Automatic Extraction Method of Tree Measurement Factors Based on Point Cloud Data
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    Abstract:

    On account of the crown’s complicated structure and various forms, extracting the tree measurement factors of standing tree automatically, accurately and nondestructively is an important research subject in the forest survey. The three-dimensional (3D) point cloud data via 3D laser scanner was used as the study object. The 3D convex hulls construction algorithm based on computational geometry was presented to extract the crown surface area, crown projection area and crown volume automatically. In order to verify the accuracy of the algorithm, totally eight tree species and 120 standing trees were randomly selected for testing. The average relative errors of standing tree height, DBH and crown width were 2.33%, 1.10% and 3.92%, respectively. The relative average errors of auto computing for crown surface area, crown projection area and crown volume were 3.48%, 6.01% and 5.59%, respectively. 3D point cloud data via 3D laser scanner and 3D convex hulls construction algorithm could help to automatically and accurately calculate the values of these parameters which could not be measured accurately before, providing a reference for extracting the tree measurement factors of standing tree automatically via 3D laser scanner in the future. The proposed method had a practical prospect of application in the survey of forest resources.

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History
  • Received:May 02,2017
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  • Online: August 10,2017
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