Drone thermal imaging technology is widely used in modern agriculture, especially in monitoring crop moisture status. This technology helps farmers identify crop moisture requirements by capturing the temperature distribution on the crop surface, thereby achieving precise irrigation and improving water resource utilization efficiency.
Technical principle
1. Infrared thermal imaging
Infrared thermal imaging technology is a technology that generates images by capturing infrared radiation emitted by objects. All objects emit infrared radiation, and its intensity is proportional to the temperature of the object. Through infrared thermal imaging, images reflecting the temperature distribution on the surface of crops can be generated. These images can show the moisture status of crops, because crops with sufficient water are usually cooler, while crops with insufficient water are hotter.
2. Crop Water Stress Index (CWSI)
The crop water stress index (CWSI) is an important indicator for measuring the moisture status of crops. The calculation formula of CWSI is:
\[
CWSI = \frac{T_c - T_w}{T_d - T_w}
\]
Where, \(T_c\) is the canopy temperature, \(T_w\) is the ground full evaporation reference surface temperature, \(T_d = T_a + 5\) is the leaf temperature when the crop stomata are fully closed, and \(T_a\) is the test dry bulb temperature (i.e. field air temperature). By calculating CWSI, the degree of crop water deficit can be quantified.
Implementation steps
1. Set up auxiliary devices
Set up auxiliary devices in the field, including field air temperature sensors and ground full evaporation reference surfaces. These devices are used to monitor the air temperature in the field and provide reference points for full evaporation in order to calibrate infrared thermal imaging data.
2. Collect infrared images with drones
Large-area infrared images of farmland crops are collected through the infrared thermal imaging system carried by drones. At the same time, the GPS module is triggered synchronously to obtain the positioning information of the corresponding image.
3. Data processing and analysis
The ground data processing system receives infrared images and image positioning information, registers and splices the images, and performs image segmentation on the spliced images to distinguish the canopy, background, and ground sufficient evaporation reference surface. The spatial distribution of canopy temperature and ground sufficient evaporation reference surface temperature is obtained from the canopy image and the ground sufficient evaporation reference surface image respectively. Combined with the air temperature data monitored by the field air temperature sensor, the leaf temperature when the crop stomata are fully closed is estimated, and finally the crop water deficit index (CWSI) is calculated and displayed on the spatial distribution map. The areas where the crop water deficit index value is higher than the critical value are highlighted and warned.
Application advantages
1. Precision irrigation
By monitoring the moisture status of crops, farmers can achieve precise irrigation, avoid over-irrigation or under-irrigation, thereby saving water resources and improving irrigation efficiency.
2. Improve crop yield and quality
Timely detection and treatment of crop water stress problems can help improve crop yield and quality and reduce economic losses caused by insufficient water.
3. Real-time monitoring and early warning
UAV thermal imaging technology can achieve real-time monitoring. Farmers can check the status of farmland at any time through mobile phones or computers and take timely measures to deal with water stress.
Challenges and future prospects
Although UAV thermal imaging technology has shown great potential in monitoring crop moisture, it still faces some challenges. For example, data processing and analysis capabilities need to be further improved to extract useful information from large amounts of data. In addition, climatic conditions and terrain complexity may also affect the flight and monitoring effects of drones.
In the future, with the development of artificial intelligence and big data technology, the data processing and analysis capabilities of UAV thermal imaging technology will be further improved, providing farmers with more accurate decision-making support. At the same time, with the popularization of technology, more small farmers will be able to enjoy the convenience brought by this technology.
