Abstract
Unmanned aerial vehicles (UAV) are widely used as remote sensing platforms to effectively monitor agricultural conditions. The wind field generated by the rotors in low-altitude operations will cause the deformation of rice crops, and may affect the acquisition of the true spectral information. In this study, a low-altitude UAV remote sensing simulation platform and a triple-direction wind field wireless sensor network system were built to explore the wind field distribution law. Combined with the multi-spectral images of the rice canopy, the influence of wind field on the spectral information acquisition was analyzed through variance and regression analysis. The results showed that the Z-direction wind field of UAV rotors dominated along three directions (X, Y, and Z). The coefficient of determination (R2) of three linear regression models for Normalized Difference Vegetation Index (NDVI), Ratio Vegetation Index (RVI), and Canopy Coverage Rate (CCR) was 0.782, 0.749, and 0.527, respectively. Therefore, the multi-rotor UAV wind field had an impact on the spectral information acquisition of rice canopy, and this influence could eventually affect the assessment of rice growth status. The models established in this study could provide a reference for the revised model of spectral indices, and offer guidance for the actual operations of low-altitude multi-rotor UAV.
Highlights
The advantages of low cost, high efficiency, and being environment-friendly make small Unmanned aerial vehicles (UAV) widely used in agriculture, especially for agricultural UAV remote sensing [1,2,3]
Combing with advance spectral imaging technique [4,5], agricultural UAV remote sensing can monitor farm crop growth in real time, generating a farmland crop prescription map based on high-resolution spectral images, which plays an important role in monitoring crop growth
The wind field of the F450 quadrotor UAV at different hovering heights was measured by a triple-direction wind field wireless sensor network system
Summary
The advantages of low cost, high efficiency, and being environment-friendly make small UAVs widely used in agriculture, especially for agricultural UAV remote sensing [1,2,3]. Low-altitude remote sensing operations are bound to affect the ground crops because of the rotor wind field. The UAV rotor wind field [6,7,8,9,10] is formed by the rotation of the rotor to promote the air flow in the crop canopy. Li et al [12] designed a method for simulating and measuring an atmospheric wind field with simple equipment by using the modulation characteristics of a semiconductor laser and the high spectral resolution Fabry-Perot interferometer, which can effectively analyze and evaluate the Doppler wind speed measurement principle, data processing method, system performance, and measurement error. The wind speed parameter acquisition system comprised an air speed sensor array and a wind speed data receiving end placed near the canopy of the field crop. The wind speed sensor array could sequentially transmit the collected wind speed values to the receiving end, and transmit these to the ground station for further processing
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