Abstract
In view of the demand for a low-cost, high-throughput method for the continuous acquisition of crop growth information, this study describes a crop-growth monitoring system which uses an unmanned aerial vehicle (UAV) as an operating platform. The system is capable of real-time online acquisition of various major indexes, e.g., the normalized difference vegetation index (NDVI) of the crop canopy, ratio vegetation index (RVI), leaf nitrogen accumulation (LNA), leaf area index (LAI), and leaf dry weight (LDW). By carrying out three-dimensional numerical simulations based on computational fluid dynamics, spatial distributions were obtained for the UAV down-wash flow fields on the surface of the crop canopy. Based on the flow-field characteristics and geometrical dimensions, a UAV-borne crop-growth sensor was designed. Our field experiments show that the monitoring system has good dynamic stability and measurement accuracy over the range of operating altitudes of the sensor. The linear fitting determination coefficients (R2) for the output RVI value with respect to LNA, LAI, and LDW are 0.63, 0.69, and 0.66, respectively, and the Root-mean-square errors (RMSEs) are 1.42, 1.02 and 3.09, respectively. The equivalent figures for the output NDVI value are 0.60, 0.65, and 0.62 (LNA, LAI, and LDW, respectively) and the RMSEs are 1.44, 1.01 and 3.01, respectively.
Highlights
Real-time, non-destructive, and high-throughput acquisition of crop-growth information is the most important requirement for precision management of crop production
The results show that, method to extract classification informationand of crops of different types from high-resolution images using the method to extract classification information of crops of different types from high-resolution collected by unmanned aerial vehicle (UAV) presents high accuracy and universality
We present a new UAV-borne crop-growth monitoring system based on research achievements of the Nanjing Agricultural University in China relating to crop-growth sensors achievements of theatNanjing in China relating to crop-growth sensors
Summary
Real-time, non-destructive, and high-throughput acquisition of crop-growth information is the most important requirement for precision management of crop production. These types of sensors can produce a detailed determination of the spectral characteristics of a crop’s biochemical components, they have several disadvantages including small monitoring range, large labor intensities, and a monitoring regime that is discontinuous These methods cannot provide the high-throughput of information needed for real-time decisions to be made in the production and management of crops spread over large areas in the field. To address this problem, research institutes have started to develop crop-growth monitoring equipment based on vehicle platforms. We subsequently thecanopy system including to determine, real-time online, the major growth of growth indices ofused a crop the in NDVI, ratioand vegetation
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