Crop nitrogen fertilizer variable management method based on unmanned aerial vehicle image

Abstract

The invention discloses a crop nitrogen fertilizer variable management method based on an unmanned aerial vehicle image. The method comprises the following steps: designing a community; acquiring the unmanned aerial vehicle image; constructing a texture index for diagnosing the nitrogen nutrition index; inversing the crop nitrogen nutrition index coupled with the texture index and the spectral index; and constructing a topdressing amount calculation model. The defect that only spectral information is utilized in traditional crop nitrogen nutrition index inversion is overcome, the nitrogen nutrition index can be diagnosed based on unmanned aerial vehicle image texture features, a technical method for crop nitrogen nutrition index inversion through coupling of image spectra and texture features is provided, the crop nitrogen nutrition level judgment precision is improved. And meanwhile, a high-precision crop variable rate fertilization method is designed by coupling a crop fertilizer requirement rule and a nitrogen nutrition index.

Description

technical field [0001] The invention relates to a crop nitrogen fertilizer variable management method, in particular to a crop nitrogen fertilizer variable management method based on drone images, and belongs to the technical field of remote sensing inversion. Background technique [0002] Nitrogen is an important nutrient element necessary for crop growth and development. For most soils, the available nitrogen content in the current season cannot meet the needs of crop growth, and external nitrogen sources need to be added. Therefore, nitrogen fertilizer management is one of the most important links in crop production with the goal of achieving high yield and high quality. The demand for nitrogen in the process of crop growth and development is affected by comprehensive factors such as soil conditions, farmland climate and crop characteristics, which vary greatly in time and space. To ensure yields, farmers often apply excess nitrogen fertilizers to the fields. Excessive ...

AI Technical Summary

Problems solved by technology

This method has the following defects: 1) It is only based on the spectral information of UAV images to judge the nitrogen nutrition level of crops, which is easily affected by the "saturation" phenomenon and causes errors, and does not consider the ultra-high spatial resolution of UAV images , can rely on UAV image texture features to couple spectral information to carry out crop nitrogen nutrition diagnosis; 2) Only divide the nitrogen nutrition level of crops into 7 levels, which is a qualitative variable fertilization method. When the condition is exactly in the middle of the grade, there will be a large error; 3) Setting up a nitrogen fertilizer gradient test with 7 fertilization levels increases a lot of field management costs, which is not conducive to popularization

However, the existing methods of crop variable fertilization have the following defects: first, the method of soil testing and fertilization is time-consuming, labor-intensive, and the accuracy is not high; Defects such as small observation range are difficult to popularize; third, crop variable fertilization management technology based on emerging drone remote sensing platforms is still immature, and the level of precision in judging nitrogen nutrition status and formulating variable fertilization strategies is not high

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