Winter wheat powdery mildew remote sensing monitoring method based on wavelet analysis and support vector machine

A support vector machine and remote sensing monitoring technology, applied in the field of remote sensing monitoring of winter wheat powdery mildew, can solve the problems of difficult monitoring and forecasting of wheat powdery mildew, and achieve the effect of improving the accuracy of disease identification

Active Publication Date: 2017-08-29
ANHUI UNIVERSITY
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Problems solved by technology

[0007] The purpose of the invention is to solve the defect that wheat powdery mildew is difficult to monitor and forecast in the prior art, and to provide a remote sensing monitoring method for winter wheat powdery mildew based on wavelet analysis and support vector machine to solve the above problems

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  • Winter wheat powdery mildew remote sensing monitoring method based on wavelet analysis and support vector machine
  • Winter wheat powdery mildew remote sensing monitoring method based on wavelet analysis and support vector machine
  • Winter wheat powdery mildew remote sensing monitoring method based on wavelet analysis and support vector machine

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[0051] 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:

[0052] Such as figure 1 Shown, a kind of winter wheat powdery mildew remote sensing monitoring method based on wavelet analysis and support vector machine of the present invention, comprises the following steps:

[0053] The first step is data acquisition. Obtain remote sensing data and ground survey point data of winter wheat powdery mildew, among which, the remote sensing data are the CCD optical data and IRS thermal infrared data of the environmental star, namely the environment and disaster monitoring and forecasting small satellite constellation A, B (HJ-1A / 1B star) data , in practical application, according to the weather conditions in the research area, the image data with better quality and the time closest to the ground surv...

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Abstract

The invention relates to a winter wheat powdery mildew remote sensing monitoring method based on wavelet analysis and a support vector machine (SVM). The method solves a problem that wheat powdery mildew is difficult to monitor and forecast compared with the prior art. The method comprises the following steps of data acquisition; remote sensing data preprocessing; selection of modeling features; establishment of a SVM model; and acquisition of remote sensing monitoring results. The method accurately obtains the spatial distribution characteristics of wheat powdery mildew in real time by using a monitoring model established by environmental satellite remote sensing data subjected to wavelet transform and feature selection in combination with a SVM algorithm, and provides a basis for the prevention and control of powdery mildew.

Description

technical field [0001] The invention relates to the technical field of remote sensing monitoring, in particular to a remote sensing monitoring method for winter wheat powdery mildew based on wavelet analysis and support vector machine. Background technique [0002] Wheat powdery mildew seriously affects wheat yield. According to statistics, powdery mildew damage can generally reduce wheat yield by 5% to 10%, and it can reach more than 20% in severe areas. Accurate acquisition of disease occurrence and its spatial distribution is very necessary for disease control. Traditional pest monitoring mainly relies on field surveys and field sampling by plant protection personnel. Although the authenticity and reliability of these traditional methods are high, they are time-consuming and labor-intensive, and are difficult to meet the needs of real-time monitoring and forecasting of large-scale pests and diseases. Therefore, it is necessary to establish a monitoring model of remote sen...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/46G06K9/62
CPCG06V20/188G06V10/449G06F18/2411
Inventor 黄林生刘文静黄文江杜世州徐超梁栋洪琪赵晋陵张东彦阮超
Owner ANHUI UNIVERSITY
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