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A Comparison of LiDAR Filtering Algorithms in Vegetated Mountain Areas

文献类型：期刊论文

作者Zhao, Xiaoqian3; Su, Yanjun4; Li, WenKai1; Hu, Tianyu; Liu, Jin; Guo, Qinghua3,4
刊名CANADIAN JOURNAL OF REMOTE SENSING
出版日期2018
卷号44期号:4页码:287-298
ISSN号0703-8992
DOI10.1080/07038992.2018.1481738
文献子类Article
英文摘要Filtering of airborne light detection and ranging (LiDAR) data is a challenging task in vegetated mountain areas. Environmental features and LiDAR data characteristics have significant impacts on the performance of filtering algorithms. This study aims to determine the effects of topographic and environmental features such as slope, canopy cover, elevation variability, and LiDAR point density on five widely used filtering algorithms, including multi-scale curvature classification (MCC), interpolation-based filtering (IBF) algorithm, morphological filtering (MF) algorithm, progressive triangulated irregular network densification filtering (PTDF) algorithm, and slope-based filtering (SBF). The results show that the performances of these filtering algorithms are all significantly influenced by the chosen factors, but the dominant influential factor varies with algorithms. The MCC works well in steep and dense forests; IBF and MCC outperform the rest of filtering algorithms in areas with steep terrain but low vegetation coverage; and PTDF is more reliable for low-density LiDAR data. Our results can provide guidance for choosing the appropriate filtering algorithm based on the specific topographic and environmental features of a study area.
学科主题Remote Sensing
出版地PHILADELPHIA
电子版国际标准刊号1712-7971
WOS关键词AIRBORNE LIDAR ; DEM GENERATION ; CLASSIFICATION ; FOREST ; SEGMENTATION ; EXTRACTION ; ELEVATION ; MODEL
语种英语
WOS记录号WOS:000461864500003
出版者TAYLOR & FRANCIS INC
资助机构National Key R&D Program of China [2017YFC0503905, 2016YFC0500202] ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [41471363, 31741016] ; Frontier Science Key Programs of the Chinese Academy of Sciences [QYZDY-SSW-SMC011] ; CAS Pioneer Hundred Talents Program ; US National Science FoundationNational Science Foundation (NSF) [EAR 0922307]
源URL[http://ir.ibcas.ac.cn/handle/2S10CLM1/20582]  
专题植被与环境变化国家重点实验室
作者单位1.Univ Calif Merced, Sierra Nevada Res Inst, Merced, CA 95343 USA
2.Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou 510275, Guangdong, Peoples R China
3.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China
4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714		 Zhao, Xiaoqian,Su, Yanjun,Li, WenKai,et al. A Comparison of LiDAR Filtering Algorithms in Vegetated Mountain Areas[J]. CANADIAN JOURNAL OF REMOTE SENSING,2018,44(4):287-298.
APA Zhao, Xiaoqian,Su, Yanjun,Li, WenKai,Hu, Tianyu,Liu, Jin,&Guo, Qinghua.(2018).A Comparison of LiDAR Filtering Algorithms in Vegetated Mountain Areas.CANADIAN JOURNAL OF REMOTE SENSING,44(4),287-298.
MLA Zhao, Xiaoqian,et al."A Comparison of LiDAR Filtering Algorithms in Vegetated Mountain Areas".CANADIAN JOURNAL OF REMOTE SENSING 44.4(2018):287-298.

入库方式： OAI收割

来源：植物研究所

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