Hyperspectral field tobacco yield prediction method and system based on unmanned aerial vehicle

Abstract

The invention belongs to the technical field of tobacco production, and particularly relates to a hyperspectral field tobacco yield prediction method and system based on an unmanned aerial vehicle. The method comprises the following steps of: acquiring field tobacco hyperspectral image data in real time through an unmanned aerial vehicle; carrying out coordinate loading on the hyperspectral image data, and extracting and processing a corresponding original spectral curve; acquiring a field quadrat yield estimation value, and constructing a field tobacco yield prediction model according to the field quadrat yield estimation value and the spectral characteristic curve; and finally, generating yield prediction data corresponding to the field tobacco. According to the method, the spectral curve of a quadrat tobacco field can be directly extracted from an image, spectrum extraction of the quadrat can be completed by collecting quadrat coordinates, the labor cost is reduced, yield estimation can be conducted before tobacco harvesting through the prediction method, the tobacco yield is calculated and analyzed through the weight of the cured tobacco leaves, the modeling method is simple, and large-area popularization and application can be performed.

Description

technical field [0001] The invention belongs to the technical field of tobacco production, and in particular relates to a method and system for predicting field tobacco yield based on unmanned aerial vehicle hyperspectral. Background technique [0002] The tobacco industry plays a very important role in the process of national economic and social development. The output of tobacco affects the price of tobacco, which in turn affects the income of tobacco farmers. The accurate estimation of tobacco production is of great significance to the pricing and overall distribution of the tobacco industry. [0003] Traditional tobacco production statistics are based on manual statistics. The data collection is not comprehensive, the collection workload is heavy, time-consuming and labor-intensive, and the statistics are all carried out after the tobacco is harvested and roasted, which cannot assist market planning and decision-making scheduling. At present, although there are some stu...

AI Technical Summary

Problems solved by technology

[0003] Traditional tobacco production statistics are based on manual statistics. The data collection is not comprehensive, the collection workload is heavy, time-consuming and labor-intensive, and the statistics are all carried out after the tobacco is harvested and roasted, which cannot assist market planning and decision-making scheduling

At present, although there are some studies on tobacco biochemical parameters and yield using handheld hyperspectral instruments, this method requires a lot of manpower to take samples in the tobacco field, which is inefficient and not conducive to the application of large-scale tobacco field yield estimation.

[0004] Therefore, in view of the incomplete collection of the above data, the heavy collection workload, time-consuming and laborious, and the statistics are carried out after the tobacco is harvested and baked, it is unable to assist market planning, decision-making and scheduling. It is urgent to design and develop a Method and system for forecasting field tobacco yield based on UAV hyperspectral

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