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A method for extracting individual tree information from lidar point clouds using hierarchical clustering

A technology of hierarchical clustering and clustering center, applied in character and pattern recognition, instrumentation, calculation, etc., can solve the problems of imperfect stand structure inversion, difficulty in extracting lower forest trees, and lack of single tree information. The effect of great significance, improved extraction capacity, and improved work efficiency

Active Publication Date: 2020-06-09
BEIJING FORESTRY UNIVERSITY
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Problems solved by technology

[0007] (1) Under the conditions of high forest stand density and complex forest layer structure, it is difficult to extract the lower forest trees, and the forest trees that can be extracted are roughly about 20-60% of the actual number; how to extract more forest trees has become one of the challenges;
[0008] (2) Part of the individual tree information is missing, resulting in an unsound inversion function of the stand structure

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  • A method for extracting individual tree information from lidar point clouds using hierarchical clustering
  • A method for extracting individual tree information from lidar point clouds using hierarchical clustering
  • A method for extracting individual tree information from lidar point clouds using hierarchical clustering

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[0041] In order to clearly illustrate the technical features of this solution, the present invention will be described in detail below through specific implementation modes and in conjunction with the accompanying drawings. The present invention: a method for extracting single tree information from LiDAR point clouds using hierarchical clustering, the main steps are set as figure 1 As shown, the method includes the following steps:

[0042] Step 1: Slice the point cloud horizontally; horizontally slice all the point clouds using the point cloud high percentile method to ensure that the number of point clouds contained in each point cloud layer is equal; the number of slices N is based on the canopy density of the stand , The complexity of the stand structure is changed, the single-layer artificial forest N can be set at about 3-5; the natural forest N can be set at about 5-10; the slice effect is as follows figure 2 shown;

[0043] Step 2: Extract the local maximum position...

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Abstract

The invention discloses a method for extracting single tree information from LiDAR by using hierarchical clustering, which belongs to the category of LiDAR point cloud data processing and information extraction. The key technical points include: 1. Horizontally layering the point cloud; 2. Using The k-means clustering method classifies each layer of point clouds and assigns different attribute values; 3. Fusion of point clouds that meet the preset conditions; 4. Extracting single tree position, tree height, and crown from point clouds with the same attribute values and other information, and calculate the forest structure information through the single tree information. The key problems to be solved include: 1. Realize the extraction of single trees in the understory layer, and accurately extract more than 80% of the number of forest stands; 2. Realize the function of extracting single tree information from LiDAR to calculate the stand structure; 3. Calculate the point cloud density No excessive requirements, 2p / m has been confirmed 2 Density point clouds can do the job. The invention can be applied to the field of LiDAR retrieval information, especially in complex forest stand conditions, and can accurately extract relevant information such as single tree position, tree height, crown width and stand structure parameters.

Description

[0001] 1. Technical field [0002] The invention relates to a method for extracting individual tree information from a laser radar (LiDAR) point cloud, in particular to a method for extracting understory trees in a complex stand structure, suitable for data processing and information extraction of airborne laser radar point clouds, The invention belongs to the technical field of lidar point cloud data processing. [0003] 2. Technical background [0004] LiDAR (Light Detection And Ranging, LiDAR) is an active remote sensing technology that measures the distance between the sensor and the target through the laser emitted by the sensor. Due to the high penetrability of LiDAR, applying LiDAR technology to forestry remote sensing can obtain a large amount of point cloud data containing forest structure information; by segmenting the whole point cloud into individual trees, it is possible to further obtain individual tree-scale forest stands Information will be replaced by fast and...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/188G06F18/231
Inventor 张晓丽霍朗宁张凝瞿帅
Owner BEIJING FORESTRY UNIVERSITY
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