Improved progressive TIN densification filtering algorithm for airborne LiDAR data in forested areas

doi:10.1016/j.isprsjprs.2016.03.016

	Improved progressive TIN densification filtering algorithm for airborne LiDAR data in forested areas
	Zhao, Xiaoqian 1; Guo, Qinghua2 ; Su, Yanjun 2; Xue, Baolin
	2016
发表期刊	ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
ISSN	0924-2716
卷号	117 页码:79-91
摘要	Filtering of light detection and ranging (LiDAR) data into the ground and non-ground points is a fundamental step in processing raw airborne LiDAR data. This paper proposes an improved progressive triangulated irregular network (TIN) densification (IPTD) filtering algorithm that can cope with a variety of forested landscapes, particularly both topographically and environmentally complex regions. The IPTD filtering algorithm consists of three steps: (1) acquiring potential ground seed points using the morphological method; (2) obtaining accurate ground seed points; and (3) building a TIN-based model and iteratively densifying TIN. The IPTD filtering algorithm was tested in 15 forested sites with various terrains (i.e., elevation and slope) and vegetation conditions (i.e., canopy cover and tree height), and was compared with seven other commonly used filtering algorithms (including morphology-based, slope-based, and interpolation-based filtering algorithms). Results show that the IPTD achieves the highest filtering accuracy for nine of the 15 sites. In general, it outperforms the other filtering algorithms, yielding the lowest average total error of 3.15% and the highest average kappa coefficient of 89.53%. (C) 2016 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.
关键词	Light detection and ranging Ground filtering Ground points Triangulated irregular network Digital terrain model
学科领域	Geography, Physical ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
DOI	10.1016/j.isprsjprs.2016.03.016
收录类别	SCI
语种	英语
WOS关键词	SCANNING POINT CLOUDS ; MORPHOLOGICAL FILTER ; CRITICAL-ISSUES ; DEM GENERATION ; DTM GENERATION ; TERRAIN ; SEGMENTATION
WOS研究方向	Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号	WOS:000377312500007
出版者	ELSEVIER SCIENCE BV
文献子类	Article
出版地	AMSTERDAM
EISSN	1872-8235
资助机构	National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [41471363, 31270563] ; National Key Basic Research Program of ChinaNational Basic Research Program of China [2013CB956604] ; National Science FoundationNational Science Foundation (NSF) [DBI 1356077]
作者邮箱	zhaoxiaoqian@ibcas.ac.cn ; guo.qinghua@gmail.com ; ysu3@ucmerced.edu ; xuebaolin@ibcas.ac.cn
作品OA属性	Bronze
引用统计	被引频次：206[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ibcas.ac.cn/handle/2S10CLM1/25168
专题	植被与环境变化国家重点实验室
作者单位	1.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China 2.Univ Chinese Acad Sci, 19A Yuquan Rd, Beijing 100049, Peoples R China 3.Univ Calif Merced, Sch Engn, Sierra Nevada Res Inst, Merced, CA 95343 USA
推荐引用方式 GB/T 7714	Zhao, Xiaoqian,Guo, Qinghua,Su, Yanjun,et al. Improved progressive TIN densification filtering algorithm for airborne LiDAR data in forested areas[J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,2016,117:79-91.
APA	Zhao, Xiaoqian,Guo, Qinghua,Su, Yanjun,&Xue, Baolin.(2016).Improved progressive TIN densification filtering algorithm for airborne LiDAR data in forested areas.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,117,79-91.
MLA	Zhao, Xiaoqian,et al."Improved progressive TIN densification filtering algorithm for airborne LiDAR data in forested areas".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 117(2016):79-91.

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