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DBI tree vertex detection method for airborne lidar point cloud data chm

A technology of airborne lidar and point cloud data, which is applied in image data processing, computer components, image analysis, etc., to avoid threshold dependence, solve the problem of ambiguous tree vertices, and achieve effective recognition

Active Publication Date: 2022-06-14
GUILIN UNIVERSITY OF TECHNOLOGY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a tree top position detection method of airborne laser radar point cloud data canopy height model, which can effectively solve the traditional window detection tree apex Threshold dependence of the method to improve the accuracy of tree vertex recognition

Method used

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  • DBI tree vertex detection method for airborne lidar point cloud data chm
  • DBI tree vertex detection method for airborne lidar point cloud data chm
  • DBI tree vertex detection method for airborne lidar point cloud data chm

Examples

Experimental program
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Effect test

Embodiment

[0018] (1) Set the maximum terrain slope: set the maximum terrain slope displayed in the point cloud to 80°;

[0019] (2) Set the iteration angle: the conversion angle of all allowable values ​​between the ground classification points to be measured and the currently known ground classification points is 8°;

[0020] (3) Set the iteration distance: the distance threshold between the point to be classified and the triangulation network is set to 1.6m;

[0021] Using the above method, filter and classify the point cloud of the experimental plot, and display the separated ground point class in brown, and the separated vegetation point class in green.

[0022] Step 2) Combine figure 2 , use the filtered and classified point cloud data to generate DEM, DSM, CHM. The DSM and DEM of the experimental forest area were respectively generated by using the TIN calculation method for the non-ground laser point cloud and the ground reflection laser point cloud. After many experiments in...

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PUM

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Abstract

The invention relates to the field of laser radar data processing, discloses a DBI tree vertex detection method for a canopy height model of airborne laser radar point cloud data, and invents a method for detecting a tree vertex based on a DBI control foreground pixel of a canopy height canopy model , including: 1. Standardize the marker pixel generation conditions of the canopy height model; 2. Use the gray level change characteristics of the height canopy model to filter and eliminate pseudo foreground pixels; 3. Introduce the similarity judgment factor DBI to filter the tree canopy with DBI-K vertex. The invention provides a tree top position detection method for a canopy height model of airborne lidar point cloud data, which can effectively solve the threshold dependence problem of the traditional window detection tree top method and improve the recognition accuracy of the tree top.

Description

technical field [0001] The present invention relates to the field of laser radar (Light Laser Detection and Ranging, LiDAR) data processing, in particular to the DBI (Davies-Bouldin Index) tree vertex detection method of airborne laser radar point cloud data canopy height model (Canopy Height Model, CHM) . technical background [0002] Lidar has a strong penetrability to the forest canopy, which is very conducive to forest census and forest stand parameter acquisition, and can accurately identify the position of treetops and the canopy of individual trees. Airborne lidar technology provides theoretical basis and technical support for the development of precision forestry, and has broad application prospects in forest management and ecosystem research. [0003] At present, due to the complexity of generating canopy height model images from airborne LiDAR point clouds, the identification of tree vertices in the field of canopy position identification is inaccurate. In the ex...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T7/194G06T7/136G06K9/62G06V10/762G06V10/764
CPCG06T7/0002G06T7/194G06T7/136G06T2207/10028G06T2207/10044G06T2207/30188G06F18/23213G06F18/24
Inventor 周国清穆叶煊
Owner GUILIN UNIVERSITY OF TECHNOLOGY
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