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

doi:10.1016/j.isprsjprs.2016.03.016

CORC > 植物研究所 > 中国科学院植物研究所 > 植被与环境变化国家重点实验室

	Improved progressive TIN densification filtering algorithm for airborne LiDAR data in forested areas
	Zhao, Xiaoqian 3; Guo, Qinghua 1; Su, Yanjun 1; Xue, Baolin
刊名	ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
	2016
卷号	117 页码:79-91
关键词	Light detection and ranging Ground filtering Ground points Triangulated irregular network Digital terrain model
ISSN号	0924-2716
DOI	10.1016/j.isprsjprs.2016.03.016
文献子类	Article
英文摘要	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.
学科主题	Geography, Physical ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
电子版国际标准刊号	1872-8235
出版地	AMSTERDAM
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)
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000377312500007
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]
内容类型	期刊论文
源URL	[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.Univ Chinese Acad Sci, 19A Yuquan Rd, Beijing 100049, Peoples R China 2.Univ Calif Merced, Sch Engn, Sierra Nevada Res Inst, Merced, CA 95343 USA 3.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China
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.