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LiDAR (Light Detecting and Ranging) data single-tree extraction method with combination of morphological canopy control and watershed

A watershed and morphological technology, applied in image data processing, character and pattern recognition, instruments, etc., can solve the problems of high dependence on CHM quality and the inability to guarantee the accuracy of single tree extraction, so as to reduce over-segmentation and enhance practical value , The effect of improving the accuracy

Active Publication Date: 2014-12-10
RES INST OF FOREST RESOURCE INFORMATION TECHN CHINESE ACADEMY OF FORESTRY
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Problems solved by technology

[0005] The purpose of the present invention is to provide a single tree extraction method from LiDAR data combined with morphological canopy control and watershed, so as to solve the problem of excessive dependence on CHM quality when extracting single trees, and the problem that the accuracy of extracting single trees cannot be guaranteed

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  • LiDAR (Light Detecting and Ranging) data single-tree extraction method with combination of morphological canopy control and watershed
  • LiDAR (Light Detecting and Ranging) data single-tree extraction method with combination of morphological canopy control and watershed
  • LiDAR (Light Detecting and Ranging) data single-tree extraction method with combination of morphological canopy control and watershed

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[0022] The present invention provides a LiDAR data single tree extraction method combined with morphological canopy control and watershed, and its implementation method is as follows figure 1 As shown, including the following operations:

[0023] Step 1. Establish CHM based on LiDAR data;

[0024] Step 2. Based on the morphological canopy control, determine external markers in the CHM established in step 1;

[0025] The external mark is a binary image used to represent the distribution of tree crowns.

[0026] The external markers do not participate in subsequent watershed operations, so as to preserve the compactness of segmentation to the greatest extent and avoid under-segmentation caused by controlling over-segmentation.

[0027] The function of the external marker is to perform canopy control on the results of the watershed calculation, so as to eliminate non-canopy gutters in the results of the watershed calculation.

[0028] Determination of external markers can be p...

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Abstract

The invention aims to reduce the dependence on CHM (Canopy Height Model) quality and improve the precision of single-tree extraction when single tree is extracted from LiDAR (Light Detecting and Ranging) data by aiming at the CHM. The purpose is achieved specifically with the following method comprising the steps of: determining an external mark in the CHM based on the morphological canopy control; performing global median filtering processing on the CHM, and by combining with the external mark, obtaining an internal mark of the CHM after the median filtering processing in a way of using a local extremum; by combining with the internal mark, performing twice watershed operations on the CHM; by using the external mark, respectively optimizing watershed operation results; and extracting single-tree parameters according to single-tree segmentation results. According to the method provided by the invention, a negligible over-segmentation phenomenon only exists in the segmentation results, so that precision of the single-tree segmentation is improved, the degree of dependence on the CHM quality is reduced and a very strong practical value is obtained.

Description

technical field [0001] The invention relates to laser radar data processing technology, in particular to a LiDAR data single tree extraction method combined with morphological canopy control and watershed. Background technique [0002] LiDAR (Light Detecting and Ranging, LiDAR) technology is one of the most revolutionary achievements in the field of remote sensing in the past 20 years. According to its characteristics, LiDAR technology has a wide range of applications in forestry, especially in the construction of canopy height model (Canopy Height Model, CHM) has outstanding advantages. [0003] There are currently many algorithms for extracting single trees from LiDAR data, some of which are for CHM. CHM is an important model in forestry research, which represents the height of the canopy above the ground, reflecting the vertical height change of vegetation and the horizontal distribution of the upper surface of vegetation. For CHM, single tree extraction from LiDAR data...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/46G06T5/00
Inventor 赵旦庞勇李增元刘清旺徐光彩
Owner RES INST OF FOREST RESOURCE INFORMATION TECHN CHINESE ACADEMY OF FORESTRY
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