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遥感技术与应用  2013, Vol. 28 Issue (4): 562-568    DOI: 10.11873/j.issn.1004-0323.2013.4.562
遥感应用     
基于机载LiDAR和高分辨率遥感影像的城市道路网提取
高利鹏1,2,史文中3,吕志勇4,张华1,2
(1.中国矿业大学(徐州)国土环境与灾害监测国家测绘局重点实验室,江苏 徐州 221116;
2.中国矿业大学(徐州)环境与测绘学院,江苏 徐州 221116;
3.香港理工大学土地测量及地理资讯学系,香港;
4.武汉大学遥感信息工程学院,湖北 武汉 430079)
Road Network Extraction based on Airborne LiDAR and High Resolution Remote Sensing Imagery
Gao Lipeng1,2,Shi Wenzhong3,Lv Zhiyong4,Zhang Hua1,2
(1.Key Laboratory for Terrestrial Environment and Geohazards Monitoring of State Bureau of
Surveying and Mapping,China University of Mining and Technology,Xuzhou 221116,China;
2.School of Environment Science and Spatial Informatics,China University of Mining and
Technology,Xuzhou 221116,China;3.Department of Land Surveying and Geo-Informatics,
The Hong Kong Polytechnic University,Koowloon,Hong Kong;
4.School of Remote Sensing and Information Engineering,Wuhan University,Wuhan 430079,China)
 全文: PDF(3086 KB)  
摘要:

利用单个数据源的数学形态学道路提取方法不能充分利用道路的特征,提取的道路信息不完整。针对这一缺陷,并考虑到机载LiDAR数据可以提供高程信息,提出了将机载LiDAR数据和高分辨率遥感影像数据结合起来的城市道路网的提取方法。以徐州市的机载LiDAR数据和高分辨率遥感影像数据作为实验数据,首先将两者进行精确配准,然后利用伪道路信息去除的方法分别将植被信息和建筑物信息等去除,得到基本的道路轮廓,再利用形态细化算法提取道路的中心线,最后,在ArcGIS和Matlab编程环境下实现了改进的道路修剪算法(IRT),利用该算法进行道路修剪,得到了平滑和连贯的城市道路网。经过精度评价可以看出:利用该方法可以较好地避免建筑物阴影、低矮植被群等对道路提取的影响,道路的识别精度达到84%以上。

关键词: LiDAR高分辨率遥感影像道路网提取伪信息去除数学形态学影像配准    
Abstract:

The conventional mathematical morphology method using single data source to extract road network which could not take full advantage of the road characteristics,the extracted road information was not complete.In view of this drawback,and base on the airborne LiDAR data can provide elevation information,this paper proposes a method which combines the airborne LiDAR data with high resolution remote sensing images to extract city road network.The airborne LiDAR data and high resolution remote sensing QuickBird images of Xuzhou were taken as the experimental data,the precise registration between them were first done,then the FRIR (False Road Information Removing) method was used to remove the vegetation and buildings separately,so the basic road contour was displayed.Finally,this paper achieved an Improved Road Trimming (IRT) algorithm under the ArcGIS and Matlab programming environment,the road network was trimmed by the algorithm,then a smooth and continuous city road network was obtained.The result of the accuracy evaluation indicates that the method was proposed can be used to avoid the influence of the building shadow,city squares,parking lots and the vegetation groups on both sides of the road to the road centerlines extraction well,and the recognition accuracy of the road network is more than 84%.

Key words: LiDAR    High resolution remote sensing images    Road network extraction    False road information removing    Mathematical morphology    Image registration
收稿日期: 2012-06-29 出版日期: 2013-08-14
:  TP 751  
基金资助:

国家863计划项目(2012AA12A305),国家“十二五”科技支撑技术项目(2012BAJ15B04),江苏省普通高校研究生科研创新计划资助项目(CX10B_143Z,CXLX12_0956),江苏高校优势学科建设工程资助项目。

作者简介: 高利鹏(1989-),男,河南平顶山人,硕士研究生,主要从事高分辨率遥感影像处理与特征提取方面的研究。Email:gaolipengcumt@163.com。
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引用本文:

高利鹏,史文中,吕志勇,张华. 基于机载LiDAR和高分辨率遥感影像的城市道路网提取[J]. 遥感技术与应用, 2013, 28(4): 562-568.

Gao Lipeng,Shi Wenzhong,Lv Zhiyong,Zhang Hua. Road Network Extraction based on Airborne LiDAR and High Resolution Remote Sensing Imagery. Remote Sensing Technology and Application, 2013, 28(4): 562-568.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2013.4.562        http://www.rsta.ac.cn/CN/Y2013/V28/I4/562

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