Visible light unmanned aerial vehicle remote sensing image forest tree species classification method based on multi-feature optimization

A tree species classification and remote sensing image technology, applied in computer parts, instruments, computing and other directions, can solve the problems of lack of spectral information in visible light UAV remote sensing images, inability to effectively distinguish multiple tree species, etc., to make up for the lack of spectral characteristics and improve The effect of precision and automation

Pending Publication Date: 2020-04-10
FUZHOU UNIV
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Problems solved by technology

[0004] In view of this, the purpose of the present invention is to provide a method for classifying forest tree species in visible light UAV remote sensing images based on multi-feature optimization, to solve the problem that the visible light UAV remote sensing image has little spectral information and cannot effectively distinguish multiple tree species

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  • Visible light unmanned aerial vehicle remote sensing image forest tree species classification method based on multi-feature optimization
  • Visible light unmanned aerial vehicle remote sensing image forest tree species classification method based on multi-feature optimization
  • Visible light unmanned aerial vehicle remote sensing image forest tree species classification method based on multi-feature optimization

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[0065] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0066] It should be pointed out that the following detailed description is exemplary and intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0067] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinatio...

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Abstract

The invention relates to a visible light unmanned aerial vehicle remote sensing image forest tree species classification method based on multi-feature optimization, and the method comprises the steps:obtaining a visible light remote sensing image of a needed forest region through unmanned aerial vehicle aerial photography, and generating a digital surface model and a digital orthographic image map through preprocessing; establishing a visible light unmanned aerial vehicle image tree species classification system; extracting multiple types of features from the digital surface model and the digital orthographic image map to construct a feature space; selecting an optimal classification feature subset by using a recursion elimination random forest algorithm; using a random forest algorithm on the feature subset to realize tree species classification, and extracting a tree species distribution diagram; and performing precision evaluation on the classification result. The method is beneficial to popularization and application of the unmanned aerial vehicle visible light remote sensing image in forest type and tree species identification in a forest region.

Description

technical field [0001] The invention relates to the field of automatic extraction of remote sensing information of agricultural and forestry resources, in particular to a method for classifying forest tree species in visible light UAV remote sensing images based on multi-feature optimization. Background technique [0002] Tree species is an important parameter in forest resources information. Accurate extraction of tree species information is of great significance for forest resources investigation, alien species monitoring, and ecological health assessment. Traditional tree species identification methods are based on field surveys, which are labor-intensive, time-consuming, and limited by spatial scope. Remote sensing means can carry out periodic and repeatable observation of target features in a wide range, and has been widely used in forest information extraction. Among them, medium-resolution satellite remote sensing images can identify forest types in a large area, but...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/188G06F18/24
Inventor 周小成郑磊黄洪宇
Owner FUZHOU UNIV
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