Tree species classification method based on multi-source simultaneous high-resolution remote sensing data

A high-resolution, remote sensing data technology, applied in the fields of instruments, character and pattern recognition, computer parts, etc., can solve the problem of refining the classification level of tree species and the classification accuracy cannot meet the needs of use, and achieves improved classification accuracy and automation. And the effect of improving precision and easy promotion

Active Publication Date: 2016-02-24
NANJING FORESTRY UNIV
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Problems solved by technology

Apparently, these methods cannot meet the requirements for refining tree species classification levels and classification accuracy.

Method used

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  • Tree species classification method based on multi-source simultaneous high-resolution remote sensing data
  • Tree species classification method based on multi-source simultaneous high-resolution remote sensing data
  • Tree species classification method based on multi-source simultaneous high-resolution remote sensing data

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Embodiment 1

[0038] Overview of the test area

[0039] The research area is selected from the state-run Yushan Forest Farm in Changshu City, Jiangsu Province (120°42′9.4″E, 31°40′4.1″N), with an area of ​​about 1422hm2 , the elevation change range is 2-261m; the study area is located in a subtropical monsoon climate, with an average annual precipitation of 1062.5mm; the forest type belongs to subtropical secondary mixed forest, which can be subdivided into coniferous forest, broad-leaved forest and mixed forest. The main coniferous and broad-leaved deciduous tree species include Pinus massoniana, Quercus acutissima, Liquidam barformosan and Castanea mollissima, etc., and some evergreen broad-leaved species are accompanied.

[0040] According to the tree species composition, age, and site stratification in Yushan Forest Farm’s forest resources investigation historical data (2012), seven 30m×30m square plots were selected, including three types of forests: coniferous forest, broad-leaved fore...

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Abstract

The present invention discloses a tree species classification method based on multi-source simultaneous high-resolution remote sensing data. High-resolution and hyperspectral data simultaneously acquired by an integrated sensor is utilized; firstly, coronal breadth identification is carried out based on the high-resolution data and an object-oriented method, then tree species classification is carried out based on spatial details and spectral features, which are extracted by the hyperspectral data, by combining a BP neural network classifier, and finally, the accuracy is verified by a confusion matrix. According to the tree species classification method disclosed by the invention, based on an edge detection multi-scale segmentation method, segmentation grades with different scales are established from multiple levels and multiple patterns and segmentation and information extraction are carried out layer by layer, so that the classification accuracy of tree species and forest types of subtropical natural secondary forests are promoted.

Description

technical field [0001] The invention belongs to the technical fields of forestry investigation, dynamic monitoring and biological diversity, and in particular relates to a tree species classification method based on multi-source simultaneous high-resolution remote sensing data. Background technique [0002] Accurately obtaining forest tree species information and their spatial distribution is of great significance for understanding the structure, function and succession of forest ecosystems, as well as biodiversity. At the same time, information on the spatial distribution of tree species can be used to parameterize forest growth models and ecological process models, guiding and optimizing forest ecosystem simulations. Conventional tree species survey methods mainly rely on ground field surveys and manual interpretation of large-scale aerial photos, which usually consume a large amount of work and are not conducive to updating forest tree species information. The remote sen...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/188G06F18/24317
Inventor 曹林申鑫佘光辉
Owner NANJING FORESTRY UNIV
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