Classification method of tropical natural forest vegetation type groups in Hainan

A classification method and natural forest technology, applied in the field of remote sensing, can solve the problems of lack of classification and identification methods for tropical natural forest remote sensing, and achieve good classification results

Inactive Publication Date: 2018-10-19
三亚中科遥感研究所 +1
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Problems solved by technology

However, the existing methods and technologies mostly focus on the identification of coniferous forests, broad-leaved forests, and mixed coniferous and broad-leaved forests in large-scale areas, and lack methods for remote sensing classification and identification of finer internal forest types in tropical natural forests. This is mainly due to the relatively hot and humid conditions of forests in tropical areas. The vegetation in the forest grows tall...

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  • Classification method of tropical natural forest vegetation type groups in Hainan
  • Classification method of tropical natural forest vegetation type groups in Hainan
  • Classification method of tropical natural forest vegetation type groups in Hainan

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[0023] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. It should be understood that the specific The examples are only used to explain the present invention, not to limit the present invention. 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.

[0024] Existing remote sensing tropical natural forest classification methods are mostly focused on the classification and application of vegetation type subclasses (secondary classes) dominated by coniferous forests and broad-leaved fores...

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Abstract

The invention discloses the classification method of tropical natural forest vegetation type groups in Hainan. In the invention, multi-temporal SAR data and mono-temporal less-cloud-covered optical remote sensing data are used to analyze a typical tropical forest land spectrum and scattering characteristic difference and dry and rainy season change information. A Hainan tropical natural forest vegetation type group type and a Hainan tropical natural forest growth distribution rule are combined and a remote sensing vegetation type group classification system suitable for a Hainan tropical natural forest is provided. Based on that, a Hainan tropical natural forest classification method based on machine learning is established. The method provides a solution for the remote sensing classification problem of a natural forest vegetation type group (three-level class) in the Hainan Island, and classification precision is higher than 80%.

Description

technical field [0001] The invention relates to the technical field of remote sensing, in particular to a classification method for vegetation type groups of tropical natural forests in Hainan based on multi-source and multi-temporal remote sensing data. Background technique [0002] Tropical natural forest is the forest ecosystem with the most abundant species in the world. It is mainly distributed in tropical climate regions near the equator, and plays an important role in global climate change, ecological cycle, water and soil conservation, and air purification. Therefore, it is of great significance to carry out resource investigation and monitoring of tropical natural forests. [0003] The natural forests of Hainan Island in my country are the most perfect and most abundant tropical natural forests in China. They are the core of the Hainan Island ecosystem and have high value in environmental protection. They have brought great benefits to the development of local touri...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N99/00
CPCG06V20/13G06F18/2411
Inventor 张露万祥星李新武史健康孙中昶
Owner 三亚中科遥感研究所
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