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A Voxel-Based Method for Automated Identification and Morphological Parameters Estimation of Individual Street Trees from Mobile Laser Scanning Data.

Authors :
Bin Wu
Bailang Yu
Wenhui Yue
Song Shu
Wenqi Tan
Chunling Hu
Yan Huang
Jianping Wu
Hongxing Liu
Source :
Remote Sensing. Feb2013, Vol. 5 Issue 2, p584-611. 28p. 16 Diagrams, 2 Graphs.
Publication Year :
2013

Abstract

As an important component of urban vegetation, street trees play an important role in maintenance of environmental quality, aesthetic beauty of urban landscape, and social service for inhabitants. Acquiring accurate and up-to-date inventory information for street trees is required for urban horticultural planning, and municipal urban forest management. This paper presents a new Voxel-based Marked Neighborhood Searching (VMNS) method for efficiently identifying street trees and deriving their morphological parameters from Mobile Laser Scanning (MLS) point cloud data. The VMNS method consists of six technical components: voxelization, calculating values of voxels, searching and marking neighborhoods, extracting potential trees, deriving morphological parameters, and eliminating pole-like objects other than trees. The method is validated and evaluated through two case studies. The evaluation results show that the completeness and correctness of our method for street tree detection are over 98%. The derived morphological parameters, including tree height, crown diameter, diameter at breast height (DBH), and crown base height (CBH), are in a good agreement with the field measurements. Our method provides an effective tool for extracting various morphological parameters for individual street trees from MLS point cloud data. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
5
Issue :
2
Database :
Academic Search Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
85818298
Full Text :
https://doi.org/10.3390/rs5020584