基于地面激光雷达点云数据的单木三维重建

doi:10.11873/j.issn.1004-0323.2015.3.0455

遥感技术与应用

2015, Vol. 30

Issue (3): 455-460 DOI: 10.11873/j.issn.1004-0323.2015.3.0455

模型与反演

基于地面激光雷达点云数据的单木三维重建

王向玉,谢东辉,汪艳,陈一铭,漆建波,阎广建,张吴明

(北京师范大学遥感科学国家重点实验室,环境遥感与数字城市北京市重点实验室,
地理学与遥感科学学院,北京 100875)

3D Reconstruction of a Single Tree from Terrestrial Laser Scanner Data

Wang Xiangyu,Xie Donghui,Wang Yan,Chen Yiming,Qi Jianbo,Yan Guangjian,Zhang Wumin

(State Key Laboratory of Remote Sensing Science,Beijing Key Laboratory of Environmental Remote
Sensing and Digital City,and School of Geography,Beijing Normal University.Beijing 100875,China)

全文: PDF(3349 KB)

摘要：

利用地面激光雷达三维点云数据,在已有的枝干结构重建方法基础上,提出了一种利用点云密度,结合间隙率模型反演的单木总叶面积,在冠层内分体元添加树叶的方法,重建完整的单木三维结构。该方法成功应用于基于光线追踪方法模拟的点云和野外实测点云数据,实现了单木三维结构重构。重建的单木叶面积与真实叶面积相对误差小于0.9%,方向间隙率的相对误差不超过4.0%。实验结果表明:重建单木三维结构与真实结构在目视效果和定量评价两方面都具有较好的一致性。

关键词： 点云; 激光雷达; 单木; 三维重建; 树叶

Abstract:

Terrestrial LiDAR systems have received lots of attention on three\|dimensional (3D) structure reconstruction for trees,especially on the branch skeleton generation.On the basis,a method is proposed to add leaves structure based on point density by dividing small cube in the canopy to reduce the influence of uneven distribution of point cloud,and combine gap fraction model to retrieval leaf area of a tree using terrestrial LiDAR data.It is successfully applied to reconstruct 3D trees using points simulated data by ray tracing algorithm as well as field measured points data.The relative error of leaf area between reconstructed and real structure is less than 0.9%.Meanwhile,the most relative error of directional gap fraction is also less than 4.0%.The experimental results prove that the method has gotten a satisfied consistency on visual sense and quantitative evaluation between the 3D structure reconstructed and real structure.In quantitative remote sensing,the method has lots of application values for simulation of canopy radiative transfer process as well as visualization.

Key words: Point cloud LiDAR Single tree 3D reconstruction Leaf

收稿日期: 2014-01-20 出版日期: 2015-08-14

P 237

基金资助:

国家973计划项目(2013CB733402),国家自然科学基金项目(41071224),自由探索项目(13ZY-08)资助。

通讯作者: 谢东辉（1976-）,女,北京人,硕士生导师,主要从事定量遥感研究。Email:xiedonghui@bnu.edu.cn。

作者简介: 王向玉（1988-）,女,吉林榆树人,硕士研究生,主要从事植被计算机模拟方面的研究。Email:xiangyuwang@mail.bnu.edu.cn。

	服务
	把本文推荐给朋友
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	王向玉
	谢东辉
	汪艳
	陈一铭
	漆建波
	阎广建
	张吴明

引用本文:

王向玉,谢东辉,汪艳,陈一铭,漆建波,阎广建,张吴明. 基于地面激光雷达点云数据的单木三维重建[J]. 遥感技术与应用, 2015, 30(3): 455-460.

Wang Xiangyu,Xie Donghui,Wang Yan,Chen Yiming,Qi Jianbo,Yan Guangjian,Zhang Wumin. 3D Reconstruction of a Single Tree from Terrestrial Laser Scanner Data. Remote Sensing Technology and Application, 2015, 30(3): 455-460.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2015.3.0455 或 http://www.rsta.ac.cn/CN/Y2015/V30/I3/455

［1］Curran P J,Dungan J L.Estimation of Signal-to-noise:A New Procedure Applied to AVIRIS Data［J］.IEEE Transactions on Geoscience and Remote Sensing,1989,27(5):620-628.

［2］Van Der Meer F D,De Jong S M.Imaging Spectrometry:Basic Principles and Prospective Applications［M］.Dordrecht:Kluwer Academic Publishers,2003:35-36.

［3］Zhu Bo,Wang Xinhong,Tang Lingli,et al.Review on Methods for SNR Estimation of Optical Remote Sensing Imagery［J］.Remote Sensing Technology and Application,2010,25(2):303-309.［朱博,王新鸿,唐伶俐,等.光学遥感图像信噪比评估方法研究进展［J］.遥感技术与应用,2010,25(2):303-309.］

［4］Duggin M J,Sakhavat H,Lindsay J.Systematic and Random Variations in Thematic Mapper Digital Radiance Data［J］.Photogrammetric Engineering & Remote Sensing,1985,51(12):1427-1434.

［5］Atkinson P M.Technical Note on Estimating Measurement Error in Remotely Sensed Images with the Variogram［J］.International Journal of Remote Sensing,1997,18(14):3075-3084.

［6］Atkinson P M,Sargent I M,Foody G M,et al.Interpreting Image-based Methods for Estimating the Signal-to-noise Ratio［J］.International Journal of Remote Sensing,2005,26(22):5099-5115.

［7］Atkinson P M,Sargent I M,Foody G M,et al.Exploring the Geostatistical Method for Estimating the Signal-to-Noise Ratio of Images［J］.Photogrammetric Engineering & Remote Sensing,2007,73(7):841-850.

［8］Asmat A,Atkinson P M,Foody G M.Geostatistically Estimated Image Noise Is a Function of Variance in the Underlying Signal［J］.International Journal of Remote Sensing,2010,31(4):1009-1025.

［9］Lee J S,Hoppel K.Noise Modeling and Estimation of Remotely-sensed Images［C］//IEEE Geoscience and Remote Sensing Symposium,Vancouver,1989:1005-1008.

［10］Gao B C.An Operational Method for Estimating Signal to Noise Ratios from Data Acquired with Imaging Spectrometers［J］.Remote Sensing of Environment,1993,43:23-33.

［11］Meer P,Jolion J M,Rosenfeld A.A Fast Parallel Algorithm for Blind Estimation of Noise Variance［J］.IEEE Transactions on Pattern Analysis and Machine Intelligence,1990,12(2):216-223.

［12］Roger R E,Arnold J F.Reliably Estimating the Noise in AVIRIS Hyperspectral Images［J］.International Journal of Remote Sensing,1996,17(10):1951-1962.

［13］Delvit J M,Leger D,Roques S,et al.Signal to Noise Ratio Assessment from Non Specific Views［C］//Image and Signal Processing for Remote Sensing,Toulouse,2002:370-381.

［14］Gao Lianru,Zhang Bing,Zhang Xia,et al.Study on the Method for Estimating the Noise in Remote Sensing Images based on Local Standard Deviations［J］.Journal of Remote Sensing,2007,11(2):201-208.［高连如,张兵,张霞,等.基于局部标准差的遥感图像噪声评估方法研究［J］.遥感学报,2007,11(2):201-208.］

［15］Baltsavias E,Pateraki M,Zhang L.Radiometric and Geometric Evaluation of IKONOS Geo Images and Their Use for 3D Building Modeling［C］//Joint ISPRS Workshop “High Resolution Mapping from Space 2001”,Hannover,2001:1-21.

［16］Crespi M,De Vendictis L.A Procedure for High Resolution Satellite Imagery Quality Assessment［J］.Sensors,2009,9:3289-3313.

[1]	廖凯涛，齐述华，王成，王点. 结合GLAS和TM卫星数据的江西省森林高度和生物量制图[J]. 遥感技术与应用, 2018, 33(4): 713-720.
[2]	虢韬，沈平，时磊. 机载LiDAR快速定位高压电塔方法研究[J]. 遥感技术与应用, 2018, 33(3): 530-535.
[3]	孟庆岩，孙云晓，张佳晖，等. 基于多源遥感的建筑区绿化垂直分布特征与空间配置分析——以匈牙利塞克什白堡市为例[J]. 遥感技术与应用, 2018, 33(2): 370-376.
[4]	梁茜茜，张汉德，孙根云，王鹏. 基于机载激光雷达数据的海岸带水域提取方法[J]. 遥感技术与应用, 2018, 33(1): 136-142.
[5]	王濮，邢艳秋，王成，习晓环，骆社周. 机载LiDAR数据提取山区道路方法研究[J]. 遥感技术与应用, 2017, 32(5): 851-857.
[6]	何原荣,郑渊茂,潘火平,陈鉴知. 基于点云数据的复杂建筑体真三维建模与应用[J]. 遥感技术与应用, 2016, 31(6): 1091-1099.
[7]	董立新. 林分平均高度卫星遥感新进展[J]. 遥感技术与应用, 2016, 31(5): 833-845.
[8]	秦海明,王成,习晓环,聂胜. 机载激光雷达测深技术与应用研究进展[J]. 遥感技术与应用, 2016, 31(4): 617-624.
[9]	汪骏,夏少波,王和平,王成,谭弘武. 基于直升机激光点云的分裂导线重建研究[J]. 遥感技术与应用, 2015, 30(6): 1189-1194.
[10]	李文娟,赵传燕,别强,高婵婵,高云飞. 基于机载激光雷达数据的森林结构参数反演[J]. 遥感技术与应用, 2015, 30(5): 917-924.
[11]	曾祥钊,李传荣,张正,周梅. 面向海量点云快速显示的叠加型金字塔索引结构研究[J]. 遥感技术与应用, 2015, 30(3): 534-539.
[12]	穆喜云,张秋良,刘清旺,庞勇,胡凯龙. 基于激光雷达的大兴安岭典型森林生物量制图技术研究[J]. 遥感技术与应用, 2015, 30(2): 220-225.
[13]	化蕾,黄洪宇,陈崇成,黄淑华. 基于激光点云数据的客家土楼三维建模[J]. 遥感技术与应用, 2015, 30(1): 115-122.
[14]	骆社周,习晓环,王成. 激光雷达遥感在文化遗产保护中的应用[J]. 遥感技术与应用, 2014, 29(6): 1054-1059.
[15]	孙美玲,李永树,陈强. 航空影像辅助下的城区机载LiDAR汽车目标检测方法[J]. 遥感技术与应用, 2014, 29(5): 886-890.

Viewed

Full text

Abstract

Cited

Shared

Discussed