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A regional-scale monitoring method for wheat stripe rust based on the red edge band of remote sensing images

A technology for wheat stripe rust and remote sensing imagery, applied in neural learning methods, image enhancement, image analysis and other directions, can solve problems such as poor accuracy

Active Publication Date: 2021-02-12
ANHUI UNIVERSITY
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  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

[0008] The purpose of the present invention is to solve the defect of poor accuracy of remote sensing monitoring of wheat stripe rust in the prior art, and provide a regional-scale monitoring method of wheat stripe rust based on the red edge band of remote sensing images to solve the above problems

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  • A regional-scale monitoring method for wheat stripe rust based on the red edge band of remote sensing images
  • A regional-scale monitoring method for wheat stripe rust based on the red edge band of remote sensing images
  • A regional-scale monitoring method for wheat stripe rust based on the red edge band of remote sensing images

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Embodiment Construction

[0067] In order to have a further understanding and understanding of the structural features of the present invention and the achieved effects, the preferred embodiments and accompanying drawings are used for a detailed description, as follows:

[0068] like figure 1 As shown, the regional scale wheat stripe rust monitoring method based on the red edge band of the remote sensing image of the present invention comprises the following steps:

[0069] The first step is the acquisition and preprocessing of remote sensing images.

[0070] In the present invention, the data used mainly include remote sensing data and wheat stripe rust field survey data (label data). The remote sensing data is Sentinel-2 satellite remote sensing data. Its detailed band and resolution information are shown in Table 1. According to the weather conditions in the study area, the image data with better quality and the time closest to the ground survey were selected. A 1m×1m quadrat was taken for each ...

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Abstract

The invention relates to a regional scale wheat stripe rust monitoring method based on the red edge band of remote sensing images, and compared with the prior art, the defect of poor monitoring accuracy of wheat stripe rust using remote sensing is solved. The invention includes the following steps: acquisition and preprocessing of remote sensing images; screening of primary selection characteristic factors; construction of a wheat stripe rust severity monitoring model; training of the wheat stripe rust severity monitoring model; The invention uses Sentine-2 remote sensing images to invert to obtain disease-related broadband vegetation index characteristics and red-edge vegetation index characteristics, and then uses ReliefF and K-means algorithms to screen broad-band vegetation index characteristics that are more relevant to diseases and less redundant. The band vegetation index feature set and the feature set added with the red edge vegetation index were used to establish a wheat stripe rust severity monitoring model with the BPNN algorithm to realize the monitoring of wheat stripe rust severity on a regional scale.

Description

technical field [0001] The invention relates to the technical field of remote sensing data processing, in particular to a regional-scale monitoring method for wheat stripe rust based on the red edge band of remote sensing images. Background technique [0002] Wheat stripe rust (Puccinia striiformis f. sptritici) is an airborne disease, spores are transmitted through the air, and has the characteristics of wide incidence, strong prevalence, and high incidence probability. It is one of the main diseases that threaten wheat yield. After the wheat is damaged, it can lead to early withering of the leaves and a reduction in the number of ears. Generally, the yield can be reduced by 5% to 10%, and the severe disease field can reduce the yield by more than 20%. Traditional pest monitoring mainly relies on ground surveys. Although it is highly authentic, it is time-consuming and laborious and difficult to meet the needs of large-scale monitoring. Remote sensing technology is a new t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08G06T7/00G06T7/136
CPCG06N3/084G06T7/0002G06T7/136G06T2207/10032G06T2207/10048G06T2207/20081G06T2207/30188G06V20/188G06N3/044G06F18/23213G06F18/241
Inventor 黄林生江静黄文江梁栋徐超张东彦赵晋陵张寒苏胡廷广
Owner ANHUI UNIVERSITY
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