[an error occurred while processing this directive] Global Geology 2018, 21(3) 194-202 DOI:   10.3969/j.issn.1673-9736.2018.03.05  ISSN: 1673-9736 CN: 22-1371/P
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airborne LiDAR
urban vegetation points
two-dimensional grid mesh
mean-square error
successive differences
iterative algorithm
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PubMed
A new approach of extracting vegetation points from urban airborne LiDAR data
CUI Shaochen1, YANG Yuanxin2, YANG Guodong1, ZHANG Xuqing1
1. College of Geo-Exploration Science and Technology, Jilin University, Changchun 130021, China;
2. Air Force Academy Institute of Engineering Design, Beijing 100068, China
ժҪ�� Urban vegetation has been an important indicator for the evaluation of eco-cities, which is of great significance to promote eco-city construction. We study and discuss the commonly used urban vegetation extraction methods. The extraction of vegetation points in this study is completed through mathematical statistics, mean-square error, successive differences and iterative algorithm which are based on the analysis of different spatial morphological characteristics in urban point clouds. Linyi, a city of Shandong Province in China, is selected as the study area to test this method and the result shows that the proposed method has a strong practicality in urban vegetation point cloud extraction. Only 3D coordinate properties of the LiDAR point clouds are used in this method and it does not require additional information, for instance, return intensity, which makes the method more applicable and operable.
�ؼ����� airborne LiDAR   urban vegetation points   two-dimensional grid mesh   mean-square error   successive differences   iterative algorithm  
A new approach of extracting vegetation points from urban airborne LiDAR data
CUI Shaochen1, YANG Yuanxin2, YANG Guodong1, ZHANG Xuqing1
1. College of Geo-Exploration Science and Technology, Jilin University, Changchun 130021, China;
2. Air Force Academy Institute of Engineering Design, Beijing 100068, China
Abstract: Urban vegetation has been an important indicator for the evaluation of eco-cities, which is of great significance to promote eco-city construction. We study and discuss the commonly used urban vegetation extraction methods. The extraction of vegetation points in this study is completed through mathematical statistics, mean-square error, successive differences and iterative algorithm which are based on the analysis of different spatial morphological characteristics in urban point clouds. Linyi, a city of Shandong Province in China, is selected as the study area to test this method and the result shows that the proposed method has a strong practicality in urban vegetation point cloud extraction. Only 3D coordinate properties of the LiDAR point clouds are used in this method and it does not require additional information, for instance, return intensity, which makes the method more applicable and operable.
Keywords: airborne LiDAR   urban vegetation points   two-dimensional grid mesh   mean-square error   successive differences   iterative algorithm  
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DOI: 10.3969/j.issn.1673-9736.2018.03.05
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