Regional pest detection diagnosis judging method based on wavelet analysis

A technology of wavelet analysis and discrimination method, which is applied in the field of remote sensing analysis of forest disease and insect pest data, and can solve problems such as the weakening of Populus euphratica.

Active Publication Date: 2017-05-24
贾翔
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Problems solved by technology

[0004] The present invention provides a method for detecting, diagnosing, and discriminating regional diseases and insect pests based on wavelet analysis, which overcomes the deficiencies of the prior art, and can

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  • Regional pest detection diagnosis judging method based on wavelet analysis
  • Regional pest detection diagnosis judging method based on wavelet analysis
  • Regional pest detection diagnosis judging method based on wavelet analysis

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Embodiment Construction

[0071] The present invention is not limited by the following examples, and specific implementations can be determined according to the technical solutions and actual conditions of the present invention.

[0072] Below in conjunction with embodiment and accompanying drawing, the present invention is further described:

[0073] as attached figure 1 , 2 , 3, 4, 5, 6, 7, 8, and 9, the regional pest detection and diagnosis method based on wavelet analysis includes the following steps:

[0074] The first step is to obtain the test data of Populus euphratica inchworm pests, extract and analyze the test data, and then enter the second step;

[0075] The second step is to use wavelet transform to perform preliminary analysis on the sampled data, and then enter the third step;

[0076] The third step is to define and construct the NDVI time spectrum curve, and then enter the fourth step;

[0077] The fourth step is to filter the noise of the NDVI time spectrum curve, and then enter ...

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Abstract

The invention relates to the technical field of data remote sensing analysis, and relates to a regional pest detection diagnosis judging method based on wavelet analysis. The method includes the first step of acquiring test data of euphrates poplar pest damage, and performing the sampling analysis; the second step of performing preliminary analysis on the sampling data by the wavelet transform; the third step of defining and structuring a HDVI time spectrum curve; the fourth step of filtering noise of the HDVI time spectrum curve; the fifth step of performing enhancement and separation analysis on euphrates poplar pest damage; the sixth step of setting up a signal detection model of the euphrates poplar leaf-eating pest; the seventh step of dynamically detecting the detected pest signal in real time. Based on the principle of remote sensing and monitoring of forest pest damage and the physical foundation, the euphrates poplar NDVI time spectrum curve containing the pest information is defined and structured by means of NDVI time sequence data; thus the evolution speciality and rule of NDVI along with time change are acquired; the method can effectively monitor the plant growth and pest damage, and avoid euphrates poplar growth weak gradually.

Description

technical field [0001] The invention relates to the technical field of remote sensing analysis of forestry pests and diseases data, and is a method for detecting, diagnosing and discriminating regional pests and diseases based on wavelet analysis. Background technique [0002] Populus euphratica is a desert riparian forest that grows under humid conditions such as river banks and lakes. Its unique physiological structure enables it to survive in harsh environments such as saline-alkali, sandstorm and drought. It is a near-top natural tree community in arid desert areas. It is an important part of the desert ecosystem and plays an important ecological function in maintaining the ecological balance of the desert area, preventing wind and sand fixing, regulating the climate, and improving the ecological environment. However, in recent years, due to excessive water diversion and climate change, the living environment of Populus euphratica has deteriorated, its growth has gradual...

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Application Information

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IPC IPC(8): G06F17/15
CPCG06F17/15
Inventor 贾翔陈孟禹黄铁成来风兵陈蜀江吴焱
Owner 贾翔
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