Winter wheat powdery mildew remote sensing monitoring method based on ASD hyperspectral data

A technology for remote sensing monitoring and winter wheat, applied in the measurement of color/spectral characteristics, data processing applications, instruments, etc., and can solve problems such as band redundancy

Active Publication Date: 2018-11-16
ANHUI UNIVERSITY
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Problems solved by technology

However, due to the large number of hyperspectral remote sensing data bands, there is redundancy between the bands. Therefore, it is necessary to design a remote sensing monitoring method for winter wheat powdery mildew based on ASD hyperspectral data. By analyzing, combining and strengthening the original band information, extract sensitive bands. And build a new vegetation index and apply it to remote sensing monitoring of pests and diseases

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  • Winter wheat powdery mildew remote sensing monitoring method based on ASD hyperspectral data
  • Winter wheat powdery mildew remote sensing monitoring method based on ASD hyperspectral data
  • Winter wheat powdery mildew remote sensing monitoring method based on ASD hyperspectral data

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[0033] The present invention will be further described below in conjunction with accompanying drawing:

[0034] Such as figure 1 A remote sensing monitoring method for winter wheat powdery mildew based on ASD hyperspectral data is shown, the method includes the following steps:

[0035] S1. Collect the canopy hyperspectral data of winter wheat in the experimental field, and calculate the disease index DI of winter wheat.

[0036] The hyperspectral data and disease index data come from the pest and disease experiments carried out in Xiaotangshan National Precision Agriculture Demonstration Base (40°10.6′N, 116°26.3′E) in Changping District, Beijing in 2001-2002. According to the relevant test standards, the wheat in the test site was inoculated with powdery mildew spores, and the wheat variety used in the test was "Beinong 10", which is susceptible to powdery mildew. In the above-mentioned field data collection experiment, the spectrum collection uses the ASDFieldSpec Pro FR ...

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Abstract

The invention relates to a winter wheat powdery mildew remote sensing monitoring method based on ASD hyperspectral data, comprising the steps of acquiring the canopy hyperspectral data of winter wheat, and calculating a disease index DI; selecting the canopy hyperspectral data in a waveband range of 400-800 nm as test data; calculating the weighted values a of respective wavebands for the diseaseindex DI and correlation coefficients between respective wavebands, obtaining distances d from the normalized weighted values to the normalized correlation coefficients between the waveband corresponding to the maximum value of the weighted values a and other wavebands, and using the waveband corresponding to the maximum value of the weighted values a and the waveband corresponding to the maximumpositive value in the distances d as the optimal sensitive waveband combination; constructing a new vegetation index NDVI1; and constructing a winter wheat powdery mildew monitoring model by using 10vegetation indices related to the condition of the powdery mildew and the new vegetation index NDVI1. The method analyzes, combines and strengthens the original waveband information in the winter wheat hyperspectral data, extracts the sensitive waveband, constructs the new vegetation index, and is used for remote sensing monitoring of pests and diseases.

Description

technical field [0001] The invention relates to the technical field of remote sensing monitoring of wheat powdery mildew, in particular to a remote sensing monitoring method for winter wheat powdery mildew based on ASD hyperspectral data. Background technique [0002] Wheat is one of the main grains in our country, and it has been planted on a large scale in some areas. Wheat powdery mildew is one of the main diseases that threaten the yield and quality of wheat. It has the characteristics of spreading in a large area. According to relevant statistics, when the disease breaks out severely, the wheat yield can be reduced by more than 20%. With global warming, good conditions are provided for the occurrence of diseases. Therefore, it is of great significance to carry out real-time and effective monitoring of crop diseases and provide effective reference for relevant departments. In the monitoring methods of diseases, the traditional field survey method is time-consuming and ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06Q50/02G01N21/31
CPCG06Q50/02G01N21/31G06V20/188G06F2218/12
Inventor 黄林生丁文娟刘文静赵晋陵张东彦杜世州黄文江徐超梁栋
Owner ANHUI UNIVERSITY
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