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The extraction method and medium of urban agglomeration green space

A green space and urban agglomeration technology, applied in the field of data processing, can solve problems such as the inability to obtain the social function attributes of urban green space

Active Publication Date: 2020-09-08
INST OF GEOGRAPHICAL SCI & NATURAL RESOURCE RES CAS
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Problems solved by technology

[0004] The present invention provides a method and medium for extracting greenness space of urban agglomerations to at least solve the problem in the related art that only relying on a single remote sensing data can only obtain land cover information, but cannot obtain the social function attributes of urban greenness space

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  • The extraction method and medium of urban agglomeration green space
  • The extraction method and medium of urban agglomeration green space
  • The extraction method and medium of urban agglomeration green space

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Embodiment Construction

[0031] The characteristics and exemplary embodiments of various aspects of the present invention will be described in detail below. In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. It will be apparent to one skilled in the art that the present invention may be practiced without some of these specific details. The following description of the embodiments is only to provide a better understanding of the present invention by showing examples of the present invention.

[0032] It should be noted that, in this document, the terms "comprising", "comprising" or any other variation thereof are intended to cover a non-exclusive inclusion such that a process, ...

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Abstract

The invention provides a method and medium for extracting urban agglomeration green space. Among them, the method includes: obtaining high-resolution remote sensing data of urban agglomerations, and extracting land cover data of urban agglomerations; obtaining social perception data of urban agglomerations, and extracting social function attribute data of urban agglomeration land; Functional attribute data, classify the land of the urban agglomeration, and obtain the classification information related to the greenness of the urban agglomeration land; according to the classification information, extract the greenness of the urban agglomeration. The present invention solves the problem in the related art that only relying on a single remote sensing data can only obtain land cover information, but cannot obtain the social function attributes of urban green space, and realizes the statistics of green space of urban agglomerations including social function attributes and research.

Description

technical field [0001] The present invention relates to the field of data processing, in particular to a method and medium for extracting urban agglomeration green spaces. Background technique [0002] With the development of remote sensing technology, the method of urban greenness mapping by means of remote sensing has attracted the attention of many researchers. There are two main methods of extracting urban green space: one is based on pixel classification, for example: Ouma et al. combined spectral and spatial information to classify Quickbird images and extract urban green space. The results show that this method can significantly improve The accuracy of urban green space extraction; Trisakti, B used a pixel-based method to classify Pleides images with supervision (MLEN) and unsupervised (ISODATA), and classified urban green space according to coverage; Feng, Q et al. Methods Texture analysis and random forest classification were carried out on UAV aerial images, and t...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/188G06F18/2411
Inventor 方创琳杨智奇李广东王振波
Owner INST OF GEOGRAPHICAL SCI & NATURAL RESOURCE RES CAS
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