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Individual Tree Position Extraction and Structural Parameter Retrieval Based on Airborne LiDAR Data: Performance Evaluation and Comparison of Four Algorithms

by Wei Chen 1,*, Haibing Xiang 2,3,† and Kazuyuki Moriya 4
1
Institute of Surface-Earth System Science, Tianjin University, Tianjin 300072, China
2
Key Laboratory of Aperture Array and Space Application, No. 38 Research Institute of CETC, Hefei 230088, China
3
Key Laboratory of Intelligent Information Processing, No. 38 Research Institute of CETC, Hefei 230088, China
4
Biosphere Informatics Laboratory, Department of Social Informatics, Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan
*
Author to whom correspondence should be addressed.
This author contributed equally to this work.
Remote Sens. 2020, 12(3), 571; https://doi.org/10.3390/rs12030571
Received: 14 January 2020 / Revised: 6 February 2020 / Accepted: 6 February 2020 / Published: 8 February 2020
(This article belongs to the Section Forest Remote Sensing)
Information for individual trees (e.g., position, treetop, height, crown width, and crown edge) is beneficial for forest monitoring and management. Light Detection and Ranging (LiDAR) data have been widely used to retrieve these individual tree parameters from different algorithms, with varying successes. In this study, we used an iterative Triangulated Irregular Network (TIN) algorithm to separate ground and canopy points in airborne LiDAR data, and generated Digital Elevation Models (DEM) by Inverse Distance Weighted (IDW) interpolation, thin spline interpolation, and trend surface interpolation, as well as by using the Kriging algorithm. The height of the point cloud was assigned to a Digital Surface Model (DSM), and a Canopy Height Model (CHM) was acquired. Then, four algorithms (point-cloud-based local maximum algorithm, CHM-based local maximum algorithm, watershed algorithm, and template-matching algorithm) were comparatively used to extract the structural parameters of individual trees. The results indicated that the two local maximum algorithms can effectively detect the treetop; the watershed algorithm can accurately extract individual tree height and determine the tree crown edge; and the template-matching algorithm works well to extract accurate crown width. This study provides a reference for the selection of algorithms in individual tree parameter inversion based on airborne LiDAR data and is of great significance for LiDAR-based forest monitoring and management. View Full-Text
Keywords: LiDAR; DEM; CHM; individual tree position; tree height; crown width LiDAR; DEM; CHM; individual tree position; tree height; crown width
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MDPI and ACS Style

Chen, W.; Xiang, H.; Moriya, K. Individual Tree Position Extraction and Structural Parameter Retrieval Based on Airborne LiDAR Data: Performance Evaluation and Comparison of Four Algorithms. Remote Sens. 2020, 12, 571.

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