stable. The proposed UAV system was successful in showing temperature differences between the cotton genotype. In conclusion, the system described in this study could possibly be used to monitor crop water status in a field setting, which should prove helpful for precision agriculture and crop research.

中文翻译：

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使用安装在无人机（UAV）上的辐射热传感器测量棉冠温度

冠层温度是与植物的水分状况直接相关的重要变量。无人机（UAV）和传感器技术的最新进展为获取高质量图像提供了巨大的机会，可用于作物监测和高通量表型（HTP）应用。在这项研究中，开发了一种基于无人机的热系统来直接测量机盖温度，从而跳过了传统的辐射校准过程，该过程既费时又使数据处理复杂化。使用传感器公司提供的软件开发套件（SDK），将在棉田上收集的原始热图像转换为表面温度。使用“运动结构”（SfM）生成顶篷温度图，并为测试位置计算热应力指数（TSI）。将无人机温度测量值与通过净辐射计和热电偶获得的地面测量值进行比较。无人机和地面测量之间的温差小于5％，并且无人机测量被证明更稳定。拟议的无人机系统成功地显示了棉花基因型之间的温度差异。总之，本研究中描述的系统可能可用于在田间环境中监测作物水的状况，这对精确农业和作物研究应有帮助。