The methods of data collection and analysis for soil moisture monitoring using drone remote sensing

One, Introduction

　　With the intensification of global climate change, soil moisture has become an important factor affecting crop growth, agricultural yield, and food security. Therefore, the monitoring of soil moisture has become particularly important. Traditional soil moisture monitoring methods have the disadvantages of high equipment cost, complex operation, and limited coverage. The emergence of drone remote sensing technology has provided a new way for soil moisture monitoring. This paper discusses the data collection and analysis methods of drone remote sensing in soil moisture monitoring.

Two, Data collection of drone remote sensing in soil moisture monitoring

Drone selection: Choose drones with high resolution and high precision, such as multi-rotor drones or fixed-wing drones. The flight altitude, flight speed, flight path, and flight time of the drones need to be set according to actual needs.

Data acquisition: Use high-resolution sensors (such as multispectral, hyperspectral, thermal infrared, etc.) carried by drones to scan the ground to obtain multi-dimensional data such as soil moisture, vegetation coverage, and surface temperature.

Data preprocessing: Preprocess the data obtained by drones, including image correction, radiation correction, and atmospheric correction, to improve the accuracy of the data.

Three, Data analysis of drone remote sensing in soil moisture monitoring

Data fusion: Multi-source remote sensing data obtained by drones, such as multi-spectral data and hyperspectral data, are fused to obtain more comprehensive soil moisture information.

Model establishment: Based on the theoretical model of soil moisture monitoring, a soil moisture prediction model is established. Regression models, neural network models, and support vector machine models can be used.

Soil moisture prediction: By using models to predict the soil moisture data obtained by drones, it is possible to evaluate the trend and spatial distribution of soil moisture changes.

Soil moisture monitoring: By using drone remote sensing, it is possible to obtain real-time soil moisture information, detect abnormal areas of soil moisture in a timely manner, and provide scientific basis for agricultural irrigation and fertilization.

Four, Applications of drone remote sensing in soil moisture monitoring

Agricultural irrigation: By using the data of soil moisture monitored by drones, precise irrigation can be achieved, avoiding waste of water resources and improving the efficiency of agricultural irrigation.

Agricultural fertilization: By using the data of soil moisture monitored by drones, precise fertilization can be achieved, avoiding waste of fertilizers and improving agricultural yield and quality.

Disaster monitoring: By using the data of soil moisture monitored by drones, it is possible to detect abnormal areas of soil moisture in a timely manner, providing scientific basis for disaster early warning and emergency response.

Five, Conclusion

Remote sensing of soil moisture by drones has the advantages of fast data collection, wide coverage, simple operation, and low cost, making it an important means for soil moisture monitoring. In the future, with the continuous development and progress of drone remote sensing technology, the role of drone remote sensing in monitoring soil moisture will be even greater, providing strong support for agricultural production and food security.