Tree species identification method based on full-waveform LiDAR canopy profile model

A profile model and recognition method technology, applied in character and pattern recognition, instruments, computer components, etc., can solve the problems of missing, not including forest vertical structure information, affecting the extraction and classification of understory low vegetation

Active Publication Date: 2015-08-05
NANJING FORESTRY UNIV
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Problems solved by technology

However, the above classification methods are based on point cloud feature variables and do not contain complete forest vertical structure information (that is, there is information missing)
At the same time, there is also a "

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  • Tree species identification method based on full-waveform LiDAR canopy profile model
  • Tree species identification method based on full-waveform LiDAR canopy profile model
  • Tree species identification method based on full-waveform LiDAR canopy profile model

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Embodiment 1

[0047] A tree species identification method based on the full waveform LiDAR canopy profile model, taking the tree species classification in a northern subtropical natural secondary mixed forest as the main forest type as an example. The forest area is 20-261m above sea level and covers an area of ​​about 1100 hectares. The main tree species are coniferous masson pine (Pinus massoniana), fir (Cunninghamia lanceolata) and slash pine (Pinus elliottii), and broad-leaved oak (Quercus acutissima), sweetgum (Liquidambar formosana) and holly (Ilex chinensis) ( See figure 1 ). In the forest area, 12 square sample plots (30×30m) were arranged according to the composition of tree species, forest age, and site conditions. In each sample plot, individual tree species were manually identified, and forest parameters such as diameter at breast height, tree height, and crown width were measured. The center of the sample plot was positioned by differential GPS, and the relative position of e...

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Abstract

The invention discloses a tree species identification method based on a full-waveform LiDAR canopy profile model. The method comprises the following steps: an airborne small-pot full-waveform LiDAR sensor acquires data; the sensor records complete waveform information returned by each laser pulse; LiDAR waveform data is preprocessed; individual tree positioning and crown extracting are performed; a canopy profile model of the vertical structure and returned energy information of an individual tree is fitted based on Weibull distribution and a cubic spline function model, and model parameters are extracted as feature variables; and tree species classification is performed by a random forest classifier. The verification results of the invention show that the overall accuracy is increased by about 9% and the Kappa coefficient is increased by about 0.1 for the level of classification of four main tree species compared with a tree species classification method using remote sensing.

Description

technical field [0001] The invention relates to the technical field of forest resource management and protection, in particular to a tree species identification method based on a full waveform LiDAR canopy profile model. Background technique [0002] Accurate tree species classification is of great significance for forestry surveys, biodiversity studies, and simulating individual tree growth of specified tree species. At the same time, this information can also be used to parameterize forest growth models and ecological process models to guide and optimize forest resource management. Conventional forest tree species survey methods mainly rely on field surveys and interpretation of large-scale aerial photographs, etc., and their accuracy is often low, and it is difficult to be practically promoted in large areas. LiDAR (Light Detection and Ranging) is an active remote sensing technology that hits the surface of an object by emitting a laser beam and analyzing its return sign...

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Application Information

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IPC IPC(8): G06K9/00
CPCG06F18/2415
Inventor 曹林朱兴洲许子乾
Owner NANJING FORESTRY UNIV
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