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Determination method of disaster-affected grades of Chinese white pines and determination system thereof

A judging method and judging system technology, applied in the direction of instruments, character and pattern recognition, computer parts, etc., can solve the problems of inability to detect pest disasters in time, subjectivity of time lag, etc., reduce manpower and material costs, and ensure healthy development , the effect of improving economic efficiency

Active Publication Date: 2018-09-25
BEIJING FORESTRY UNIVERSITY
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  • Description
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Problems solved by technology

Usually, these monitoring methods have a time lag and are highly subjective. In areas with dangerous terrain and restricted movement, staff cannot detect pest disasters in time

Method used

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  • Determination method of disaster-affected grades of Chinese white pines and determination system thereof
  • Determination method of disaster-affected grades of Chinese white pines and determination system thereof
  • Determination method of disaster-affected grades of Chinese white pines and determination system thereof

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Embodiment Construction

[0041] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0042] see figure 1 , the system for judging the damage level of Chinese pine proposed by the present invention includes a camera mounted on an unmanned aerial vehicle, an image acquisition card, an area segmentation module of a damaged Chinese pine area, and a module of a disaster level of Chinese pine, wherein the unmanned aerial vehicle, camera, image acquisition card, etc. constitute the present invention. The image acquisition module in the invention. Th...

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Abstract

The invention discloses a determination method of disaster-affected grades of Chinese white pines and a determination system thereof. The determination method comprises following steps of S1: shootingsample place images of the Chinese white pines through a camera carried by an unmanned aerial vehicle; S2: by use of the type-two fuzzy clustering algorithm, carrying out region segmentation on the disaster-affected Chinese white pines in the sample place images of the Chinese white pines and calculating the specific value of the regions of the disaster-affected Chinese white pines to the sampleplace images of the Chinese white pine; and S3: by combining the leaf loss rate obtained through the ground investigation statistics, judging the disaster-affected grade of the Chinese white pines.

Description

technical field [0001] The invention relates to the technical field of prevention and control of forest diseases and insect pests, in particular to a method for judging the damage level of Chinese pine and a judging system thereof. Background technique [0002] Forest pests and diseases are the primary factors that threaten forest health. The occurrence of forest diseases and insect pests in my country is very serious, and the disaster rate of forestry pests and diseases is much higher than the average level in the world, which has brought a huge impact on my country's ecological environment construction and forestry production. How to monitor and prevent forest diseases and insect pests has been an important topic studied by forestry experts at home and abroad for many years. There are three main monitoring methods for traditional forestry pests and diseases: 1. Regularly arrange forest farm staff to conduct manual inspections of key forest areas that are vulnerable to disa...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/188G06F18/23211G06F18/24
Inventor 刘文萍骆有庆陆鹏飞宗世祥
Owner BEIJING FORESTRY UNIVERSITY
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