Forest point cloud sorting method based on mode recognition

A technology of pattern recognition and classification method, applied in character and pattern recognition, instruments, computer parts, etc., can solve the difficulty of data acquisition, does not distinguish between photosynthetic parts and non-photosynthetic parts of tree canopy, does not have a wide range of universality, etc. question

Active Publication Date: 2013-09-25
NANJING UNIV
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Problems solved by technology

The spectral method mainly calculates the parameters of the canopy structure based on the different reflectance of each part of the tree, and usually establishes some correlations to calculate, but these correlations usually do not have a wide range of universality
The porosity theory method is based on the measurement of transmitted beam radiation, which provides a powerful tool for the estimation of LAI and leaf inclination angle, but t

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  • Forest point cloud sorting method based on mode recognition
  • Forest point cloud sorting method based on mode recognition
  • Forest point cloud sorting method based on mode recognition

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Embodiment Construction

[0023] The present invention will be further described below by specific examples:

[0024] Use the ground 3D laser scanner Leica ScanStation2 (its parameters are shown in Table 1) to scan the sample quadrat, and then select a relatively complete tree as the research object. In order to better reflect the geometric characteristics of the research object in the point cloud, When choosing, it should be as close as possible to the instrument, so that the occlusion effect will be smaller and the point cloud density will be larger. The final point cloud data of the research object is as follows: figure 2 As shown in (a):

[0025] Table 1 Parameters of 3D laser scanner Leica ScanStation2

[0026]

[0027] Combined with the flowchart, the implementation of the algorithm is described in detail.

[0028] First, use the 3D laser scanner to obtain the point cloud data of the sample square, and then use the software to obtain the point cloud data of the research object. According t...

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Abstract

The invention provides a forest point cloud sorting method based on mode recognition, and belongs to the research field of forest canopy structure parameter obtaining methods. The method comprises the following steps of: obtaining three-dimensional laser point cloud data of the forest, selecting training sample of each sort, and computing obvious feature of each training sample; initially sorting the point cloud data by using an algorithm for obtaining Gauss mixed model based on expectation maximization algorithm, sorting the initial sorting result by using a filter and then processing. Compared with the traditional and existing method of obtaining the canopy structure parameter by using LIDAR, the method provided by the invention is time-saving and labor-saving, free from damaging the forest canopy structure, strong in applicability and high in precision.

Description

1. Technical field [0001] The present invention is a method for automatically classifying forest data using spatial three-dimensional geometric information of laser point cloud data, that is, dividing forest point cloud data into scattered points (leaves, grass, etc.) , linear (thin trunks, branches, etc.), planar (ground, thick trunks, etc.). 2. Background technology [0002] Forest vegetation canopy structure can be defined as the shape, size, orientation and spatial distribution of all aboveground canopy elements, which control the transfer of matter and energy between the land and the atmosphere, by affecting the rate and magnitude of photosynthesis and transpiration It affects the material and energy exchange between vegetation and the environment, and also provides habitat for some animals and plants. Therefore, quantitative description of canopy structure is a prerequisite for understanding forest canopy structure and revealing the long-term succession law of forest ...

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Application Information

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IPC IPC(8): G06K9/62G06K9/46
Inventor 李艳马利霞郑光居为民
Owner NANJING UNIV
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